Are we cooked? We’re going to be revisiting this question quarterly now, it seems. To discuss, we have Peter Harrell, former Biden official and host of the excellent new Security Economics podcast, Kevin Xu, who writes the Interconnected newsletter, and Matt Klein, author of Trade Wars Are Class Wars and The Overshoot substack.

We discuss…

• Short-term positive indicators, including the stock market rebound, the continued independence of the Federal Reserve, and the administration’s compliance with court rulings,

• Why talent is the ultimate bottleneck to AI progress, and how the attacks on foreign students, universities, and scientific research will impact America long term,

• Whether Trump’s policies will cause mass divestment from dollar-denominated assets,

• The state of U.S. alliances, from the apparent thawing of relations with NATO and Zelenskyy, to signs of friction with Japan,

• Next steps for Trump’s industrial policy.

Listen now on iTunes, Spotify, or your favorite podcast app.

Dollar Depreciation and Self-Inflicted Brain Drain

Jordan Schneider: Peter, kick us off.

Peter Harrell: We did this last quarter in late April, and looking around the short term over the last three months, the indicators are decent. We’re looking less cooked. Trump TACO’d out on a lot of the tariff wars, so the stock market rebounded. He can post memes about bombing Iran and get away with it — the short-term indicators actually suggest the last couple of months have gone decently well for the United States from a big picture perspective.

However, I’m pretty concerned about the long-term trajectories. Looking at some of the core things that have made the US what it is today — substantial investment in scientific R&D, attracting talent from around the world to do science and innovation, business leadership here in the United States, and the social fabric we have — I remain worried about whether we’re cooked long term, even though I have to give some credit to the last three months.

Kevin Xu: To add onto what you just said, Peter, in preparation for this podcast, I looked at the value of the dollar chart because I remember we brought it up the last time we talked about this. It went down by another 5 to 6 percent from our last recording to today. That was one of the biggest conundrums at the time. Right after Liberation Day, everyone who thinks about tariffs in perhaps the most conventional way would expect the dollar to go up, everything else being equal.

But the erosion of the dollar, no matter how you want to slice it, continues slowly but surely going down. It’s no longer a big story because there have been so many other attention-grabbing geopolitical and economic stories since then. But for me, that’s something I’m going to watch from time to time as this collective “how does the world vote with their feet” question regarding how much credibility they place in the United States government and leadership through how they treat the dollar.

Matt Klein: The overall level of “cookedness” has not actually changed much one way or another. Partly because I discounted the damage from the tariffs. Not that the tariffs announced on April 2nd were good, but that was never the main issue. The attacks on scientific research, the attacks on foreigners coming into the country — and we’re not just talking about changes in Southern border policy, but the way European tourists are treated — across the board restrictions on foreign students coming into universities, the attacks on the rule of law — these things have not abated in any way.

There has been ongoing pushback from courts, but many things remain problematic. The changes to scientific research policy, the changes to approaches on medical research funding in particular and vaccinations — that has not improved in the past few months. If anything, it’s been entrenched.

If I wanted to be more pessimistic, I would say the fact that immediate concerns about things such as tariffs have subsided and the stock market has recovered might actually reduce the pressure to unwind those longer-term, more damaging policy changes that have occurred over the past six months, making them more likely to persist. Even if the immediate impact is not necessarily substantial, it could be a very long-term drag, not just on GDP growth, but on the quality of life, power, and well-being in this country.

The analogy is Brexit. When the UK was voting about whether to leave or remain in the European Union, there were concerns — people called this “project fear” — about an immediate catastrophe if they voted to leave. That didn’t happen, so people said the case was overstated. But the more realistic and correct argument was that everything would be worse — not catastrophically worse, but persistently worse over time. That has been borne out. I fear we’re ending up in a similar, if not worse, situation as a result of all this.

Jordan Schneider: I’m going to take the other side of this argument. Many of the worst-case scenarios we were contemplating in April are much less likely to manifest now. I’m taking Brexit as a win, if that is our analogy, as opposed to something even more dramatic.

Elon is done. DOGE’s energy is abating for the most part, which I think is positive for governance and civil service. We have Congress — maybe they’ll pass a bill — it doesn’t look great, but it’s also not republic-wrecking. There’s going to be an election not that long from now.

On the immigration side, yes, the direction of travel is not great, but we have not banned all foreign students. The country bans that we’ve seen and will continue to see are directionally problematic, but we could have had much more aggressive paths that would have presaged an even more aggressive four years, which have not happened. You’ve even seen Trump at one point tweeting about protecting the farmers, saying we can’t kick out all of our undocumented immigrants.

It’s not just on trade where this administration has blinked. It seems there are other topics — science accepted, we’re in a pretty poor timeline on that front — but at least on the immigration front, it seems we could be in a worse place than where we are now.

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Peter Harrell: I’ll add two points, one on each side of the ledger, building on what you’ve both said.

On the positive side, Trump appears to be stepping back from the brink, at least somewhat, on whether he’s going to outright defy the courts. That felt more real to me a couple of months ago. He did bring home the individual who was sent to El Salvador and charged with crimes — a complicated issue. But he does seem to be stepping back from his showdown with the judiciary, though time will tell. I’d put that in the positive ledger.

On the other side are things that are eroding U.S. centrality in the international economic system, at least long term. I want to pick up where Kevin left off on the decline in the dollar’s value. We’re seeing several other data points where foreign governments and private parties have quadrupled or quintupled their efforts to create financial networks substantially outside U.S. jurisdiction.

You see this in the drop in the dollar’s value — investors are clearly beginning to pull back from the United States. You also see it in the large run-up in gold prices. This 3,000-year-old store of value has had an explosive couple of months, building on a strong year or two, driven very much by central bank purchases of gold as a way of hedging and reducing their exposure to the dollar.

But perhaps moving to gold isn’t even enough. There’s now a debate in Europe, in Germany and Italy, about whether they need to repatriate their gold reserves — which are currently stored deep in the rock underneath Manhattan, in the custody of the New York Fed — because they don’t even trust us as custodians of their gold anymore.

This is a significant data point. Now, it’s not easy to develop large-scale financial networks outside the U.S. — it’s very hard and doesn’t happen overnight. We’re still seeing foreign investment here, and we’ll still attract the capital levels we need. But this foreign government distrust about the long-term stability of the United States, whether right or wrong, is driving something that you’re beginning to see in the numbers.

Matt Klein: I might push back on that a little because while that intuitively makes sense, the numbers aren’t necessarily showing something as extreme as one might have expected.

The dollar depreciation was sharp around April 2nd, but if we zoom out, the dollar is still quite expensive on a trade-weighted basis relative to the rest of the world. It’s still up something like 20 percent compared to early 2021, up 30 percent compared to 2014. It’s still quite expensive — maybe not quite as expensive as before.

Foreign investors had been massively overweight in U.S. assets. On a market cap basis, they were equally weighted, but 70 percent of stock market capitalization being American feels odd given that the U.S. economy is a quarter of the world economy. Yes, American companies may be more profitable, but still, there were plenty of reasons why, with more benign catalysts, you would have seen some of these market moves, particularly on exchange rates or foreign allocations.

In some ways, the story is that there hasn’t been as much of a move yet. I agree that if the Germans and Italians move their gold, that’s symbolically interesting, although what that means in practice is debatable. But it’s striking what hasn’t happened, which is honestly surprising.

The same thing applies on the U.S. side — have Americans been moving a lot of money out of the U.S. into foreign assets? Maybe some, but it’s not super clear in the data that it’s been enormous volumes of the kind you would have expected.

We have other examples of countries with sharp moves in response to political instability — Turkey in March, for example, after the arrest of the mayor of Istanbul. There was a very sharp move, actually a similar-sized move in the exchange rate for the Turkish lira as for the dollar. But in terms of the quantities of what was actually happening, it was on a much different scale. Turkey’s central bank only has $40 billion in reserves to keep the currency stable. We didn’t see that here.

As much as it would be logical to say that’s what’s happening, I don’t think we’ve seen it yet. Maybe we will; maybe it’ll be more gradual. The gold price move is certainly interesting, although that really dates back to the sanctions on Russia’s central bank when that trend began. Otherwise, it’s hard to see it as a dollar-specific story.

Jordan Schneider: Matt, we’re doing better on the Fed, right? That was a news story that completely burned itself out. I think we’ll have a Fed come 2028.

Matt Klein: Maybe. This is the other thing — I talk about the independent Fed, the independent judiciary, but these are Senate-confirmed positions. It’s not clear to me what kind of pushback the Senate would provide if you have a Trump-supporting majority there.

The judiciary we have now is not necessarily the judiciary we’ll have four years from now. That could change. The Fed situation could change. If I remember correctly, there’s a passage in the big, beautiful bill they’re putting through that basically says administration officials would be immune from contempt of Congress. I’ll defer to the lawyers on the exact terminology, but there are things being done by the other branch of government to support the potential for further executive overreach, which should be concerning even if it’s not necessarily generating the same kind of headlines and market responses as tariffs.

Peter Harrell: In fairness, I said a couple of minutes ago that Trump is stepping back from his confrontation with the judiciary in a noticeable way, though the long-term impact remains to be determined. Part of that is because he’s winning. He’s making the assessment that he can win at least a large enough percentage of his cases in front of the judiciary.

We saw that today, at least temporarily, with what the Supreme Court did on nationwide injunctions and birthright citizenship. He’s essentially saying, “If I’m winning two-thirds of my big cases in the courts, maybe I don’t need to outright confront or defy them over the third that I’m losing."

As a lawyer, I’ll take compliance with judicial rulings. That’s all I’m saying.

Jordan Schneider: Peter, give us the “tariffs are actually illegal” update.

Peter Harrell: This is one near and dear to my heart. Most of Trump’s tariffs — certainly all of the Liberation Day tariffs from April that caused significant market turmoil — weren’t imposed under a trade law statute. He imposed these tariffs under a 1977 emergency powers statute that previous presidents had used for sanctions on Iran and Russia. It had never previously been used for tariffs.

This is progressing through the court system. There’s a specialty district court in New York called the Court of International Trade. Plaintiffs challenging these tariffs won at the specialty district court, but that victory is on hold while the government and plaintiffs deal with an appeal before the Federal Circuit, one of the federal appellate courts.

The Federal Circuit will have its hearings on this case on July 31st. We’ll likely get an opinion from the Federal Circuit by the end of August, and then this will go up to the Supreme Court in the fall.

If I were betting, I would bet Trump loses on the merits here. At the end of the day, these tariffs are going to be found unlawful. That doesn’t mean the end of all tariffs — it means a mad scramble across the U.S. government to see what tariffs they can recreate under other legal authorities.

Matt Klein: They’ve been doing that with Section 232. The 50 percent tariff on steel isn’t being challenged. The pharma tariffs in the pipeline are now separate.

Kevin Xu: There’s your alpha for the episode.

Peter Harrell: For those thinking about this from a market perspective, one thing that’s going to happen is that companies paying the tariffs this year will get a rebate. They’ll be entitled to a rebate of paid unlawful tariffs, which would probably happen next year. From a market perspective, you’ll see an earnings shift from this year to next year as they get rebates of tariffs paid this year, which they’ll then have to pay going forward again. Retroactively, 2025 might look better on earnings than it does right now.

Matt Klein: Are the tariffs tax-deductible? Are tariff payments deductible against income tax? Is the rebate going to be taxed?

Peter Harrell: I’m not a tax lawyer — that’s a good question. It’s certainly a business expense, so you can claim it as such.

Kevin Xu: They’re not going to tax tips.

Peter Harrell: How to tax this is full employment for lawyers. That’s Trump trade policy 101 — full employment for lawyers.

Talent > Transistors

Jordan Schneider: Kevin, how about an AI update?

Kevin Xu: One thing in the AI world — whether it’s investment or technological progress — speaks to how equipped the U.S. is. I’m not necessarily saying China will lead or run the table — I’m analyzing our country specifically.

CapEx is growing for at least another one or two years. The AI trade is on. But everyone’s realizing that GPUs are no longer scarce. That was more of a temporary thing. If you have the money, you can get whatever latest NVIDIA GPU you want for a data center.

The pace of energy coming online in the U.S. is still relatively slow compared to other places. That’s why the Middle East swing by the president and all the AI executives is so consequential. There’s an executive order coming from the White House to make that easier in the U.S. — we’ll see what happens in real life.

All of this really comes down to people. I’m talking about both the supply of general contractors to build and dig data centers and wire all the power sources to make data centers come online as quickly as possible, as well as the top-end research talent that’s becoming more of a bottleneck — not just for which country could advance, but which company within which country will advance.

The most interesting position right now is probably Mark Zuckerberg’s spending spree to hire whoever from OpenAI is willing to jump ship. He’s willing to pay whatever he needs to pay. It’s like a classic “buy the free agent market” way to win the championship.

It’s an interesting comparison, keeping the sports analogy going, to how DeepSeek got to where it is — a pure scouting and drafting way of building their team. Their team got built within China (maybe they got some secret offer from Meta too, we don’t know), but these are very different ways of accumulating AI talent, which we know is in real scarcity — not the hardware anymore.

How do we extrapolate that to which country or company will be first to reach the promised land? This makes me think about the immigration issues we discussed at the beginning. Our country never had a great immigration policy for any kind of immigrant, to be perfectly honest. We had enough prestige and resources to attract the brightest in the world. But when that chilling effect sets in, it could be a problem for the long haul, while the scouting ecosystem or drafting source on the China side seems sufficient to put together a DeepSeek, if nothing else.

Peter Harrell: Can I ask you a question, Kevin? It’s not an area I know much about. Is Europe anywhere on the map with AI these days, or is this really remaining a U.S.-China competition?

Kevin Xu: This is very much a U.S.-China competition, particularly because of the talent question — not so much about the money. Jensen went through a Europe swing just a couple of weeks ago and announced a bunch of sovereign AI projects in the UK, France, Germany, Slovenia, and some smaller countries. The governments are generally pretty good at building hard infrastructure from the ground up and signing really big checks when everyone comes together politically. That’s what governments are good at.

But when it comes to organic talent development, most European top-end talent either moves to the U.S. if they can — because they find the European system generally stifling if you want to move fast — or they work locally at the labs of American companies that are building locally to recruit there. The three most recent successful Zuckerberg recruits from OpenAI were from the Sora Lab of OpenAI. Is that European talent or American talent? You tell me.

Matt Klein: DeepMind is UK, right? They’re owned by Google, but —

Kevin Xu: That’s the one shiny example.

Jordan Schneider: Does it count anymore? They were a subsidiary as of 10 years ago. It’s an interesting question, all this sovereign AI buildout. It almost reminds me of Chinese provinces that spin up their own data centers and proudly buy some hardware chips. What are we doing here?

Another aspect I wanted your take on, Kevin: there are rumors that Meta was going to bow out of the open source game. In that case, we’d have no 10-figure companies in the U.S. really pushing on open source, basically seeding the entire ground to Alibaba and DeepSeek. What does that mean from a 10-year perspective?

Kevin Xu: First, Meta’s version of open source — LLaMA — since we do have a lawyer in the room here, is actually from a legal perspective less open than all the Chinese open source models currently, from a legal licensing perspective. Meta came up with its own version of an open source license that was hotly debated within the tiny community of open source licensing lawyers that I’m part of.

Part of those restrictions is that once you use LLaMA’s model up to, I believe, 700 or 750 million monthly active users, then you need to engage with LLaMA’s parent company to have a commercial licensing agreement. That’s an important nuance to start with.

From that perspective, and I’ve heard this from other sources too, there was at least an expectation from LLaMA at some point to still make money directly from its open source models. If it gets competitive enough — whether it embeds into another coding agent like OpenAI and Anthropic, or some other B2B or enterprise product — they had some expectation of that. They weren’t just going to throw a ton of money and talent into this theoretical financial dark hole and do something good for the world, even though they were falling behind.

The fact that this was even leaked as an internal discussion point — I don’t know if they’re really going to do it — but the fact that serious people inside Meta have considered abandoning the open source part of LLaMA and actually abandoning LLaMA entirely in favor of just the best model in the market has so many layers of irony. We have the open society here in America, the open this and that, freedom and whatnot, but we chose this most singularly transformative technology direction to be as closed as possible among the companies.

You can imagine a lot of siloing going on. A lot of things that probably could have been shared but aren’t shared for one reason or another. That actually blunts progress on the long-term horizon, as well as the diffusion pace of certain technology, where open source is just the best way to diffuse a lot of technology — even if it’s the worst way to make money off that technology. That might be the reason why a lot of U.S. companies are choosing the closed source path, while the Chinese side is right now leading in all the open source model benchmarks.

Peter Harrell: Jordan, it’s a question for you. When we think about “Is America cooked,” we often think about this in the U.S.-China context.

Peter Harrell: Has China done anything right over the last three months?

Kevin Xu: I’ll jump in here real quick. This is actually related to the dollar again — speculative because it’s very recent. They did have a recent high-level finance summit in Shanghai, the Lujiazui Forum 陆家嘴论坛, where the governor of the People’s Bank of China and all the relevant high-level financial regulators came and gave speeches.

What came out of this specific forum this year is a concerted willingness to really promote the RMB in ways and places where the dollar is falling short for one reason or another — not to necessarily replace the dollar as the global reserve currency, because that’s a whole other can of worms that I don’t think anybody in China really wants to be. But in countries or trade directions where having the RMB be the settlement currency in lieu of the dollar, or being able to buy global commodities in large chunks using the RMB versus the dollar, is advantageous, there is now a policy appetite.

This is very much a reaction to Liberation Day, to the way that the U.S. instigated global trade war has unfolded. That prompted this. How far will this particular policy direction go? Nobody knows at this point — it’s way too early. But the appetite is there now to be a little more proactive about making whatever reforms necessary to make the RMB more attractive in certain situational settings when the dollar is becoming a little less appealing.

On Allies and Immigration

Jordan Schneider: How bad is Trump going to end up being to the allies? Q1 was probably pretty close to a worst-case scenario with those really obnoxious speeches in Munich. But since then, we had Haley do a trip to Asia where she basically said things that a Nikki Haley administration would have said.

What does the Iran bombing mean for America’s commitment to Asian allies? On one hand, it shows that Trump’s willing to bomb stuff, but on the other, it’s bringing us back to the Middle East. Maybe that’s a bit of a wash.

There was also talk of some crazy DOGE cuts to the Pentagon, but there are basically going to be no defense funding cuts. Whether they’re actually going to reform defense acquisitions and buy stuff we need to buy is an open question.

Even though we’ve had some serious U.S.-Japan weirdness — with Japan being sick enough of the Americans to cancel a two-plus-two dialogue — I still think we could be on a worse timeline than the one we’re on now with the way Trump has treated Asian allies.

Matt Klein: If you really want to be optimistic, you just say the way that the administration is now treating European allies — that’s where you’re seeing the biggest shift, maybe. We’re friends with Zelenskyy all of a sudden. Who knows how long that will last, but that is notable. The European NATO countries seem to have managed to figure out how — with the exception of Spain — to put together a deal that looks like it’s getting everyone on the same page. Who knows how that will play out longer term, but if you want to be encouraged, that’s definitely somewhere to look.

Kevin Xu: Isn’t that just giving Trump what he wanted?

Peter Harrell: That is part of it.

Matt Klein: You reframe it. He said he wanted five percent, and they said three and a half percent plus one and a half percent other, which is fine. Everyone agreed on it. Arguably, it’s good for them too. But the shift with Zelenskyy is interesting, as Jordan said. Trump met him at the NATO summit and said they had a great conversation. Now he’s saying, “Supposedly, Putin called and I need help with mediating with Israel, and I need help with you.” Who knows?

Jordan Schneider: It’s hard to know what’s really going on there. But if you want to be optimistic, the thing with this stuff is that it was unclear if Trump was going to be doctrinaire about these things or just vibrate to weirder places than any American president had gone to, then vibrate back to a more mainstream place and keep swinging. But him staying at “No, we’re leaving NATO, this is a terrible thing" — that’s not something that’s happened. He has shown the capability to get pissed off and fed up by people like Putin, which is something you may not have entirely priced in April of this year. I consider that positive.

Although I’m the Trump optimist here.

Matt Klein: To be fair, it’s also not as if we’ve actually adjusted our Russia policy in a way to imply that he’s actually gotten upset with them. So far, it’s just words. But we’ll see.

Jordan Schneider: I’ll take words.

Matt Klein: Better than the other words.

Jordan Schneider: They’re a start.

Peter Harrell: I very much agree with the point Matt made. Obviously, the words coming out of the NATO summit and the words around Zelenskyy are much better. The lived experience over the last six months is that words change. The thing I’d note in the other direction: two or three weeks ago, Trump was saying nice things about Canadian Prime Minister Carney. Right before we got on this call, he’s now back to saying Canada’s the worst and we’re going to tariff them all over again. Nothing really stays stuck with our current president.

Jordan Schneider: But if things don’t stay stuck on the dumbest timeline, then that is — again, it’s more the Brexit arc, less the actual America self-owned catastrophe one, which is okay.

Peter Harrell: Maybe I should be worried here. The other thing I’m watching to see how it plays out — conceptually related to immigration but also distinct — is where we’re going with our universities. To pick up on a point Kevin made earlier, it’s not that we always had the best immigration policies. American immigration policy has been totally dysfunctional for my entire life — I’m 45 — but we have had, against a backdrop of dysfunctional immigration policy, some very important bright spots. The ability to attract truly great talent to some of the world’s best universities who then stay here and found and run businesses and contribute to scientific innovation.

Trump’s war on the universities has now spread, at least with Harvard, beyond just cutting off funding to trying to cut off their ability to enroll foreign students. It appears that he may be trying to get the University of Virginia to fire its president. I’m not going to defend all kinds of crazy things universities have done over the last five to eight years — there have been plenty of challenges with American universities — but they are a huge source of long-term American strength from a scientific innovation perspective, from a talent attraction perspective, from educating people who then go out and do great things.

It’s looking like a fairly full-out war and not just something that he’s looking for a détente on. There’s a ton of institutional strength in American higher education. I have bias here because both my parents were full-time academics all my life growing up, so I’m biased toward American educational institutions. I worry that if we structurally harm our higher education system, that would be another thing — cutting scientific R&D — that helps us be cooked longer term.

Matt Klein: That’s part of how we’re hurting it. They get a lot of that scientific R&D funding, and if that’s cut off — and also, this is not just a Trump obsession — in the bill that currently passed was this punitive tax on endowment income for universities. For universities that have enough endowment income for that to matter, that pays a very large chunk of their operating expenses. Most of the rest comes from things like government grants for research.

If you cut those things at the same time, they’re going to go out of business or they’ll have to drastically change what they do. Again, this is not something that’s really getting a lot of pushback because people pay a lot more attention to other things — the tariff on this is going up by this amount or whatever — but these other things are still steadily going on despite the fact that people’s attention isn’t focused on that. As you said, it could be a relatively benign Brexit outcome, but it adds up and would be very harmful.

Kevin Xu: That will never show up in these more short-term twitchy indicators, whether it’s the market, the dollar, or any of that stuff. Two points I want to add to what Peter said — which probably makes the best case for long-term cookedness if there’s no really forceful reversal of what’s happening right now, but hopefully some actual tangible improvement on immigration — not just keeping together whatever we had left prior to this presidency.

First, the way in which a lot of these scientific research grants are cut isn’t just a problem because they’re cut from an absolute value perspective, but they’re cut from a “Control-F” perspective. You go through the grants, you Control-F for words that the administration doesn’t like for entirely ideological reasons, and you cut them. That is the reason a lot of the top academics and researchers who came to the United States from other countries specifically came to escape from.

Matt Klein: Right, like “neurotransmitters” because it has “trans” in there. Now you’re saying you’re not looking at Alzheimer’s research.

Kevin Xu: Exactly. The word “diversity” just trips up a bunch of alerts from this Control-F way of thinking about scientific research when the word “variance” could have replaced “diversity” and that grant could have been safe. All these very blunt instrument ways defeat not just the fact that we get to have this innovation happen in our country, but that the people who come to this country to do the research and want to stay — they didn’t just come for the money. Nobody in academia, even at Harvard or Princeton, really celebrates the amount of salary they get to make, even at the highest level. They came here because they don’t have to be worried about being Control-F’d in their own country of origin.

The second point that builds off of that — which is really the long-term cook scenario — every time we have this American declinism conversation (this is not the first time we’ve had this conversation as broader public discourse) the most common way that we patted ourselves on the back or were able to go back to sleep after the conversation was immigration. We still had immigration. All the smartest people in the world are going to save our ass by coming here. That may not be an answer we can just default to anymore. That’s probably the one thing that would put you on the cook ledger in the 10-year timeframe — certainly not a quarter-by-quarter timeframe, because who knows what the market is going to do.

To come back to immigration today — we’re actually selling Trump cards. We’re selling a spot in the best country in the world, quote-unquote, to the highest bidder, not the smartest people. What kind of people do you attract from that? I’ll let the listeners have their own imagination over what those people could be.

Matt Klein: It’s worth noting that the U.S. university system has been so dominant and so good for so long that we assume it has always been that way. But that’s not actually true. Before 1933 — which is a significant date to think about — the U.S. university system was not particularly competitive globally. After that, it was. English wasn’t even the dominant language among academics — it was German. It’s not inherent that it has to always be this way. You’d have to work hard at it, but if you’re committed enough to self-harm for ideological reasons, then you can get rid of these long-term advantages.

Peter Harrell: Another topic that the Trump administration needs to prove it can handle — and it’s an open question — is supporting U.S. manufacturing and some of these strategic industries and products it talks about. There’s also a lot of bipartisan support for the idea that we should have at least some onshore or ally-shored critical minerals production, shipbuilding, and these strategic lower-tech industries.

The administration has certainly talked a good game about some of this. They’ve put out executive orders, they’ve said they want to reduce permitting hurdles to make it easier. It seems entirely up in the air whether they’re actually going to be able to achieve any of this manufacturing renaissance that they’re talking about.

This is going to require a more integrated approach than what we’ve seen from them to date. That’s a big X factor for me: Are they going to be able to actually put this together or not? Will it be in the industries that actually matter to us? All due respect to Howard Lutnick, I’m not sure “screwing tiny, tiny screws into iPhones” is really the industry we want to be focusing on in terms of our manufacturing.

Jordan Schneider: Are there any data points that are encouraging on this line? We’ve seen various efforts to gut the DOE loans program. The CHIPS Act has been exploded.

Peter Harrell: If you look at what they’ve actually done with the money, the DOE loans program was focused on clean energy, and they don’t want clean energy. That seems to be fizzling. There’s anecdotal evidence — Matt, you may have plugged into the data more — that some of the big announced manufacturing investments in those sectors have been put on pause. There’s a slowdown there.

While Trump’s talking about things like shipbuilding, we’re not actually seeing shipbuilding. Let’s put aside the climate impacts of oil and gas and current energy prices — I’m not sure you’re going to see a huge oil and gas boom.

Matt Klein: We haven’t. The joke about “now we’re going to unleash drilling” — you should talk to the shale drillers. They don’t want to do that. Briefly, when Brent went close to $80 because of fears of Iranian activity in the Strait of Hormuz, if it had stayed there long enough, maybe you would have seen more shale. But between the fact that their costs have gone up tremendously because of tariffs on steel — what do you think the pipes are made of? — and the fact that the price of the product they sell has gone down, plus labor costs are still going up over time, it’s not super compelling.

Investment in manufacturing peaked in the middle of 2024. A lot of the growth in investment and manufacturing capacity in this country had been directly attributable to CHIPS and IRA — semiconductors, batteries, things like that. If that’s what the incremental investment is coming from, and then those sources of incentives are being gutted as quickly as possible, it’s not surprising that you’re going to see that move in reverse.

Some of the money may already be out the door enough that it won’t be pulled back on projects that have already started. But it’s not super encouraging. The Loan Programs Office was talking about clean energy, but they were also talking about doing it for critical minerals. Those minerals have green energy-related uses, so you could say, “Oh, we’re going to get rid of it.” But to the extent that they say those things are strategic — whether it’s magnets or whatnot — if you cut the funding, it doesn’t matter whether you call it green energy or not. You still are not going to have the resources.

It’s going to be very difficult to have a domestic industry in those sectors be competitive without some kind of government support because they’re so cyclically volatile on price and because the main producers right now are in China, where market-based constraints are not as severe. Because the capacity is there, they can basically flood the market when they want to. If any seemingly viable competitor shows up — which is why you’ve had such problems with lithium in the U.S. in the past — you need some kind of government backstop to prevent that. That was being done out of DOE.

It could change, but it’s not clear to me there’s strong interest in doing that. I don’t know why a manufacturing renaissance would occur. On top of which, if part of the rationale for a manufacturing renaissance is that these tariffs are going to make U.S. production for the U.S. market more competitive, but then no one knows what the tariffs are going to be — either because they’re illegal or because they’re going to get negotiated away for unclear gains — why would you make a commitment now? It doesn’t pencil out. You want to use a pencil, not a pen, because you can just change.

I don’t see it. It’s not showing up in the data that we’re having any kind of manufacturing renaissance. Far, it’s the opposite. It’s not like it crashed or anything, but it’s not clear to me why we would see a big change given what we know so far.

Kevin Xu: This is a question for Matt, but obviously anybody can jump in. What are the things that got some play but did not get nearly enough play during the DOGE stuff? The cutting of staffing or investment in places like the Bureau of Labor Statistics and BEA. Basically the only neutral arbiter of actually accounting for how cooked we are or not as a country — hard data, not soft data, not live data, not sentiment data.

That’s another thing that just confounds me. If we were to actually answer this question from a statistics perspective or in a rigorous way a year from now, two years from now, whatever — I don’t even know if I could really trust any of the GDP numbers going forward, any of the non-farm payrolls going forward. The government pumps out so much good data and it takes so much time to build up that infrastructure, but you need one bad cut to completely get rid of that discipline.

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Matt Klein: One thing I would say is some of that actually precedes even the election. It had to do with some of the budget deals that were being done in 2023-24. I don’t know why these were agreed to, but basically — I’ve talked to the BEA people and seen they announced tables have been discontinued because they’re not in the budget for it. This was over a year ago. That’s unfortunately been an ongoing problem.

The BLS, which compiles things on inflation and labor market, has been having issues for a while — not necessarily because of underfunding, though that’s probably related to it, but just because people don’t respond to surveys the way they used to, for who knows why. You take a survey of employers every month, figure out how many people are working, and then aggregate it up to give an estimate. But if the employers are not answering your call for whatever reason, or fewer of them are proportionally, that creates potential problems. That was already an issue.

It’s compounded by cutting people arbitrarily. There was an announcement in the past few months — the Commerce Department, which runs the BEA and the census (not BLS, that’s in the Labor Department), had this outside body of advisors, mostly academics, to judge the quality of federal statistics. They just decided to cancel the meetings. Who knows? Maybe they just decided we don’t need the meeting. But it’s the kind of thing where if you were to say, “Okay, this would be the first step if you wanted to fudge the numbers."

I don’t see any evidence that’s what’s going on so far. I don’t want to impugn any of the numbers or any of the work that’s being done now. I don’t see any evidence of that yet. I don’t even know what it would look like, but I agree it’s something to be worried about. Just the fact that we’re talking about it is indicative of the kinds of people who are in charge and what they’ve generally shown in their attitude toward things — that this is a possibility, that it could be happening, even if it hasn’t actually happened yet.

Jordan Schneider: It would be pretty remarkable if we’re in a world where we start treating American numbers like Chinese numbers. There’s the intel community stuff of fudging judgments and people leaking out what the real numbers are. I can imagine that happening also in BLS pretty quickly, where there’s enough of an institutional allergy to this that you hear pretty fast within that org of any of these types of shenanigans happening.

Matt Klein: I had two things. One is that far there are independent ways of verifying inflation stuff. The Billion Prices Project was invented by an Argentine working in the United States as an academic economist — very appropriately — to figure out alternative measures of tracking inflation. They just look at online listings. Far for the U.S., you say, “Okay, what are the prices of a basket of goods that matches the CPI basket of goods based on online listings?” And it’s tracked perfectly so far. That’s encouraging.

On the Chinese side, I guess you might know more than I do. My understanding is the headline GDP numbers may or may not be massaged. The underlying stuff is probably the good faith best estimate. But if they don’t like something, they just stop publishing it. It’s not even that they make it up — they just stop publishing the number. That seems like that actually could be an issue, especially given you have budget cuts anyway.

Jordan Schneider: There’s enough money in getting good numbers on U.S. employment that people will just invest in getting this right.

Matt Klein: It might not be public. There’s value in it being publicly available.

Kevin Xu: It’s locked up in Jane Street’s data center somewhere.

Peter Harrell: Bloomberg will add it to the terminal for an extra $500 a month.

Jordan Schneider: Does anyone have recommendations? Anything you’re reading or enjoying?

Peter Harrell: I just finished reading a book from 15 to 20 years ago by a Wall Street Journal reporter about the rise of the Texas oil families from the 1930s to the 1950s — the wildcatters like the Hunt family and similar figures. It’s fascinating because there are so many parallels, both culturally and psychologically, to the people who have made fortunes in tech over the last 20 years.

These were individuals doing innovative things with new technology who made tremendous amounts of money and then started converting that wealth into political influence. They began buying up media — literally purchasing radio stations at the time. It was quite striking to see how these people started out drilling oil wells in the 1920s and eventually came to build or at least fund the modern conservative political movement in the 1950s. It’s a very interesting piece of history.

Kevin Xu: I started reading Inside the House of Money, which is a collection of interviews with macro hedge fund managers, conducted by another macro hedge fund professional. The interviews are very intimate and revealing.

One of the interviews features our current Treasury Secretary, Scott Bessent, from when he was running his own fund right after leaving Soros. Apparently, going into this interview, he was extremely sleep-deprived — he hadn’t slept for days — and was worried about something that might happen in China. He didn’t specify what, but that was the context for his interview.

This book was written between 2004 and 2005, and I still haven’t figured out what was happening in China at that time that kept our future Treasury Secretary awake at night. If anyone can help me solve that mystery, I’d appreciate it. Regardless, the book is a really engaging read if you enjoy understanding the mindset of global macro traders.

Matt Klein: I don’t have anything quite as sophisticated, but I recently started watching Your Friends & Neighbors, and I’ve been enjoying it tremendously. I also bought The Party’s Interests Come First on your recommendation, though I haven’t started reading it yet. It sounds excellent.

Jordan Schneider: I have another recommendation that will preview a future China Talk episode — To the Success of Our Hopeless Cause: The Many Lives of the Soviet Dissident Movement. It just won the Pulitzer Prize.

It was actually amusing because I booked the author before he won the Pulitzer, and then we had to postpone our interview because he suddenly had major media obligations to attend to. The book is beautiful and literary, with incredible sources. You have all these transcripts from court cases where these dissidents are essentially mocking the prosecutors and judges, taking them to task at every turn.

While it doesn’t necessarily tell you much about this moment in American politics, it provides a fascinating window into the world of these very brave and frankly eccentric people who made remarkable choices in the 1950s, 1960s, and 1970s in the Soviet Union. This was after the Stalin era, so they weren’t going to be executed, but they were still putting an enormous amount on the line to confront the regime.

Our “cooked level” remains undetermined. See you all in September.

Mood Music

How does Russia prevent uprisings, and what can other authoritarians learn from Moscow’s methods of coup control?

For the second anniversary of the Wagner uprising, ChinaTalk interviewed London-based historian Kamil Galeev, who was also a classmate of Jordan’s at Peking University.

We discuss…

• Why the Wagner Group rebelled in 2023, and why the coup attempt ultimately failed,

• How Wagner shifted the Kremlin’s assessment of internal political challengers,

• Similarities between post-Soviet doomerism and the American right,

• Historical examples of foreign policy influenced by a victimhood mentality,

• Barriers to Chinese hegemony.

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Today’s podcast is brought to you by 80,000 Hours, a nonprofit that helps people find fulfilling careers that do good. 80,000 Hours — named for the average length of a career — has been doing in-depth research on AI issues for over a decade, producing reports on existential risk, scenarios for potential AI catastrophe, and examining the concrete steps you can take to help ensure AI development goes well.

Their research suggests that working to reduce risks from advanced AI could be one of the most impactful ways to make a positive difference in the world.

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Why Russians Don’t Rebel

Jordan Schneider: Kamil, can you explain the Wagner insurrection that happened two years ago in Russia?

Kamil Galeev: The Wagner coup attempt in summer 2023 was perhaps the lowest point for Russia during the course of this war — the biggest moment of internal instability. It made a profound impression internally and changed the priorities and policies of the ruling regime.

How did the coup attempt become possible in the first place? Before discussing that, we need to examine why coups haven’t been more common in Russian history prior to the Wagner insurrection.

The primary reason is that since 1917, the modern Russian state has carried direct, uninterrupted institutional continuity. Since the October Revolution, the Russian Armed Forces have been heavily co-opted, which is easy to explain.

Imagine you’re Lenin, Trotsky, and others taking power in 1917. You’re constantly comparing yourselves with revolutionaries of the past, most importantly the French Revolution, but also the English Revolution. What pattern do you see?

You see English parliamentarians taking power from the King and waging war. As they wage war, they create an army, a military force that eventually overthrows them. The same happens with the French Revolution — National Assembly deputies take power and wage war, but the powerful armed force they create ultimately overthrows them.

The pattern they observed from history is that the English Revolution ends with Cromwell and the French Revolution ends with Bonaparte. This became their primary fear for their own revolution.

They took massive, systematic precautions against this outcome. In Trotsky’s memoirs, My Life, he describes discussing an officer of the Red Army called Blagonravov, who performed admirably. Lenin had a strong reaction when Trotsky remarked that Blagonravov, if translated into Italian, sounds like “Buonaparte.” This may seem paranoid, but it demonstrates their deep concerns.

“‘Out of such a lieutenant,’ I had once said jokingly to Lenin, ‘even a Napoleon may come some day. He even has the right name for it: Blago-nravov, [In Russian this means “good-natured” or “good-mannered.” - Trans.] almost like Bona-parte.’ Lenin laughed at this unexpected comparison, then he grew thoughtful, and, with his cheek-bones bulging even more, said very seriously, almost threateningly, ‘Well, I think we’ll manage the Bonapartes, don’t you?’”

~ Leon Trotsky, My Life p. 317

When building the Red Army, they were constantly obsessed with the possibility of Bonapartism, scanning for potential Bonapartes and weeding them out. From the beginning, the Red Forces, from which the Russian army naturally inherits, were extremely optimized to prevent any coup attempt.

This explains what the KGB was all about. You don’t build an enormous, all-permeating, all-powerful state security apparatus merely to fight dissidents — that would be overkill. You don’t even build it just to suppress rebellions. You build the KGB to infiltrate the army, control it, and if necessary, suppress armed insurrections. It’s essentially a second internal army to control the first.

Since 1917, Russian military development has been heavily optimized for this specific purpose. All armed forces, either in the Soviet Union or the Russian Federation, were heavily infiltrated by state security agents with double and triple layers of control. The system was designed so that, first, you cannot prepare an insurrection in secrecy, and second, you cannot execute one because these layers of control would be activated.

State security agents were embedded in every unit, regiment, and army. They would simply eliminate a general who attempted anything subversive. This system worked effectively in preventing military coups, which may explain why the Russian state remained internally stable through the 1990s, despite poverty, lack of resources, and extreme discontent within the military. Many officers were upset, but taking action was impossible.

The interesting thing about Wagner is that it may have been the first military unit since 1917 that avoided this state security infiltration, escaping these double and triple layers of control.

Wagner famously recruited people with various backgrounds — former military officers, police officers, customs officials, drug control agents, and prison guards. Interestingly, they even recruited ethnic Russians from the French Foreign Legion. However, they didn’t recruit state security personnel for obvious reasons — if you start recruiting former state security officers, you’ll quickly be completely infiltrated by current state security officers.

Why was this allowed to happen? It seems like a completely irrational decision for the political leadership. To answer this question, we need to view it not as a single decision but as a sequence of consecutive decisions.

The creation of this large, non-infiltrated force without checks or control layers didn’t happen instantly. It evolved over time, iteratively. Originally, Wagner was a small unit of mercenaries, primarily for special operations far from Russia’s borders — in Syria, Libya, and eastern Ukraine.

A member of the French Foreign Legion displays Wagner-affiliated patches, December 2022. Source.

Early Wagner was small — dozens, then hundreds of fighters who were usually far away, sometimes thousands of miles from Russian borders, with some veterans in reserve at home. These reservists lived normal lives in Russia until called upon. At any given moment, the force was small and mostly distant, which allowed it to largely bypass direct control, partially because it wasn’t considered important.

The enormous expansion occurred only in 2022. Before the Ukraine war, Wagner was essentially an assassin group or hit squad. When the initial invasion failed massively, the political leadership tried to improvise new tools, mobilizing whatever resources they had. At this point, Wagner was authorized for massive expansion.

This wasn’t part of the original plan. When Russian troops crossed the Ukrainian border, Wagner wasn’t there. After the initial invasion failed, they mobilized whatever they could — they called reservists, recruited other people, and soon began mobilizing prisoners.

Before long, they went from having a few hundred fighters mostly in Africa or Syria to tens of thousands relatively close to Russian borders. As this happened rapidly, normal control mechanisms weren’t established. The most basic control would have been oversight by state security officers and possibly the Federal Protective Service, who are essentially Putin’s bodyguards.

When the political leadership eventually tried to impose stricter control by integrating Wagner into the normal military structure, the uprising began.

My point is that although creating a large, uncontrollable structure seems irrational for the leadership, that’s not how it happened historically. First, they created a small structure where additional control layers seemed unnecessary. Then, when the situation deteriorated dramatically, they had to improvise with tactical responses to tactical problems, dealing with consequences later. This happened through many iterations, not just one.

Wagner’s rebellion represents perhaps the greatest internal threat to the regime in decades. Not only during Putin’s rule, but including through Yeltsin’s era as well. There hasn’t been a military rebellion of this scale probably since the October Revolution. It was the most serious internal political threat. The question is, why did it evaporate and turn into nothing?

There could be several valid answers to that question. One possibility is that the Wagner group never actually intended to take power. It was most probably a negotiation attempt rather than an effort to overthrow the political leadership and replace them. It appears to have been an attempt to renegotiate their position, perhaps as a reaction to being taken over. They tried to avoid the imposition of additional control through a show of force. It didn’t work out, but they likely never aimed to overthrow the leadership from the beginning.

This may actually be a common occurrence. Many rebellions and revolts don’t initially aim to overthrow leadership but rather to make specific demands. However, in many cases, these still bring disastrous consequences. Why didn’t this one?

Another valid explanation is that they were positioned too far away. Were there any Wagner garrisons in the Moscow region? Had there been, events might have unfolded differently.

The main reason, however, is that the dirtiest secret about military coups is that successful ones are typically invited. In most cases, it’s extraordinarily difficult to execute one without invitation. The creation of Wagner as an independent and uncontrollable armed force didn’t happen overnight but resulted from an accumulation of many tactical decisions over time.

The common image of military officers secretly preparing and then executing a lightning strike to seize power is largely fictional. In most functional regimes, this approach simply wouldn’t work. For the military to successfully take power, they typically need to be invited or solicited.

Jordan Schneider: Kamil, would you apply a Nazi Operation Valkyrie analogy here? How would you classify that within the solicited versus unsolicited framework?

Kamil Galeev: Consider the Eighteenth Brumaire — probably the most famous and iconic military coup in history, when Napoleon Bonaparte came to power. The important understanding here is that it didn’t happen in a vacuum but culminated a long process.

Since at least the Thermidorian Reaction, the political leadership in France had been using the military to control political processes. They deployed troops to deal with armed rebellions in Paris or popular mutinies. When afraid of losing elections, they used troops to “correct” electoral procedures and break the opposition. When wanting to purge political opponents from parliament and the National Convention, they used troops.

This happened repeatedly. Early in the French Revolution, the use of force was disguised as popular rebellion. Eventually, it became undisguised military force. With each passing year, the government ruled increasingly through explicit military force.

The problem was that as this progressed, the leadership became more dependent on the military. When Bonaparte took power, the coup wasn’t even his idea. It originated with Abbé Sieyès, a political leader who wanted to achieve personal political goals using the military — just as the political leadership had done many times before. This last time, however, it backfired.

What we see isn’t a single coup but many “mini-coups” where political leadership repeatedly corrected political outcomes through military means. In doing so, they gradually invited the military to take power. Examining history, we could find many more examples of this pattern.

Jordan Schneider: The Nazi analogy might be more appropriate than the 18th century Brumaire comparison. There was a war going poorly, with generals realizing their leader was unstable and deciding action was necessary. Many senior Nazi leaders supported the plan, but it failed simply because the bomb exploded on the wrong side of the table.

Kamil Galeev: That’s an interesting comparison with Wagner, noteworthy for both similarities and differences. One key distinction is that the officers who attempted to assassinate Hitler were pursuing what they perceived as a common interest, not personal gain. Many of these officers actually owed their careers to Hitler, so they weren’t motivated by professional setbacks.

The Wagner coup attempt, however, clearly pursued particularist interests. They were essentially protesting against being taken over and demonstrating their force. The first case involved belief in a common good — the second lacked this motivation.

Another obvious difference is that the Nazi coup plotters actively tried to eliminate Hitler and arrest Goebbels, attempting to seize political leadership directly. This wasn’t really Wagner’s approach. Their action resembled a negotiation more than a takeover. The officers who tried to kill Hitler weren’t seeking concessions or privileges, while Wagner was.

The third difference is that Nazi officers were part of the regular military structure, while Wagner operated as an irregular mercenary force. Many Wehrmacht officers could be seen as part of established elites predating Hitler, whereas Prigozhin and his organization were entirely Putin’s creation.

This last point is particularly important because, unlike the Nazi officers within the normal military hierarchy, the Wagner phenomenon only became possible through Yevgeny Prigozhin’s personal connections. Though a junior member, he belonged to the same network as Putin. The creation of this force didn’t happen overnight but through several iterations, succeeding because Prigozhin was integrated into the same contract network.

In Russia, there exists an informal personal network of Putin’s longstanding friends from St. Petersburg, including oligarchs who rose to prominence under his rule, such as the Rotenbergs. Prigozhin appears to have been a subordinate of the Rotenbergs, placing him just one step removed from Putin — a trusted man of Putin’s trusted man. This position gave him access to the sovereign’s ear and allowed him to be entrusted with matters outside normal processes.

One thesis I want to develop later is that power is often misunderstood. Power largely represents one’s social metric status within the contract network. In highly centralized systems, politics revolves around gaining the ruler’s ear at any cost. I believe we’ll increasingly see elements of this in the United States as well, where informal contact with the supreme ruler will matter more and cost more.

Infected by Victimhood

Jordan Schneider: Kamil, how did this experience change Putin and the regime’s calculus going forward?

Kamil Galeev: Somewhat paradoxically, the regime appears to have become relatively more relaxed about civilian threats. After the coup, there seems to have been a recalibration of what constitutes a threat. Dissident groups were effectively downgraded in threat assessment, while state security and intelligence services focused on dealing with Wagner’s aftermath and monitoring potential opposition from armed entities, including those within the regular military.

Essentially, following the coup, significantly greater emphasis was placed on monitoring potential threats from individuals with weapons, regardless of their agency affiliation.

Jordan Schneider: Kamil, what impressions do you have of what’s happening in America right now?

Kamil Galeev: One impression — and this is not so much an analysis as a genuine observation — is that it feels oddly familiar. I grew up in Russia, born in 1992, and much of the Russian atmosphere of the 1990s and 2000s was characterized by a pervasive feeling of resentment. There was a widespread belief that we had been screwed over, ripped off, and victimized. This mentality fueled a desire for revenge in some form.

This feeling of resentment and victimhood has been the major cause of what outsiders might perceive as irrationality in Russian foreign policy. When you feel like a victim, when you believe you’ve been abused and treated unfairly, you often declare a crusade against a cruel world that has mistreated you. This is a common occurrence both among individuals who feel victimized and start attacking everyone around them, and among nations.

The deep resentment and sense of defeat in Russia and post-Soviet countries made them behave in counterproductive ways. This was somewhat explainable because Russia lost the Cold War and consequently acted as a sore loser, which typically means acting irrationally.

Now I sense the same feeling of resentment and a similar atmosphere in America. There’s this notion that “we have been mistreated, we have been ripped off, and now we’ll take revenge.” This is much less comprehensible to me because America didn’t lose — it actually won. I can understand how this sentiment emerged in Russia, but it’s much more difficult for me to construct a functional model of how it developed in the United States.

Consider the trade war, for example. You could argue that decoupling from China serves American interests, which may indeed be the case. However, it doesn’t appear that America is simply decoupling from China — it seems to be attempting to decouple from the entire world simultaneously. This doesn’t resemble a reasonable or rational plan; it looks more like an emotional reaction, an attack against everyone at once.

The only explanation I have is that this behavior stems from a sense of victimhood, which leads to attacking indiscriminately. Within the American conservative movement particularly, I observe an incredible feeling of resentment. Yet it remains puzzling to me how this emerged as a mass phenomenon in the first place. America is the richest large country in the world, yet a big portion of the population sees themselves as victims, abused by everyone.

Jordan Schneider: That’s the world we get to live in now.

Kamil Galeev: Yes, but again, it’s a puzzle I don’t quite understand. In the UK, where I live now, there’s a sense of decline in the standard of living — not necessarily in absolute terms, but in relative terms. Not so long ago, the UK was much wealthier than almost any continental European country, particularly before World War I or even World War II. That’s no longer the case.

But the American situation feels especially puzzling. Perhaps one takeaway is that it’s very difficult to monitor the sense of victimhood within yourself, because once you become infected by it, you begin undermining yourself through your own actions.

Jordan Schneider: Are there any historical examples of victimhood mentality unwinding itself and a new conception or national purpose taking its place?

Kamil Galeev: I’ll avoid modern examples as they would generate too much controversy. Instead, I can offer some more distant historical ones.

We often discuss the problems and madness of Nazism and Nazi decisions, but it’s difficult to ignore that much of German foreign policy was established long before the Nazis rose to power. Consider how hostilities with the United States developed during World War I with the Zimmermann Telegram. Germany sent a telegram offering Mexico a portion of the United States. Even though the British intercepted and published it, few believed it because it seemed so absurd. Then the German ambassador confirmed it and repeated the threats, which led to hostilities with America and ultimately contributed to Germany’s defeat.

This may be the most illustrative example, but when examining German foreign policy before and during World War I, it appears they were actively collecting enemies worldwide. Finding a rational explanation for this behavior is challenging, but this pattern was evident in early 20th century Germany long before the Nazis came to power. This mentality certainly made their policies, particularly foreign policy, much less effective.

To condense it into one formula, if you perceive yourself as a victim, ripped off by a cruel world, then the entire world becomes your tormentor. Launching a crusade against the whole world might sound like a perfect plan, but it inevitably leads to conflicts you cannot possibly win.

Jordan Schneider: Kamil, would you like to share your reflections on China?

Kamil Galeev: If we were living in a conventional world, comparable to 100 or 200 years ago, I would say China appears to be the next world hegemon. This is partly because China has taken over much of global material production and is rapidly improving and expanding into other sectors. In almost every sphere of the material economy, and increasingly the digital economy, Chinese companies are outperforming nearly all competition. Typically, this is how a future global hegemon behaves.

However, we now live in a fundamentally different world from the past, most notably because it is aging and will soon be shrinking quantitatively. When the Netherlands became the economic hegemon of Western Europe, they were booming and expanding. It was a young, rapidly growing country. England during the Industrial Revolution and throughout its 19th-century hegemony was also young and quickly growing. The small manufacturing cities of England were booming with people, particularly young people. The same applies to America in the 20th century.

Now we’re entering an interesting phase where most industrial countries will be shrinking quantitatively and, more importantly, aging. How this will unfold in this new era is unclear. Perhaps the most serious problem facing China is that it appears to be aging faster than other nations.

The most logical solution for them would be to ease their stance on immigration, bringing in more people — and to be cynical and candid — particularly facilitating the inflow of women. The fact that they haven’t taken steps in this direction leads us into unknown territory. I don’t fully understand what will happen when the number of young people falls below a certain minimum threshold.

Jordan Schneider: To close, what are you researching right now?

Kamil Galeev: Currently, I’m primarily interested in coups and power dynamics — how political power is gained and lost. My main topics of interest are the October Revolution and its consequences, as well as the French Revolution and its aftermath. In the coming months, I’ll be writing about Lenin, Stalin, and the Bolshevik rise to power, as well as revolutionary Napoleonic France. Both these historical periods significantly shaped the world we live in today.

is the author of the Concurrent Substack and host of the CyberPink podcast. Concurrent explores the parallel and colliding tech and cultural currents shaping Silicon Valley, China, and beyond. Her show 疲惫娇娃 CyberPink is a Chinese-language podcast about popular culture. From screens to the cosmos, it explores culture in its broadest sense—using women’s voices to expand the ways we engage with and imagine the world. It is very good I highly recommend!

I recently hosted a 2-session reading club for Abundance, bringing together paid subscribers of my Chinese-language podcast CyberPink and those of our sibling podcast American Roulette. Ours was conducted entirely in Mandarin Chinese, which meant that the participants, by default, were like me: born and raised in China, educated in the West, and now navigating the cultural and ideological fault lines between the two. Among the attendees were academics, lawyers, consultants, AI investors in Silicon Valley, and engineers in big tech.

When you discuss American politics in a group like this, perspectives shift constantly. As we dissected Abundance, we toggled between the imagined readers in Brooklyn, the Bay Area, and D.C., and a more distant, more foreign vantage point — one grounded in the trajectories of China itself. In short, we examine the U.S. as foreigners, as immigrants, as Chinese.

Somewhere along the way, our Signal group of book club organizers — my podcast co-hosts and friends — jokingly named the group *Ezra Thought Study Group* (Ezra思想学习小组), a parody of Maoist-era “Marxism Study Group” or more recent “Xi Jinping Thought Study Group.” It was tongue-in-cheek, of course, but it also captured something real: we all sensed that this book was both a techno-optimistic manifesto from central-left, and a piece of strong political persuasion to the reconfiguring Democratic Party.

In this article, I’ve selected fragments from the 100-page (!) transcript of two book clubs, each lasting 1.5 hours — but not the ones you’ve probably heard before. I’ve deliberately cut the standard U.S.-centric book analysis and policy talks; this article is some curated moments that I believe offer some fresh takes. Consider this: Reading Abundance from China.

Note:

The book club followed the Chatham House Rule: participants may use information from the meeting but cannot reveal speakers' identities or information sources. However, I received permission to include some speakers' names and occupations. I've tried to maintain the conversational rawness and haven't done extensive editing, so the transcript may contain factual mistakes. If you find any, please leave a comment. The transcript has been translated and made readable by Claude.

The poverty of American imagination:

Lokin (Lawyer, lives in NYC): I think there's this incredibly limited imagination about what the "good life" looks like in American culture—both among ordinary people and political elites. And this limitation becomes a huge obstacle to building a more abundant, more public, more sustainable future.

There's this perfect example: a Democratic delegation visited Japan recently, and several congresspeople toured the Shinkansen—which, by the way, was built in the 1960s with American funding.1 What's almost laughable is that even today, this public transportation system—which isn't exactly cutting-edge anymore—still managed to "shock" American congresspeople. This tells you that even the highest-ranking political elites don't really have opportunities to experience or understand the kinds of lifestyles other countries have built.

More broadly, American society's vision of lifestyle is still heavily dependent on this outdated American Dream: everyone should own a detached house with a front and back yard, white picket fence, and one or even multiple cars of their own. This individualized, anti-public understanding of the "good life" makes it hard for people to imagine, let alone accept, lifestyles based on public transit, shared spaces, and urban density. So we can understand why American rail infrastructure always struggles to move forward—it's not just technical and budget issues, it's cultural and imaginative barriers.

I was talking to a professor at Columbia—one who’s knowledgeable, well-traveled, worldly person. He told me how impressed he was by Beijing's public safety: at 1 AM, he saw a woman in fur and jewelry walking alone on the street, eventually taking the subway home without any worry. He cited this as positive evidence of modern urban life.

I politely reminded him: if you want to use an example to illustrate good urban safety, you should really mention Tokyo or Seoul instead. Because these cities are equally safe, but they're less likely to be misunderstood as depending on "authoritarian order" for maintenance. When you use Beijing as an example, in the American context, it easily activates this "authoritarian scratch"— people who are culturally inclined to believe order can only be achieved through strongman rule will instinctively equate urban safety with authoritarian governance. They'll think only highly centralized power systems can achieve clean, safe, orderly urban life. This imagination further reinforces their pessimism about democratic countries' inability to govern cities well, providing psychological support for rationalizing some kind of authoritarian governance logic.

But this is actually a very dangerous misreading. We have to dismantle this binary thinking: cities can be both safe and free; public life can be both efficient and democratic. This kind of life exists not only in Tokyo, Seoul, Amsterdam, Zurich, but could absolutely be realized in America, provided we first culturally change our assumptions about what "ideal life" looks like.

What's even more concerning is that even these elite intellectuals still lack basic concepts of what "modern urban life" should look like. They may have never truly internalized the daily experience of "stepping out and taking clean, safe subway, walking freely in dense urban neighborhoods." They still view "cities" as dirty, dangerous, anxiety-inducing places, while treating "suburbs" as safe, clean, ideal residential areas.

This deeply rooted cultural cognitive structure is the biggest resistance we face when promoting public lifestyle transformation. Under this cultural logic, even with sufficient resources and mature technology, it's hard to push for truly progressive infrastructure transformation.

Afra: The poverty of American elite imagination about "happy life" is a key factor preventing visions like Abundance from being realized. Even if we set aside structural obstacles like racial discrimination and economic interests, just looking at popular culture, America’s deeply influential soft power, the society has already fallen into a kind of imaginative local optimization.

As the world's most powerful popular culture exporter, Hollywood has long been continuously and repeatedly producing a specific kind of life picture, and this picture's singularity is actually quietly limiting public understanding and imagination of the possibilities for abundance and "good life."

For example, when Hollywood wants to show a big city's bustling scene, the template is almost always New York: broken-down subways full of rats, Manhattan's towering skyscrapers, a city that's vibrant yet dirty and chaotic. This "city equals anxiety" narrative has almost become American culture's default setting.

And when film and TV want to imagine "ideal life," the camera often turns to suburbs: spacious detached houses, white fences around front yards, two cars, a few dogs, quiet tree-lined neighborhoods, and a typical nuclear family. This repeatedly reinforced template creates a ceiling for cultural imagination, making it hard for people to conceive of a lifestyle that's both urban and livable, both public and high-quality.

It's precisely this imaginative pathway that's been constantly reproduced by the cultural industry for years that makes "abundance" futures largely misunderstood as extensions of consumerism or "upgraded versions of suburban dreams," rather than optimization of public spaces, infrastructure innovation, or reorganization of human relationships.

On environmental assessment in China and the US

T, (Economist): I'm an economist, and my main research area is causal inference. Right now, most of our policy evaluations are built on causal inference methods. The most common example would be A/B testing or randomized controlled experiments. Many policy evaluation paradigms, including things like environmental assessment, basically follow this same logic and process—they're all built on this scientific framework about what makes policy "rational."

But the problem is, this approach might be missing a crucial point: when we do A/B testing, we often can't capture general equilibrium effects. We don't have the ability to properly measure the chain reactions that policies create at the system level. What we get is often just a local impact—a primary feedback observed under specific settings. But this local effect might not be the most important first-order effect; the deeper structural impacts might be exactly what gets excluded because our evaluation methods are too reductive.

I think environmental assessment is a perfect example of being shaped by this paradigm. Many countries do environmental assessments—China has similar systems too. But China's environmental assessment often feels more like formalistic copying: seeing that the U.S. and other countries have environmental assessment mechanisms, so we "should" have them too. But for a long time, China's environmental assessment wasn't treated as a serious, scientific problem, so it didn't adopt the kind of rigorous processes based on scientific methods like America does.

The result is that in China, environmental assessment plays a very limited actual role in infrastructure development. And in America, while the environmental assessment system itself is more influential, the methods it relies on still tend to only capture partial effects while ignoring broader general effects. For example, opportunity cost might be a crucial variable in policy choices, but it's not something that's easily captured in our current mainstream operational inference frameworks.

So I think there's this really interesting, even ironic paradox here: our methodology is indeed getting more and more advanced, allowing us to make increasingly "scientific" policy evaluations. But at the same time, it's precisely these methods themselves that are making our understanding of the complex, multi-layered impacts after policy implementation more narrow. Maybe in trying to make policy evaluation more "falsifiable" and more "rigorous," we're also losing our sense of its holistic and long-term dimensions.

The "tech OS gap" between China and the US

Du Lei (tech investor, lives in the Bay Area): From my background—I originally did AI research and now I'm in tech investing—so I instinctively tend to look at problems from a "system design" perspective. My very intuitive feeling right now is: America is using an outdated institutional framework, this old governance "software," to deal with a real-world social system that has higher bandwidth, more complexity, and faster change. The result is—the whole system is starting to fall behind.

The deregulation that Abundance mentions frequently, in the short term, might indeed be an emergency measure to improve efficiency. But if it's just deregulation without actually rebuilding this institutional infrastructure, it's probably just "treating the head when the head hurts, treating the foot when the foot hurts."

It's like a programmer who just joined a company that's been using a ten-year-old system, saying: "This legacy code is too messy, just delete it." Deletion might feel good, but three months later the whole system could just crash.

Let me talk about the differences between China and America. I think China's execution advantage in certain areas doesn't necessarily come from so-called systemic superiority, but is more like a manifestation of a technological generation gap.

At the end of the day, China's bureaucratic system is more updated than America's. So even if both countries are equally bureaucratic, Chinese government departments use WeChat to communicate directives and share spreadsheets—at least at the tool level, it's faster and more efficient than America's approach which still relies on email and paper processes.

Of course, China has its own systemic problems too. Like this "layer-by-layer responsibility implementation" approach we've seen since SARS, all these "red line" administrative mechanisms often cause inefficiency and even suppress genuine local feedback. But from an operating system perspective, China is indeed faster at "hardware updates," even if the "software logic" still has plenty of problems.

I also want to respond to this topic about "industrial planning vs. basic research." My personal view is: I don't really believe the government can actually push forward much substantive breakthrough in "basic scientific research."

In another book our CyberPink listener’s community is co-reading, Nexus, it talks about how many real scientific breakthroughs actually come from a broad peer network—they need free, open exchange and sufficient resources. So a lot of times, the technological explosions we see are actually the result of long-term, multi-path, slow accumulation.

For example, America's AI explosion didn't just appear one day with a "lightbulb moment," but is the result of twenty years of big data accumulation, gamers pushing GPU performance, miners driving computational power—all these things stacking up over a long time.

It's the same on China's side. A lot of the technological progress we see isn't some policy suddenly deciding something, but the entire manufacturing system, craftsmanship system accumulating through massive iteration processes.

This is a kind of compound advantage. I think we can't misread this compound progress as achievements brought by "government systems." It's more the result of an ecosystem.

The economic-political split: ground-level contradictions in the U.S.

Amber (Consultant, lives in New York): Hi everyone, I'm Amber. When Afra mentioned America "wanting to catch up" or "wanting to lead" in areas like batteries and solar energy, I really resonated with that—there's this complex emotion behind it, both envy and a deep sense of being torn apart.

Let me give you some background. My day-to-day work involves directly dealing with local governments across America, investment promotion departments, including some global investment projects landing in the U.S. Many of the projects I handle involve building factories, offices, job creation, and so on. And in this process, I've observed a very obvious contradiction:

On one hand, local governments desperately want these investment projects to land because they bring tax revenue, jobs, can revitalize their communities and drive regional development. But on the other hand, they're extremely cautious, especially when facing investments from China—political agenda almost always gets put first.

Here's a simple example: it's not just Texas or those Southern states everyone's familiar with—even states like Southern conservative states and Midwest states that seem like swing states are now very sensitive about "Chinese property ownership." Many local governments explicitly write in their RFP documents that they won't accept investments from China—they just completely won't entertain it. For many of the projects we're working on, this is like a blow to the head.

What's more ironic is that many local officials are actually very conflicted privately: they really do want these projects to land, they know these projects are good for the local economy, but they can't help it because the governor, state legislature, and voter pressure require them to "stay aligned with Trump" politically, they have to put on a tough stance. So the whole system is full of internal tension.

And it's the same on China's side. Many Chinese investors really want to enter the American market, they see opportunities, but they just can't get in.

So what we're seeing now is this bidirectional tear: America and China are mutually wary at the policy level, mutually hostile in public opinion, but economically, they both want to get a piece of the pie from each other. America is worried about leaks on one side and unwilling to give benefits, but on the other side wants to take China's money; China is the same—worried about technology blockades on one side, but hoping to get American subsidies and market access on the other.

So on the surface, both sides seem "calm," but privately, the ground-level exchanges are full of struggle and distrust, like a relationship being pulled in two different directions.

This is also the most real state I've experienced when dealing with American local governments, especially some small-town industrial parks: they really are desperate for development on one hand, but on the other hand they're completely constrained by the upper-level political environment, stuck between a rock and a hard place.

The US and China spend too much time doomscrolling on each other’s social feeds

Yiting (tech worker, lives in London): I think China and America right now are exactly like two doomscrollers brainrotting on each other's social media feeds.

It's like America suddenly scrolls through China's feed, sees some superficially shiny stuff, and goes: "Oh? I want that too!" But they don't really understand what this "person" China is actually like—what reality they're facing, what their situation is, what their resources and challenges are. They don't care, and they don't understand. They just see a filtered photo and start envying, imitating, even getting anxious.

Then America's own actions start getting distorted, wanting to "become another person," without figuring out why that other person is the way they are.

Actually, China does the same thing to America.

Many Chinese people, maybe even including some people at the policy level, don't really understand America's political ecology, social structure, or how their institutions actually work. But they scroll through America's social feed—like some very free, very advanced, very prosperous moments—and think: "I want to be like that too."

So the end result is: both sides are looking at each other's highlight reels while ignoring each other's complex realities, and they both fall into this illusion of "everyone else is living better than me."

At the end of the day, I think both China and America should probably spend less time brainrot.

The blind spot of China envy

Luke (tech worker, lives in NYC): I want to ask a direct question—have you guys listened to the latest episode of Bumingbai podcast?2 They mentioned some huge problems behind China's prosperity. I'm particularly curious: if it's people like Derek Thompson or those centrist liberals, in their process of "rediscovering China," after learning about these problems, what kind of reaction would they have? How do they view these realities?

H (media professional, lives in NYC): Personally, I feel like they don't really understand China—many of them haven't even been to China. When they mention China in articles or podcasts, it's not because they really care about China's history, policies, or the situation of its people. They're using China as a mirror or reference point—not exactly a cautionary tale, and not a positive example either, but a contrast that can inspire Americans' imagination, fighting spirit, and policy action.

What you just mentioned, like solar panels—I'm not an expert in this field, but from some reporting and observations, China's rise in this industry did go through a complex process: from early government subsidies and factory expansion to gradually establishing a globally leading position. But in this process, many Western observers ignored the real costs behind it, like compressed labor rights, serious resource waste, and even corruption and benefit transfers. These realities, as people with Chinese backgrounds, we should of course pay attention to, but in the discourse of people like Ezra Klein or Derek Thompson, these are hardly mentioned. What they care more about is how to use "China's success" to inspire competitive consciousness within America.

When they talk about China-U.S. relations, they easily apply the Cold War framework, like comparing it to the Soviet Union's Sputnik moment: the Soviets launched the first satellite, which inspired America's systematic investment in space, education, research, and other fields. This kind of "being inspired" is the process they hope to replicate from China again. But whether this path is correct is itself a controversial political judgment.

Afra: I agree. Ezra Klein and Derek Thompson are, after all, American political commentators working within that context. When Ezra Klein mentioned in his podcast that he went to China once about a decade ago, he mentioned that he was talking about having a lot of meetings with officials, with economists, with some business people. So naturally, his China experience draws from that particular slice of the country.

When H mentioned the lithium battery industry earlier, I also remembered chatting with a British scholar a few days ago. She said she attended an academic conference where a young female scholar shared her research on the environmental impact of a lithium battery factory in Sichuan or Anhui (I couldn’t recall). After this young scholar finished speaking, she told all the attendees: "I really hope this paper can be published in China, but I know it's almost impossible." This exposes a core problem: many environmental and industrial costs in China cannot be openly discussed.

A few months ago, I also read an article in Rest of World by Viola Zhou about Chinese lithium battery company Gotion wanting to invest in building a factory in a small Michigan town, bringing huge funding and job opportunities. But the project was ultimately blocked by small-town politics and strong opposition from local residents, where the main resistance was exactly concerns about environmental pollution. In contrast, in China we can hardly truly see these local costs of EV manufacturing or lithium battery factories—exactly how much wastewater was discharged, how much land was occupied, how many people's lives were affected. Much of this data is unknowable because of media lack of transparency and the absence of civil society, meaning these voices have no channels to be heard at all.

H (media professional, lives in NYC): Right, these American "China-envy" people only see the results, like Chinese electric car companies like BYD rising in the global market. But they often ignore the real problems behind these companies, like product quality issues, defaulting on supplier payments, and so on. These more detailed, more complex layers—they don't really care about them.

Debate about the secret sauce and manufacturing mobility

Afra: Ezra Klein mentioned, “the re-emergence of industrial policy in America is 100% about China. Take China out of the equation, and there is no re-emergence of American industrial policy.” Actually, going back to this American reindustrialization thing. Manufacturing: When you really interrogate what technology in manufacturing actually is, of course, you can say part of it is about patents, about things that can be written down, about hard knowledge in manufacturing.

But there's actually another huge part that's tacit knowledge.3 How do you manufacture an iPhone? You need many skilled workers going through many complete assembly lines to put this iPhone together. It's not like you can write the iPhone assembly steps in a piece of paper, and then have new American workers read that paper and immediately go into the factory and start working.

If America needs to reindustrialize, you might really still need to bring Chinese workers back to continue training American workers before you'd have a relatively effective production process. Is America's imagination about reindustrializing very arrogant? Massively ignoring this kind of tacit knowledge in manufacturing and China's accumulated experienced workforce.

X (ML engineer, lives in NY): I have a pretty different, pretty opposite view, because manufacturing itself has extremely high mobility. The reason it exists, the biggest reason it can scale, is that it can reproduce very quickly—the entire factory, the entire process, assembly lines can reproduce very quickly following a template. This is the essence of manufacturing.

At least we might see individual cases like Huawei in the news being a bit less common, or things like that Cao Dewang factory in America having trouble getting started being less common, but including—I don't know if that CyberPink listener is here today, he works in chip industry landing in America—this stuff being able to flow back is the norm.

Manufacturing being able to flow between countries, building a factory and being able to make stuff—this being possible in most cases is actually the norm. If this wasn't the norm, globalization wouldn't have happened. Shenzhen, I think, does have a very unique ecosystem, including its concentration of talent and concentration of knowledge and the existence of the entire ecosystem. I think Shenzhen is a unicorn, just like Silicon Valley itself is a unicorn. But I don't really agree with what you just said about treating manufacturing as something that needs secret sauce, because the essence of manufacturing itself is that it can land anywhere and you can follow the recipe to make it, because if this wasn't possible, this industry wouldn't exist.

So including why everyone in manufacturing, all people in the manufacturing industry, always have this strong sense of crisis about manufacturing mobility—it's still because its mobility is too strong. Including that article I posted before about India, about that piece Viola wrote about India, I found that article very familiar because all the problems they were discussing—Indians feeling like our Indian manufacturing will never get off the ground—but the problems they cited are exactly the same as what I think Chinese people said 20 years ago about how our Chinese high-end manufacturing will never get off the ground.

So I think many things aren't inevitable—it's the current state produced by globalization at this moment. And including my overall view—because I might have followed a few cases at work where a chip factory was moved over from start to finish—I think everyone's degree of exaggerating the secret sauce of many industries is still a bit much.

Afra: What I actually want to say isn't that China now has high-end manufacturing secret sauce that other countries don't have, but that I think this secret sauce cultivation is a very long process. And the reason China was able to cultivate this secret sauce is because China was in a situation at that time—early 2000s, late 90s—where everyone was sharing secret sauce without reservation in a very radical and idealistic state of globalization. But now in 2025, it's no longer that kind of state. Of course, I feel like secret sauce is a very inappropriate term—I'd rather use the term tacit knowledge.

Back in the early 2000s, if China's Foxconn built factories in China, Apple could send large teams of technical bureaucrats to help China build factories and educate the workers. But now if India builds factories saying they want to replace China in manufacturing iPhones, if they want to ask China for some high-end manufacturing help, China definitely say no, because globalization now is not the same as globalization back then. Everyone knows this tacit knowledge is very precious, everyone thinks this is to some degree a huge asset.

X (ML engineer, lives in NY): I think whether they give it or not depends on who's paying—that's also part of the... Back then I think Koreans weren't that willing to give us (China) technology either, but this thing... I think we're all old enough to remember China's manufacturing going from nothing to something, so I'm also very worried that it going from something to nothing is also something we could witness in our not-very-long lifetimes.

Afra: I'm not saying this transition won't happen, but what I quite agree with in Abundance is "America forgot how to build." I think that's a very precise statement, because in manufacturing, knowing how to build and deploy is a "practice makes perfect" technical skill. It's a state that needs more than a lab, more than a book. Just like if you don't exercise for a long time, your muscles gradually atrophy—America's manufacturing muscle has atrophied for decades.

The Deploy chapter in Abundance talks about the lithium battery case, which is really exactly about Americans inventing lithium battery technology and then forgetting how to deploy and scale. Now Chinese lithium battery manufacturers can compress prices in every single link to the lowest, optimize every aspect and every raw material of lithium batteries to the optimal state—this deployment optimization has gone through twenty years. If suddenly tomorrow a Silicon Valley company appeared saying: we're going to build a lithium battery factory from scratch without relying on Shenzhen to teach us, I don't believe it would immediately succeed.

Bay Area’s military-industrial startup renaissance, and China’s "crossing the river by feeling the American stones" innovation style

Du Lei (tech investor, lives in the Bay Area): When we think about San Francisco startups, we traditionally picture a software-dominated entrepreneurial ecosystem. But if you head down to the South Bay, there's still this atmosphere tied to traditional industry—especially over the past decade, we've seen the emergence of a whole batch of defense-related startups in America.

Companies like Anduril represent this trend. People are starting to realize that in this new phase of industrialization, defense startups can actually attract venture capital funding, and their returns and growth potential look pretty damn good. So we're seeing that in America, entrepreneurship isn't just limited to crypto or AI—even defense is becoming a new direction that VCs are paying attention to.

I just shared an image in our Zoom chat, it's the business card of a CEO from a startup that makes anti-drone defense systems. You can see a perfect example here: Reddit-style geek culture meeting the defense industry. This seemingly awkward fusion actually shows that America isn't completely hopeless when it comes to rebuilding its manufacturing and industrial base.

At the same time, fields like blockchain and robotics are gradually recovering too.

This highlights a fundamental difference between the innovation ecosystems on both sides. In America, the entire industrial structure and institutional environment is more encouraging of disruptive innovation. Entrepreneurs are more inclined to do things that are completely different, trying to solve old problems with entirely new approaches. Once this kind of innovation gets market validation, it can quickly attract massive capital, and America's institutional and capital mechanisms can give successful players decent returns.

In contrast, truly disruptive innovation is relatively more difficult in China. The path dependency is stronger—a lot of times it's still "crossing the river by feeling America"4, so incremental innovation is more common. This incremental approach actually has strong advantages, especially in large-scale industrial production industries. As mentioned in Abundance, much of real technological progress often doesn't come from some genius's "eureka moment," but from countless small iterations on the production floor, on the assembly line.

America definitely has advantages in excavating "innovation points" that have clear commercial value and market acceptance, but when it comes to those "1.1 improvements"—the continuous polishing and optimization—the gap compared to China is obvious. This actually reflects deep institutional design differences between the two countries: America's system encourages high-risk, high-reward winner-takes-all, while China's structure tends more toward stable returns and inclusive distribution. These institutional and cultural differences in risk appetite ultimately show up in the industrial realities and innovation models we see today.

X (ML engineer, lives in NY): I've been thinking about the past few years, and maybe as someone in the healthcare industry—at least from my own perspective—I actually feel like the reasons why these two countries can't achieve disruptive innovation in certain areas are quite similar: whoever's figuring out how to make money off the government, whoever's trying to optimize the bureaucracy, they can't do disruptive innovation.

The ones who can leapfrog across barriers, especially recently I've been reading Careless People. I've found that whoever can cleverly circumvent regulation, taking action before regulators even react, they're more likely to succeed. This viewpoint might sound a bit cliché, but that's really the situation now.

I think many industries in both China and the US are the same—they're all trying to figure out how to capture more government funding. These industries, as we just touched on, have fallen into a state of false innovation. Just like we discussed in our last book club, they're addicted to surface-level innovation, with all costs going into the bureaucracy. The people who can actually focus on innovation, focus on coding, are really few and far between, and these programmers spend every day in meetings.

The hidden costs of re-industrialization: the Factory Girls nobody talks about;

Afra: Before the book club ends, let me add one more thing about American re-industrialization. Remember during that period when Trump and J.D. Vance were heavily promoting "American re-industrialization"—there were tons of memes on X. Professor Huang Yasheng from MIT posted a trolling tweet.

Huang Yasheng was basically suggesting that this book tells you some reality about manufacturing and re-industrialization. that you wouldn’t learn in the schools in the U.S. I found that tweet fascinating, so I tracked down the book, which I had heard about for many years, and read it. Many scenes in the book are shocking. Not just because they made me remember that institutionally chaotic China from over 20 years ago, but because they made me rethink the lived reality of ordinary workers under the factory system. The book spends extensive pages describing the real conditions of young female workers on assembly lines.

For instance, in the factories, many female workers (almost all come from rural areas) wouldn't tell their coworkers their real names. Because once you reveal your name, if you happen to run into someone from your hometown, information might get back home, and relatives—even parents—might find out about their income, leading to economic exploitation, with wages being demanded and controlled. These female workers were doing shift work day after day on assembly lines, twelve hours a day, while also facing "exploitation" from their families of origin. The book also describes how they struggled to establish their own identity in extremely compressed living spaces—in factory dormitories with no privacy, living in rooms with six or eight other female workers, where even just trying to make yourself "different from others" was difficult. There was no mobility, no prosperity. It was this state of people struggling to survive within the system, under the assembly line, within silent norms.

After reading this book, I went online to look up what Foxconn factories look like today. I was surprised to find that photos, videos, and even content shared by workers on platforms like Xiaohongshu that circulate on the Chinese internet really aren't that different from the lives of that generation of Shenzhen female workers that Leslie Chang wrote about in the early 2000s.

During my doomscrolling, and some of them really saddened me. If you just search keywords like "Foxconn," "assembly line," "factory girls", "factory boys" (厂妹，厂弟）on Xiaohongshu, you can see tons of real documentation: what workers eat, where they sleep, their shift conditions, what they do after work. There are also many factory veterans"giving advice to vocational school students and high school graduates preparing to enter factories.

Behind this content is actually a complete factory culture and factory logic; a grim way of organizing people, controlling time, and stripping away identity.

This made me think—if US wantS to replicate a massive, complex, comprehensive manufacturing ecosystem like Shenzhen, then the social costs and structural prices behind it are far beyond what American politicians are actually thinking about when they're currently discussing "re-industrialization."

Another related example: director Yu Xinyan made a documentary called Made in Ethiopia, about Chinese companies setting up textile factories in Ethiopia. They established what's called the "Eastern Industrial Park"—just the name alone carries this heavy self-orientalist flavor, plus some Belt and Road style developmentalism logic.

The first part of the documentary tells the success story—thousands of Ethiopian female workers employed, smooth cooperation with the local government. But the focus of the documentary is on how to expand the factory to the second phase, they had to requisition villagers' farmland and promote village-scale migration. It was about trying to "system-switch" an agricultural society into one that accepts factory labor logic.

The film is full of conflict and tension: farmers' resistance, government buck-passing, cultural misalignment, and how Chinese-style production logic, such as progress determinism, gets forcibly transplanted into a completely different social soil. These scenes are extremely similar to the pain points in China's early manufacturing development.

Speaking of transnational factory landing, there's another example really worth paying attention to (which was previously mentioned): NPR's Planet Money recently did a follow-up episode about the Gotion story with more details, including how several consecutive town hall meetings in this small town gradually evolved into strong opposition to "Chinese capital entry." The whole thing essentially became a collision between American grassroots democratic politics and global industrial expansion.

Through these reports, I really saw the complexity of "industrial projects" in the American local context: how small-town political culture operates, how the public expresses opposition, how policymakers struggle to compromise.

Subscribe to Afra’s great substack and check out her podcast!

Concurrent

Understand the parallel and colliding tech and cultural currents shaping Silicon Valley, China, and beyond.

By afra

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is a Professor of Urban Studies at Singapore Management University, and research fellow at MIT. His research examines the political economy of digital infrastructure in China and Southeast Asia, and maintains the excellent substack Sinocities.

U.S.-China competition in AI is seen as the defining technological rivalry of our time. Much of the analysis in this competition is premised on a zero-sum logic — we cannot let China get ahead of us in AI, so the logic goes, as this will inevitably mean the forfeiture of American technological and military primacy.

There is another possibility–China and the U.S. may develop different “varieties” of AI. For example, the U.S. advantages in cloud computing, software development, and openness to talent (tbd…) give it an edge in development of enterprise software and large language models (LLMs). However, China has clear advantages in manufacturing and infrastructure, which could offer an edge in what experts term “embodied AI”, or in Chinese jù shēn réngōng zhìnéng, 具身人工智能. Embodied AI systems interact with the physical environment through sensors (like cameras, microphones, touch sensors) and actuators (motors, limbs, wheels, etc.). Embodied Intelligence is shaped by a real-time, physical engagement with the world.

The central government recently included “embodied intelligence” in its work report, indicating the area as a key priority. Zhongguancun, Beijing’s hi-tech area, recently released its plan for embodied intelligence. A recent report by Georgetown’s Center for Security and Emerging Technology (CSET) focused on efforts in the city of Wuhan to embody “AI algorithms in real environments. Imbued with the Chinese Communist Party’s predefined values, the AI interacts with its natural surroundings, learning as it proceeds.” In this post, I explore some of the origins and implications of China’s interest in “embodied AI”, and then present a few examples of this approach in sectors such as autonomous vehicles, personal mobility, robotics, and the“brain-style” AI models being used for smart city operations. While the current push for embodied AI is part of a prevailing fever for AI globally, China’s priorities reflect long-standing beliefs in the use of technology for solving governance problems, and the need for physical infrastructure and manufacturing as key priorities for the country’s development.

Internet+, the Fourth IR: the Party’s Embrace of Embedded AI

In 2015, China’s Made in 2025 Plan drew the ire of many in the West for its ambitious goals of replacing foreign companies in China and dominating frontier industries like aerospace, biotech, and smart manufacturing. In the same year, Vice President Li Keqiang unveiled a vision for Internet Plus (互联网+), which called for applying data and AI to manufacturing, smart homes, intelligent vehicles, robotics, wearable devices, and more. The Internet+ Vision is seen as one of China’s earliest national strategies on the application of AI to industry, and underscored the degree to which policymakers in China saw digital data not merely as a sector in itself, but as an input for many other sectors. Li Keqiang’s Internet Plus was also inspired by Industry 4.0, a concept initially proposed in Germany in 2011 (Huda 2023), and which influenced World Economic Forum founder Schwab’s idea of the “Fourth Industrial Revolution” (Schwab 2017). Schwab popularized the idea of the Fourth Industrial Revolution, but the term itself emerged around 2011 at the Hanover Fair as part of Germany’s strategy to use digital technologies to maintain and deepen its edge in manufacturing. The 4^th IR predicted the application of computing technology and the internet to a wider range of everyday life and objects. This encompassed “artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing.” The concept found resonance in China, a country that, like Germany, was arriving on the world stage as a major manufacturing power.

The idea of the fourth industrial revolution was embraced by top party leaders, including Xi, who saw the coming technological revolution as part of a critical period of changes in world history that China had the opportunity to lead. In 2017, Xi used the term “profound changes unseen in a century”, or bǎinián wèi yǒu zhī dà biànjú 百年未有之大变局, encompassing technological transformations but also a shift away from a U.S.-led global order. As Jin Canrong 金灿荣, Dean of the School of International Relations at Renmin University, put it in 2019, “After the fourth industrial revolution, the productivity of the East is likely to be ahead of the West, or at least a balance between East and the West will be achieved. This is the most important change among the three changes unseen in a century.” Jin goes on to note that, “If the 4th industrial revolution is, as Schwab described, ‘5G + the internet of things,’ then China is already leading this revolution, but I tend to be in the camp seeing this as more of a deepening of the 3rd (internet) revolution.” Nevertheless, Jin still saw China as having an advantage over the U.S. due to its production capacity. “The U.S. still has the best innovation capabilities, but the hollowing out of industry is a big problem. If you cannot turn innovation into products, it’s the same as a piece of waste paper.” Thus, Jin viewed manufacturing as a crucial component of China’s strength that would allow it to outcompete the U.S. Recently, Tsinghua Professor Tang Jie 唐 杰 repeated a view on China’s advantages as comprising “super-large population, rich application scenarios, and rapid iteration of the end-side ecosystem provide fertile soil for the rapid development of AI big models.”

Of course, the “4th industrial revolution” hasn’t played out entirely as Schwab or China’s leadership assumed. Around 2015, 5G and the “internet of things” were predicted to revolutionize everything. So far, 5G and the Internet of Things have proven less transformational than originally anticipated, but we are still early innings of what could be a longer story in the application of AI to other areas.

Governance: City Brains and other Brain-inspired AI

In addition to being home to Alibaba, the city of Hangzhou helped spawn the so-called “six little dragons”, 六小龙 which include DeepSeek. Hangzhou is also the site of one of China’s first successful “City Brains,” 城市大脑 — a smart city platform developed by a partnership of the city government with Alibaba’s Ali Cloud back in 2016. The platform was first deployed to help reduce traffic jams. A network of AI-enabled cameras, produced mostly by local firms Hikvision and Dahua, feeds information into a cloud system that gathers real-time information on traffic flows and accidents, and processes this information to adjust and optimize traffic lights across the city. The City Brain 3.0 integrates data from traffic lights, surveillance cameras, vehicle GPS, municipal records, public services, and IoT sensors. Alibaba has gone on to market its City Brain platform to cities around China and the world, and China has promoted the construction of City Brains around the country as a core component of the 2023 Digital China Plan. China’s 14th Five-Year Plan (2021-2025) calls for using “digitalization to boost urban and rural development and governance model innovation, build an urban data resource system, and promote the construction of urban data brains" (14th Five-Year Plan). Subsequent policies have followed the 14th Plan, including the 14th Five-Year Plan for National Informatization, which includes plans for a “ubiquitous, intelligent, connected digital infrastructure system”, comprising 5G, big data centers, and smart networks, for example.

The “city brain” concept dovetails with the established interest in using AI to improve governance. The PKU-Wuhan AI institute has apparently been developing a “large-scale social simulator” (大型社会模拟器). While the focus of these initiatives is on AI, they follow from a longstanding faith in systems thinking and technology to solve government administration problems. In the 1980s, the concept of cybernetics was embraced across a wide swath of scientists and leaders as the country turned away from the fervent ideology of the Cultural Revolution towards science and technology. The crux of cybernetics as developed by Norbert Wiener in the 1950s is information processing: “Cybernetics takes the view that the structure of any system engaged in communication or control must be analyzed in terms of the transfer and processing of information, whether the system be an electronic brain, a living organism, or a social institution.” Qian Xuesen 钱学森, a Chinese student of Wiener’s, helped build the PRC’s rocket force and other technologies in the 1950s after being forced to leave his professor position at Caltech in the wake of the Red Scare. In a 1978 article, Qian described cybernetics as a “technology of organizational management” (zǔzhī guǎnlǐ de jìshù 组织管理的技术). One of his protegees in cybernetic thinking, Song Jian 宋健, would go on to become a leading advocate for the one-child policy.

There are a number of research centers and projects working on various dimensions of “brain-inspired AI.” (类脑 Lèi nǎo AI) which aim to develop artificial systems based on models of human cognition and learning. Launched in 2016, the China Brain project focuses on the neural basis of cognitive function, brain-inspired AI, and the development of intelligent technologies that mimic the brain’s architecture and processes. The project is supported by the Chinese Academy of Science (CAS) Centre for Excellence in Brain Science and Intelligence, a consortium of laboratories at over twenty CAS institutes and universities, focusing on understanding neural mechanisms of cognition, developing brain-inspired intelligence technologies, and advancing brain disorder diagnostics and treatments. Beijing Institute for General Artificial Intelligence” (北京通用人工智能 研究院, BIGAI) was set up in 2020 in a joint effort of the city government, MIIT, and Peking and Tsinghua Universities. Peking University also helped launch the PKU-Wuhan Institute for Artificial Intelligence in 2022.

Training the Terrain: Autonomous Vehicles

After an hour-long subway journey southeast from Beijing’s city center, I arrive at a new gleaming glass-walled mall in the Yizhuang district. On first glance, the area is unremarkable and virtually identical to the myriad other “new areas” and new districts that have sprouted up on the edge of Chinese cities over the past few decades. But Yizhuang is not merely a typical new area, it’s also home to one of China’s most advanced autonomous vehicle testbeds, Beijing High-level Autonomous Driving Demonstration Zone (BJHAD). In 2020, China’s NDRC released its ’ “Intelligent Vehicle Innovation and Development Strategy, which called for “building a big data cloud control infrastructure platform for intelligent networked vehicles.” This oriented China’s approach to AV development around a principle of “vehicle-road-cloud integration” or 车路云一体化 chē lù yún yītǐ huà. In this model, pilot projects have been developed to deploy intelligent sensing and camera equipment on intersections within testing zones. The approach has been championed by an influential Tsinghua engineer, Li Keqiang 李克强 (same name as the former Premier), and endorsed by several of the country’s ministries and vehicle engineering associations. The idea has been around for a while — Andrew Ng, the Stanford-trained AI expert and former head of Baidu’s AI division, had championed what he called “training the terrain” back in 2016, just before he left Baidu in 2017 to found his own autonomous vehicle startup.

The crux of this approach is that, in addition to vehicles having onboard cameras and other equipment to navigate, intersections are outfitted with smart devices to communicate with vehicles in the area. As an autonomous car outfitted with sensing equipment approaches within 200 meters of such an intersection, the millimeter wave radio (MWR) detects incoming vehicles. Now, say there is a long truck in the left-hand lane. As the car approaches, the MWR and the low-latency cameras on the traffic pole detect the incoming car. Feeding the information rapidly into the mobile edge computing unit, the computer system processes the information. The latency, a measure of the time it takes for data to travel from one point to another, is within 200 milliseconds — around 70 milliseconds is how fast a human can react, so it’s not much slower than a human. Another car approaching the intersection from the perpendicular direction is also detected by the MWR and cameras on the other traffic pole, which also feed into the system. Using the information of incoming traffic, the mobile edge computing unit then communicates with the incoming car, which automatically begins to apply braking, slowing the car down before it reaches the intersection and averting a collision in the intersection.

There are problems with this approach. Intelligent intersections are costly to build and expensive to maintain. The safety benefits are relatively marginal for these “edge cases” that don’t occur often. Autonomous vehicle companies want their systems to work anywhere, not just where intelligent intersections are constructed. So why has China continued to pursue this infrastructure-centric approach? In the view of a former planner who worked for Baidu in Yizhuang, it's more of a political arrangement. “Think of it this way,” he said. “It’s a win-win for the government and Baidu. The local district government wants to attract automakers to invest here. They need to figure out how to provide a subsidy to Baidu. But they can’t buy the cars from them. So they purchase the software and computing infrastructure. Baidu has built an autonomous car factory nearby, so that counts for the local government’s economic development numbers.” The data collected in these “pilot zones” can also be used by the local government, whereas in infrastructure-independent scenarios, most of the data on autonomous vehicle operations remains with the company, such as Tesla or Waymo in the U.S. Foreign companies operating in China, such as Tesla, have been required by regulators to store all data from their operations in China, and refrain exporting sensitive data out of the country to comply with China’s strict cybersecurity laws.

A former Vice President of Baidu’s AV division, Wu Shulin 吴书林, recently founded a startup called Freego (正奇智能技术公司), focused on autonomous personal micro mobility. When bikeshare startups arose in China, they scaled quickly but also led to problems such as piles of misplaced or broken bikes cluttering city sidewalks. These systems also have problems in matching supply and demand, for example, how to get bikes to areas when they are needed most. If personal mobility devices were equipped with autonomous driving features, they could automatically return themselves to areas of higher demand after a user finishes a trip. The company is starting with automated wheelchairs, which are regulated as health devices in China and therefore require less permitting than vehicles. But they also have a larger ambition of expanding into a range of personal micro mobility devices such as scooters, e-bikes, or micro vehicles.

In their office in a startup park on the southwestern outskirts of Beijing, the founder animatedly showed me a diagram of an iterative loop in which devices are trained in real environments, continuously collecting new data on a variety of terrains, environments, and situations they encounter. Each type of device would collect different sorts of data, but collectively, this helps train a general model for navigating a variety of environments, such as climbing up staircases, navigating on sidewalks, or through crowded interior spaces.When I asked what the greatest obstacle to implementing their vision is, the founder replied, “It’s not a lack of government support or policy, but it's really the lack of high-quality AI software engineers.” (Interview, Beijing, 2024).

Robotics

Robots are seemingly everywhere in China today — running marathons, boxing each other. Unitree (宇树科技), China’s leading humanoid robotics company, released robotic dogs that became a social media sensation. Robotics is one of the most promising areas for deployment of “embodied AI” and one in which China already has a commanding position. China operates the world’s largest stock of industrial robots, accounting for over 50% of the global total. Robotic cooking machines have been seen in China for some time, tossing bowls of noodles. So what’s different now? According to Grace Shao, “embodied AI robots are trained on real-world data that uses reinforcement learning and they have developed the ability to “think. Recently, the Huisi Kaiwu platform was unveiled in Beijing as the world’s “first general embodied intelligence platform” for interfacing with robotics and other devices. The idea is that robots could be programmed and customized through this platform to handle specific tasks. The project is overseen at the Beijing Innovation Center of Humanoid Robots, jointly funded by the Ministry of Industry and Information Technology (MIIT), the Beijing municipal government, and other private firms and research institutions. In Shenzhen, Huawei (Shenzhen) Global Embodied Intelligence Industry Innovation Center began operation in 2024 and has cooperation with Shenzhen-based robotics firms Leju Robotics, Zhaowei Electromechanical, and Daju Robotics. Leju’s humanoid robot Kuafu (夸父) apparently offers 5G compatibility, which would facilitate data collection and training of robots for industrial applications.

Implications of Embodied AI with Chinese Characteristics

1. Diverging Models of AI Development, and bifurcation in global AI trajectories: The U.S. centers on abstract, cloud-based intelligence (e.g., LLMs), while China develops AI tightly integrated with physical systems and infrastructure. This divergence has implications for technological standards, ethics, and the global diffusion of AI technologies.

2. Infrastructure as an Advantage/Differentiator: China's infrastructural focus enables deployment of AI in real-world contexts at scale, especially in mobility, urban governance/management, and robotics. This presents a comparative advantage not often captured in typical U.S.-China tech rivalry narratives.

3. Legacy of Cybernetics and Systems Thinking: The enduring influence of cybernetic thought — from Qian Xuesen to current smart city projects—reveals a unique continuity in how China views technology as a tool for social coordination and governance.

4. Human Capital Bottlenecks: Despite policy support, China faces challenges in high-end software and algorithmic talent. The article notes concerns about the availability of top-tier AI engineers, which may limit scalability of embodied AI initiatives.

What can the U.S. learn from China’s approach to AI? So far, U.S. application of AI has focused largely on LLMs and application of AI in enterprise software. This means AI could be monopolized by tech platforms like Google, Facebook, Microsoft, and OpenAI. AI is being embraced across a wide array of sectors. Diffusion of embodied AI could even make efforts to reshore manufacturing more feasible, with the caveat that it would employ fewer workers and offer fewer well-paying jobs. Conversely, a failure to incorporate embodied intelligence could mean American manufacturing becomes even less competitive with China’s increasingly advanced factories.

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Sinocities

Cities, China, Geopolitics, Technology, and everything in between. By: Andrew Stokols ; Phd, MIT Department of Urban Studies & Planning, Masters in Urban Planning, Harvard.

By Andrew Stokols

Patrick McGee is the author of Apple in China: The Capture of the World’s Greatest Company. Our discussion led us through a detailed history of Apple’s relationship with China, where iPhone manufacturing became a project of nation-building.

Cohosting today is Kyle Chan of the High Capacity Substack.

Today, our conversation covers:

• Why Apple moved production to China in the 1990s, and why it struggles to leave,

• How Apple’s obsession with perfection catalyzed China’s industrial upgrading and why it bought every CNC machine in the world

• The political side of production in China, including how Apple’s relationship with the Chinese authorities has evolved over time,

• The rise of Foxconn and other partners in Apple’s network,

• A peer into Apple’s management style, including the “Divorce Avoidance Program.”

Listen now on iTunes, Spotify, or your favorite podcast app.

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“Real Men Own Fabs”

Jordan Schneider: I want to start with the near-bankruptcy moment and the challenges of manufacturing in America in the 1990s.

As you write, Patrick, there was very much a “real men own fabs” energy to hardware manufacturing, where most companies, Apple included, decided that if they wanted to compete, they had to build all the stuff themselves. But as you write in your book, that line of thinking reached its limits in the mid to late 1990s. Why don’t you start our narrative there and tell us that story?

Patrick McGee: I talked to the earliest employees at Apple, and it was part of the ethos that you built your own computers. This is how Steve Jobs and Steve Wozniak met at the Homebrew Computer Club. They’d be taking apart computers, presenting to other people, and Steve Wozniak’s genius was to take apart a computer, improve some of the circuitry himself, and then put it back together in a faster way.

Apple wasn’t doing anything different by assembling computers themselves. That’s what you had to do. I don’t think the electronics manufacturing supply chain existed, certainly not in a globalized sense of taking things from Taiwan or elsewhere. That’s all later.

The computer I give credit to for changing everything was the IBM PC in 1981. Steve Jobs largely misunderstood it because when he disassembled it, he looked inside and said, “There’s nothing special here.” He’s not wrong about that. But what he missed was that IBM had launched a whole new battleground that Apple wasn’t prepared to fight against.

The IBM PC wasn’t about the graphical user interface. It wasn’t about user design or UX. It was about making these things and building them at a massive scale. To do that, they relied on third-party assembly giants. One that I highlight is called SCI Systems, which you could think of as the Foxconn of its day. It was founded in Alabama and played a role in satellites and rockets — it played a role in the Saturn V rocket that went to the moon.

Once they had that military precision, IBM scouted them out and they ended up doing the circuit board for the first PC and then assembling computers writ large. Then they played this massive role, doing that for HP and Dell and all these other companies, along with the rise of a whole new industry of Solectron, Celestica, and Jabil— all these North American companies who outsourced on behalf of the PC giants.

They gave birth to electronics globalization because once you have standardized parts in this booming industry, then the likes of Taiwan can outmaneuver everybody else and start building them in great quality and at great scale. Then they vertically integrated. They went back upstream and did more of the computer until by the mid-1990s, you had Taiwanese companies that were putting together everything and badging it with different names, and then they were even badging it with their own names.

There’s this fascinating 20-year history where Steve Jobs in particular has this DNA that he leaves to the company, which is something like, “We will build it ourselves because we’re going to design it ourselves. That’s how we distinguish ourselves, even as the PC companies go to this outsourcing boom.” When he goes to NeXT Computer — the other company he founded after he’s ousted from Apple in 1985 — he says of the computer, “My favorite thing about it is that it wasn’t built in Osaka.” Obviously Japan was playing the role that China plays now.

There’s something fascinating about that. Even when the narrative after 1997, when he came back, was that Apple had to outsource, it took Tim Cook years to convince Steve Jobs to give up manufacturing. I write about how in 2000, he handed out t-shirts to everybody that said “Mac-tories” on them. He wanted these Mac factories to play a role.

Without the dot-com crisis, you would have had Apple trying to make a push in building things themselves, which would have included building in America. But Apple stock, as people sometimes forget, lost 50% in a single day in September 2000.

They’re almost purchased — well, maybe I shouldn’t say they’re almost purchased, but Gateway thought they were such a contender that they could purchase them. That’s how bad things were at Apple — that Gateway of all companies was going to acquire them.

Anyway, my point is I have this manufacturing-focused history of Apple, that’s a new angle to report on the company, and yet I think it shouldn’t be a new angle. This is a company that manufactures — now they orchestrate the manufacturing — but their DNA was doing it all themselves. This shouldn’t be an obscure angle to have brought a new lens to, but somehow it is. I’m uncovering more than I should have been able to because I think we should have been reporting on this the last 25 years.

Jordan Schneider: It’s fascinating, Patrick, because when people think of Apple’s moat and what distinguishes them from the competition, a lot of folks first go to iOS. We have this America arc, and then we have this “go abroad to lots of different countries and try to find one or more that works” arc. What were some of the starts and stops in that arc in the 1990s and early 2000s before they ended up going to China?

Patrick McGee: This will sound less strange if the listener understands that Apple had a tri-continental strategy for building locally but at the continental level. Apple built its own computers in California and Colorado — that’s obviously for North America. For Europe, they built them out of Ireland and for Asia, they built them out of Singapore.

When they get involved with contractors in the late 1990s, they have them replicate this strategy. LG makes the translucent computer — the Bondi blue color that then becomes Life Savers colors — and LG does it in Korea. But when they expand to meet demand, they do so in Wales and in Mexico.

When Foxconn comes on as a second supplier, this is the meeting of the minds of Foxconn founder Terry Gou and Tim Cook, who’s a pretty new person at the time but is running operations. Foxconn does it in China, which is significant because Foxconn’s Taiwanese and some of the other Taiwanese companies are not in China at that point. I’m thinking of Inventec, for instance, which made the iPod in 2001, and that’s out of Taiwan.

But then Foxconn expands, and they expand to the Czech Republic for Europe and California for America. Once you are comparing costs and efficiency between these three regions, China is winning out time and time again for multiple years, such that by 2003, Apple has effectively given up everywhere else and consolidated into China.

I suppose technically the Czech operations are in effect until 2010 or so, but everything is moving to China because China is tailor-making policies for someone like Apple. Industrial clusters are forming. They’re putting up factories, not in great quality, but at an amazing scale.

I have this funny anecdote with this engineer from Apple in the early 2000s, and he’s literally counting the stairs between floors because it’s so obvious to him that it’s not the same distance between each floor. He’s even measuring the stairs and he’s finding that this is so slap-dash — everything’s put together so quickly. This does, if we’re jumping ahead, have implications for us, because of course, we would never build something that quickly because we would emphasize the quality, the safety, and everything else that we should emphasize.

We would still be doing the environmental paperwork by the time an entire factory in Shenzhen would be built.

John Rubinstein’s anecdote for the iPod is that it’s steel girders when he goes there and sees the iPod factory actually up and running because you get to the second floor and it’s all finished, but the rest of the building is not, and yet they’re still churning out iPods.

There’s this amazing sense that when Apple went to China in the early 2000s, it was very early days. China was not known for quality at the time. They are known as a manufacturer, of course, but they’re not building quality electronics. That was something that Apple played an instrumental role in.

Kyle Chan: One reason I found this book so fascinating — it’s the story of global electronics manufacturing told through one company across a number of different countries. You chart the movement of Apple’s efforts to figure out the best place to manufacture — the one place, the company, the country — that might suit their quality needs. They’re extremely demanding with rapidly changing specifications.

The way I think of it, they’re dating a bunch of countries over time, and you know that they’re going to marry China in the end. They’re going to marry Foxconn. It’s like a rom-com — “When Harry Met Sally” — and you’re going to follow the dating along the way.

Could you tell the story of searching for the right partner? In the background I have in my head the whole “flying geese” model of development in East Asia, conceived by a Japanese theorist in the 1930s about how Japan would take the lead technologically. Then, over time, different sectors would move on to South Korea, Taiwan, and then eventually to China.

The Apple story, the Apple manufacturing story, matches that so well in terms of the search. By the time you go through the process, you’re like, “Okay, come on. I know you’re going to end up in China.” But what were some of the steps along the way? Why did they end up settling on China as the place to be?

Patrick McGee: A saying I love about journalism is that you should always show, never tell. When I was submitting the book, my biggest black swan worry was that my editor would say, “I don’t understand why this book begins in 1996. China’s not in the book for the first 90 or 95 pages. Let’s get there.” But the whole point was, I needed to tell you without actually ever explicitly saying so that Apple had this totally obsessive, maniacal, perfection-oriented, no-tolerance-for-defects attitude.

You need to understand that when they were building something like the iMac G4 — the thing that people might remember because it’s anthropomorphic and looks a little bit like a Pixar lamp — I joke that it looks like it’s ready to break dance. That’s actually the first commercial that Apple used for it, grooving to the beat, nodding its head.

Nobody knew how to build that thing. Apple upended tools and machine makers all across Taiwan to get it done. Without me explicitly saying so, the reader begins to understand that Taiwan is too small to get this done. They’re literally having to get people from the Philippines to fill the factory lines, and they’re using a VCR machine maker in Malaysia. They’re relying on Singapore Airlines for a blade fabrication facility.

You realize that for them to have a meeting about various supply chain conundrums that they’re having, you’re having to get on flights and hand-carry things from one country to the next, which by the way is illegal. They’re doing so with five or six countries as far apart as Singapore and Japan.

When China begins to offer all of this in one industrial cluster around Shenzhen, it is mind-bogglingly good for anyone involved. One thing that I say in interviews — I don’t think I explicitly say so in the book — is that Tim Cook is often credited as the architect of the China strategy. He’s not the architect, and there is no architect. It was the suppliers themselves — and there are hundreds, if not thousands of them — are all choosing China because if they’re comparing Singapore versus China, the labor rates, the abundance of labor, the flexibility of that labor, the hardworking determination of that labor is all off the charts in China versus any other place.

The suppliers themselves are all moving there and Apple is able to take advantage of that movement more than anybody else. If you still want to give Tim Cook a title, I would say he was more like an admiral navigating the macroeconomic seas of supply chains. But he’s not the architect because he didn’t have to strategize anything. Terry Gou was strategizing. Tim Cook was following, but then doing more with what Terry Gou and others were coming up with than anybody else.

Jordan Schneider: Yeah, you have this line: “Nobody architected the move to China, but in one opportunity after another, Apple operations were lured into the country.” I think having a tri-continental strategy sounds ridiculous sitting here in 2025. But it’s also the case that you were scaling hardware manufacturing at an exponential rate for 20 years. If you’re making 10,000, 50,000 computers, it’s not insane.

But as you write about in your book, the number of actual items you’re making is increasing by a factor of 10 or by 50 or even by 100 on a year-on-year basis. It is getting more difficult and complex and the labor required is also rising at an exponential curve. You’re not going to find that many people in Wales and Singapore to do all this stuff.

Patrick McGee: I would emphasize another thing, which is that Moore’s law is decreasing the size of the products. Apple was not a big volume player in anything until 2003. I think in 2003, they made more iPods in a year than they made iMacs in the prior five years.

If you’re shipping things either by air or by sea, the fact that it’s the size of an iPod rather than a desktop computer is a major distinction. When SCI was building stuff in Huntsville, Alabama, it wouldn’t have made sense for them to move over to China and be early on this trend. That would make no sense at all. The computers were too big and bulky. Especially if you went back 10 years when it was a mainframe computer the size of a garage.

Once you’re into laptops, which is where Taiwan first makes its mark, it begins to make a lot of sense. Especially when you get into iPods and then dumb phones and especially smartphones, which then scale — that becomes a dramatic increase in efficiency. The cost per item — the logistics becomes de minimis once you’re doing it in the millions and let alone the tens and hundreds of millions.

Kyle Chan: Speaking of the logistics, I love the parts about United Airlines and the Boeing 747 playing a role in both directions. You’re talking about the product getting smaller and smaller to the point where you can have a Boeing full of iPhones that’s totally worth a flight, more than worth a flight. They’re helping to export this product around the world. At the same time, they’re providing the inputs in terms of the Apple engineers and the managers flying in.

It’s ridiculous — entire flights, I think you had documented, were for Apple staff to go back and forth between Cupertino and Zhengzhou or Shenzhen or other parts of China. It was astounding.

Patrick McGee: You’re finding this poetic symmetry that I didn’t make myself. Well done, Kyle. But to give that anecdote, because that’s pretty funny. I forget which cities it was and in what order, but in 2014 it’s probably Zhengzhou and in 2016 it’s probably Hangzhou, where the same thing happens where Apple convinces United Airlines: “Look, we need you flying nonstop to this place three times a week. It doesn’t matter if the rest of the plane is empty, we will pre-purchase so many of the first-class tickets that you will still make money.”

I think that’s hilarious. People who went to Shanghai and then took the bullet train to Hangzhou beforehand said it wasn’t exactly a schlep — it was pretty easy. But if you were an American engineer who had to go there regularly and you didn’t want to have to deal with the Chinese signs and all this kind of stuff, it was a nice comfort.. Because Apple had so many people going, it was worth them doing it. That was amazing.

The thing that was already out, but maybe people don’t know it, is in 2019, United accidentally leaked that 50 engineers from Apple were flying first class from San Francisco every day. They were the largest corporate client on the planet. When you talk about Apple’s size, there are many things you can point to that show they upend entire industries. But who knew that the airline industry was one of them?

Manufacturing the “Un-manufacturable”

Jordan Schneider: I want to talk about the design of the items themselves. You have this refrain over and over again where people say the contractors who don’t see the future ask, “Are you crazy? We can’t do this.” Then Apple comes up with a new manufacturing methodology that’s both labor-intensive and requires a level of sophistication that they have to teach to their contract manufacturers in order to execute.

Let’s do a case study. Pick your favorite item — which one haven’t you talked about on the other podcast that you want to discuss?

Patrick McGee: The translucent iMac is the one where the chapter is called “Unmanufacturable,” and that’s where I devote most attention. It’s also a computer. Everybody knows there’s one thing I hadn’t banked on — people say there’s a sense of nostalgia when they’re reading the early chapters because they’re going through some of the products they loved as high school or university students.

Jordan Schneider: Totally. I felt the same way. It was very tangible. I remember being 12 years old, going to my uncle’s house, seeing his candy-colored iMac and thinking, “What the hell?” It’s this object from space — but it’s not from space, it’s from these crazy engineers who were battling with Steve Jobs and the manufacturing people. Thank you for that.

These things are in design museums now and in your older cousins’ closets if they were smart enough to keep them.

Anyway, please continue, Patrick.

Patrick McGee: The computer was considered un-manufacturable by the product design team at Apple. The tooling engineers at Apple looked at what Jony Ive had come up with and said, “This can’t be built. I’m not saying it can’t be built at scale — we can’t build one of these in the lab.”

It’s interesting because they had created this thing that’s impossible, yet this is where you get the Apple mentality of “even though it’s impossible, we’re going to figure it out.” In the end, they don’t figure it out and the design has to be changed. But nevertheless, in hindsight, it looks like Jony Ive had tasked them with something that was impossible just for the sake of seeing who would stay on the project to get it done.

I’m not saying that was actually intentional — Jony Ive had to go back to the drawing board and make major changes to the product. But by the time they have a product that can be built, the only people left on the team are those who are willing to try and experiment with all these new things.

If people remember the computer, it has these translucent pinstripes on the front. Those used to be horizontal. What the engineers told me is that they couldn’t be horizontal because of how plastic injection molding works — the mold has to be parallel with the lines. Jony Ive had done something where they were perpendicular to the lines, and that couldn’t work.

They experimented for months. They had specialists come in from the outside to work on the product. What’s fascinating is that Steve Jobs had just come back. This was the product that, in my telling — because I’ve got all these Steve Jobs notes from the summer of 1997 — this is an interesting period where he’s given the role of CEO if he wants it, but he won’t take it. What his notes reveal is that he thinks Apple’s about to die, and he doesn’t want to oversee its demise. He is trying to help and see if it’s possible.

It’s a meeting of the minds with Jony Ive. Steve Jobs goes to the meeting expecting to fire him. Jony Ive goes to the meeting with his resignation letter in his pocket. Instead, they hit it off. What they come up with is the translucent iMac.

If you’ve seen the eMate 300, this translucent product they’d already made — it was a Newton and laptop mixed together — that was the first translucent product they made. You can see how Steve Jobs would’ve gotten excited by that and began to envision what he thought at the time was a network computer. That was their big idea.

They came up with this design. Steve Jobs got all excited about the idea of Apple making a comeback and redefining the aesthetics of the computer. But the first thing that Jony Ive comes up with literally couldn’t be made. The product design team goes through multiple iterations of who the leader is because nobody can do this, but Steve Jobs had inherited this team. He honestly didn’t know if they’re any good.

When they told him it was unmanufacturable and he goes on this tirade where he threatens to sell his “one last fucking remaining share of Apple stock,” he goes to his favorite design consultancy called Lunar. These two guys had actually designed the NeXT computer — that black magnesium cube, if you’re familiar with it. They go through all the blueprints and they agree with Apple’s team: “This cannot be built. This is not a quality design.”

I found this interesting because when I’ve read biographies of Jony Ive, even in grade seven, 12-year-old Jony is all about minimalist designs and elegant sketches.

For me, this was a real turning point where Jony Ive realized, “I need to know more about manufacturing to actually be able to give something that can truly be built.” He does have to change the lines. They do have to make the computer foggier than they wanted it to be because the inside was kind of ugly — the circuit boards were sticking out. That’s something they eventually changed by 1999 or 2000.

He had idealized this computer that couldn’t be built. But the changes that they made — I quote somebody else saying — they’re not major changes. The essence of the idea still lived. It’s still this egg-shaped thing rather than this angular square.

But it is the product that absolutely saves Apple. If they couldn’t figure out how to build it and how to change the design so that it was manufacturable — the term is DFA, designed for manufacturing — Apple wouldn’t exist. It was absolutely clear — the company was going to be bankrupt if this product wasn’t a hit, and it became America’s bestselling computer. It’s quite the dramatic narrative.

Jordan Schneider: I want to tie this to Ren Zhengfei 任正非. We’re running this episode after our series on Huawei, and this story is another one of these “leadership matters” anecdotes. The other thing that struck me about that is how far Steve Jobs was willing to go with the gimmick of, “Okay, this impossible thing — figure it out, figure it out, figure it out.”

There’s a lot of human pressure when all these people are saying, “No, you can’t do this.” Kyle, is there a Ren Zhengfei angle here?

Kyle Chan: Yeah, I think there is. Ren Zhengfei is famous for pushing his team to the limit and then some. There are all sorts of issues related to the work culture — people being driven too hard — but then that culture is carried with those personnel later on when they leave Huawei and go out to other parts of the Chinese ecosystem.

I see this parallel with a maniacal focus on realizing this concept, whatever it is — whether it’s going to be a cutting-edge Ascend AI chip or whether it’s going to be this candy-colored, perfect device that everyone wants to buy immediately when they see it in the store. That kind of drive is very reminiscent.

Terry Gou also plays a huge role in this story, and I see a similar parallel with his personality, although complementary in some ways, he’s so cheap, for lack of a better term. He’s focused on efficiency — he eschews the glitzy corporate HQ of Apple. But they share ultimately the same goal of producing at scale with ruthless efficiency these goods that will make all of them together a lot of money.

Patrick McGee: I’ve got to throw in the DAP here — the Divorce Avoidance Program — because so many marriages are broken up in the first five years of Steve Jobs’s comeback that the engineers are given these different policies to save their marriages. One of them is an understanding that, for example, there might be days when Jordan and Kyle aren’t going to be in to work because their marriages are on the line, and we have to give them a break.

That works well for a time, but we need Jordan and Kyle on the factory line. Instead, it becomes, “If we need to send them to Korea on a random Sunday even though they only got back two days earlier and their spouse is going to be upset, let’s give her $10,000. We need to assuage her because we don’t want to be losing engineers through attrition.”

That was happening to such a degree that all these policies needed to come out. It’s funny — well, I say it’s funny, it’s tragic as well. I’m getting the stories 20 years after the fact. People talk about the dollars being called “Danny Bucks” or “Dan Bucks” in reference to VP of Product Design Dan Riccio, because he was the person who fought for these things.

Sometimes our narrative is overly emphasizing how difficult the Foxconn workers worked, and that’s necessary. Obviously it gets to the point of suicides and suicide nets to prevent that from happening. But the Apple engineers were doing a similar number of hours while also having to fly back and forth all the time. It was causing so much strain that Apple had to institute these policies that engineers talked about. If you talk to anyone on the iMac project in the late 1990s and you mention the DAP, they haven’t thought about it for 20 years, but they immediately know what you’re talking about. Then they start telling stories.

I should say that one guy said, “Never mind the divorces, you need to look at the deaths.” That shook me. I was finding the DAP funny at times, and this person was saying there was nothing funny about it. He could rattle off names of people who had died on the production line or come back and died. I didn’t want to overemphasize that because as a journalist, I can’t determine, when someone died 15 years ago or 20 years ago, that overwork was the cause of death.

Steve Jobs himself says that the reason he thinks he got cancer is he was working so hard as CEO of both Pixar and Apple in 1997 that his immune system was weak and it allowed cancer to creep into his system. Whether that’s the medical diagnosis, I don’t know, but Steve Jobs understood that about himself or believed that about himself.

Jordan Schneider: Another interesting parallel is that the exit opportunities for these people existed. The compensation they were getting was not so different from what they could find at other firms from the Apple side that they couldn’t find other jobs. But there was something to this work that, similar to early Huawei, was not just the money. There is an aspect of team and mission and excitement that was around in this era of Apple that drove the Apple employees to give themselves and give all they had and more to this company and these products.

Patrick McGee: Jordan, let me agree on one part. I do think there’s a band of brothers, bunker mentality that would happen among the Apple engineers putting in the 18-hour days.

On the other hand, Apple later gets sued for collusion because there was an agreement among Silicon Valley giants not to hire from each other’s firms. One of the engineers I spoke with is someone who sued Apple later on because he didn’t understand at the time how being such a high-profile product design engineer at Apple wasn’t getting him job offers. He said, “I’m doing such good work. Why aren’t I being hired by Motorola or Google or whoever?”

Much later, he found out that was taboo. Steve Jobs had yelled at people and the emails came out later. I forget exactly what happened — I’m pretty sure they settled. The evidence was pretty good that there was collusion among the tech giants.

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Kyle Chan: Let’s talk about the example of the CNC machines. One of the parts that struck me — I had heard a little bit of this before, but reading it in the book, I’ve got to read this short snippet:

“Apple dumbfounded the industry when it purchased more than 10,000 CNC machines in a single year, enabling a form of mass production that Steve Jobs called ‘a whole new way of building notebooks.’ Apple even made a deal with Fanuc Automation Group from Japan to purchase its entire pipeline of CNC machines for years to come, shutting out all of its competitors from access, and then scoured the globe for more. ‘There were not enough CNC machines in the world to do the machining that we needed to do,’ one person said.”

I was struck by the scale and also by the — again, this is reminiscent of Elon Musk — “We need this part now. Whatever it takes, fly it out personally, make it happen.” For this Apple story, for the aluminum single-body MacBooks, it’s what it’s going to be. If it takes 10,000 CNC machines, then so be it. We’ll fly them over. Those stories capture the “whatever it takes” mentality.

Patrick McGee: We’ve jumped ahead to 2008 here. This was an achievement of imagination. There’s nothing novel about a CNC machine — I forget how many decades they go back. But the thing is, they build prototypes. Apple had the wherewithal and the imagination to say, “Well, wait a minute. If these things are so good, why don’t we build all of our products using these things?”

My focus is on the MacBook — they got the unibody MacBook — but they’re used in all sorts of products, including the iPhone, and have been ever since. These are machines that individually cost between $500,000 and a million dollars. Who knows what Apple is paying when they’re able to buy them at scale and they have someone like Tony Blevins negotiating for them.

This is so successful that this is the first time that MD (manufacturing design) is put on the map. In other words, it’s the first time Steve Jobs, in a keynote presentation, talks about their manufacturing prowess. This is probably the time — I don’t know this for a fact — that MD becomes MD. Before then, they were a part of product design, and it’s called Supply Base Engineering. Now they’re a part of ops.

It’s interesting that MD doesn’t have their own senior vice president. I don’t know exactly why it’s a part of ops — they should be their own thing — but it’s possible that Apple doesn’t love the narrative of more people knowing about this division because they are the ones where, when my book talks about the geopolitical influence that Apple has, it’s because they’re flying MD engineers who are brilliant, usually based in California, over to Asia to train and audit and supervise and equip these third-party manufacturers with what becomes billions upon billions of dollars of machinery.

This is where I get into the argument that Apple’s influence is like that of a nation-building program.

iPhones and Nation Building

Jordan Schneider: I have a smaller question — more on the design stuff. As the design process is being incredibly creative with the CNC machines, one of the questions I have is to what extent they could have optimized for design features which would have given them more geographic flexibility?

The degrees of freedom that Jony Ive and company were able to operate under are unique in the industry. As we've discussed with the CNC Apple Unibody story and the translucent iMac, they were willing and excited to push the physical design features of their products to the point where the answer at the end of the equation had to be China and Chinese suppliers.

I'm curious whether there were other pathways where they could have introduced different constraints at the design phase. This approach might have allowed them to manufacture more products in different places around the world without losing as much capability. The alternative would be trying to manufacture something like the unibody MacBook—as it was designed to be constructed in 2008—somewhere else outside of China, which would result in significant compromises.

Patrick McGee: That’s a great question. One question that you get now is: why doesn’t Apple automate these processes so that it’s not dependent on China, where you’ve got 400,000 people building an iPhone? That sounds like a rational thing to do.

But what you would be doing is upending how Apple designs its products, which is to say that Jony Ive’s team — and I’m aware that Jony Ive has left, but we’re talking about the golden era here — they could operate with a “no constraints” mentality. In other words, other companies will say from the get-go, “This is going to be automated, so we’re going to design for automation.”

The degrees of freedom under which Jony Ive and company were able to operate is unique in the industry. As we’ve talked through with the CNC Apple unibody story, as we’ve talked through with the translucent iMac, they were willing and excited to push the physical design features of their products such that the answer at the end of the equation had to be China and Chinese suppliers.

But I’m curious if there were other pathways where they could have introduced more or different constraints at the design phase such that you could have at the end of the equation been able to manufacture more stuff in different places around the world without losing as much — without losing as much as you would if you were trying to manufacture the unibody MacBook as it was designed to be constructed in 2008 somewhere else outside of China.

I like to ask people what their favorite Dell computer from the early 2000s was. Of course, none of us has a favorite Dell computer from the early 2000s. It’s not only the money that Apple’s making and investing in China that distinguishes them from others, because they were a small player in the early 2000s.

What distinguishes Apple is what they are doing and the fact that nobody knows how to build it. It’s not a knock against China to say that Apple taught them a lot. When you think of Apple products — whether it’s multi-touch glass or the anthropomorphic metal tubing between the base and the computer for the Sunflower iMac — nobody knows how to build that stuff. I’m not saying the Chinese didn’t know how; nobody knew. The marriage of Apple and China is skill and scale coming together.

The line I use is that Jony Ive and Steve Jobs made Apple products unique. Terry Gou and Tim Cook made them ubiquitous.

Now, if you had a different mentality where you said, “Let’s make these things easier to manufacture, more automation-friendly, to give us geopolitical safety,” that absolutely could have happened. You could have had more boring products, fewer design changes year to year, and you would’ve been able to have a more resilient supply chain based on production in Mexico, for example.

In that world, the first iPhone, if it were built at all, absolutely would have a plastic screen rather than a glass screen. It was only by working with the Chinese factories at their scale and industriousness that Steve Jobs was able to make dramatic changes. Literally after he has presented the iPhone — when he famously announced the iPhone in January 2007 — he was holding a phone that has a plastic screen. It was in the period between him announcing it and it going on sale that Apple upended the entire thing.

They work with a Taiwanese supplier called TPK, which builds the invisible circuitry within the glass so that your finger actually causes an effect. You’ll notice that if you do that on your window, it doesn’t do anything. You need to have a bunch of technology in there. Then they worked with Lens Technology to shape and temper the Corning glass that everyone’s familiar with.

The glass is American-made, but then it has to be shaped, tempered and cut. There are tens of thousands of people working at Shenzhen Lens to do that. You have people like Steve Zadesky, who’s on a whole bunch of iPod and iPhone patents, literally sleeping on the factory floor to get that all done.

China offered something that nobody else has offered. The reason why the epigraph to the book is a “Made in China 2025” document from 2015 that says:

“Without manufacturing there is no country and there is no nation.” Find me another country that has that as their motto, their mantra. You don’t get that just anywhere.

Sometimes I find it amusing that I have a 90-second sound bite on X and someone will say, “This guy’s saying China couldn’t be anything without Apple.” It’s the total opposite. I’m saying Apple is screwed without China because nobody will offer the things that they offer. They were a once-in-a-century partner to respond to the demands of Jony Ive.

If I’m fast-forwarding a bit, the only thing I would say is that Apple thought they were wearing the pants in this relationship for the first two decades — from 2000 to 2020. It’s only afterwards that there’s this realization that, “Wait a minute, we were lured in by the siren call of an emerging superpower who had all their companies willing to do all these things so that they would learn all the technology transfer and put America in a position, and all other industrialized nations in a position, where none of them can compete.” Everything has gone into China.

Kyle Chan: Can we talk about learning and this process of learning and technology transfer? To me, this is such a big deal — not only for Apple, but Apple exemplifies a lot. All these foreign firms that China in many cases very deliberately tried to bring into the country, tried to attract — maybe it’s by the central government, maybe it’s by local government, maybe it’s certain incentives, maybe it’s a whole concerted effort.

The point was to bring in these foreign firms, have them manufacture in China, share know-how, and train a whole generation of not only workers, but engineers and managers. The story of Apple and China captures that fantastically.

To give you a contrast, I love the quote: When Apple was working with Sony in Japan, you had an operations executive from Apple leaving Tokyo saying, “I was in Japan about five minutes, and Apple can teach the Japanese nothing.” This was earlier in the story, and this was a difficult product, but not as difficult maybe as some of the later ones. That story was not one of technology transfer.

Whereas later on, especially for the case of China and Foxconn, there was a very deliberate effort to use Apple as a source of upgrading your entire industrial ecosystem — upgrading your suppliers, upgrading your machinery, your equipment, all of the tacit knowledge, not only the blueprints and stuff that you can license and patent. Some of this stuff was not anywhere in existence. It was pioneered — they were all operating at the forefront.

Can you say more about this process of learning? I read a lot and talk a lot about, from the Chinese side, their very active process of trying to get as much as possible from every kind of foreign firm in high-tech industries. This process of technology transfer and learning.

Patrick McGee: In the late 1990s, Apple actually struggled to find contract manufacturers for its products because they were not seen as worth the effort. We have to remember that Apple was creating things in pretty small volumes, and they were very demanding. The workers at these Chinese factories often did not like working with Apple because you’ve got these overbearing engineers who are dictating all these things. Usually they’re dictating it through translators because these are American engineers who don’t speak the language.

I have these funny anecdotes that aren’t in the book where some engineers have a free weekend, so they decide to go to this factory that they’ve been training up. They cause such hell that when they’re trying to leave the following day, there’s a problem with the car — the wheel is flat or something. As the car drove, it was causing sparks to fly. They’re thinking, “I guess we’ll have to stay here another day.” Then they get a call from the leader of the factory who demands that the taxi driver drive even with the sparks flying and everything, because God forbid these Apple engineers come back because they’re such a pain in the neck.

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This is the sort of level of training that Apple is providing — the sort of stuff that makes you go mad. Yet obviously they’re very, very effective.

My narrative about Terry Gou is that he is the first person to understand: “This is not about making big volumes necessarily, and this is certainly not about making margins, but we’re getting tuition-free, on-the-ground training from these overbearing engineers who are willing to teach our cohorts all sorts of stuff.”

Apple’s orderly meets its match in Terry Gou and vice versa. This on-the-record anecdote from Tony Fadell is that he and his team would come in to train the engineers they’ve been working with and find not a face that they recognize because Terry has taken these graduates and put them on the Dell line or whatever, where they can use their newfound skill sets to actual money-making effect. He’s, in a sense, without Apple’s permission, started a new semester for these other engineers.

I don’t think the Chinese understood that until 2016. That is a key reason why you’ve had Foxconn being squeezed out the last couple of years and they’re having to go to India because Apple’s essentially telling them, “If you want to keep your market share, you need to go to India for us.”

The learning is absolutely fundamental to the relationship between Foxconn and Apple and to why all the Chinese factories are able to do so much. If you want, we can go into the wonky differences between ODM and OEM and why Foxconn does so much better than Quanta or Inventec or anybody else.

Jordan Schneider: Sure, let’s tell that story.

Patrick McGee: In the late 1990s, none of the Taiwanese wanted to be doing assembly. Assembly is how you get the orders, but it’s very low margin, it’s totally cutthroat. The likes of Inventec and Quanta and the predecessors to Pegatron are doing something called ODM work. “D” is for design, and design means more margin, and it also means more investment. It’s an investment that typically pays off.

What it means is that if you’re a Western manufacturer of a computer, you’re already offloading your manufacturing to a third party in Taiwan. But what this will allow you, if you work with an ODM, is that they’ll also do the research and development, and they’ll also do the design. You have less and less to do. It gets to the point where the Taiwanese can literally show a catalog of computer designs, and you choose one. Imagine how much that takes off your balance sheet.

It works very well. The problem, of course, is that the Taiwanese begin branding their own computers and competing against you. If there are times of scarcity of a certain product, they’re going to source it to their own companies rather than to you as the third party.

Apple never falls for this trap, in part because they’re wanting to do so much design themselves. It’s never appealing for someone to say, “We’ll do the design for you.” Foxconn maintains itself as an OEM, a manufacturer — the manufacturing-as-a-service model. They were condescended to because it’s not sexy, high-margin work. Yet Terry Gou has an understanding of Chinese politics that nobody else seems to have.

Kyle mentioned that this is what we get wrong about Chinese communism: it’s not only about the relationships with the federal officials, it’s the provincial officials because the cadres in various districts are incentivized for factory growth. They will offer tax exemptions and bonded zones and tailor-made policies and all sorts of stuff — getting in the labor from the hinterlands or whatever — so that your investment goes to that district and not some other cadre’s.

It’s worth knowing that that is one of the key distinctions between Soviet and Chinese communism. The Soviet system was top-down.

I don’t know that you’d call Chinese capitalism grassroots per se, but I compare it to federalism on steroids. It’s something that we miss all the time.

The reason why being an OEM is important is the labor intensity and the vertical integration that Foxconn introduces. Instead of doing design and R&D, they are just building. What makes them so good at building is having many clients and then allocating those resources. That allows Terry Gou to expand — literally in a real estate sense — building dormitories, building entertainment venues, and having these migrants set up shop in Shenzhen all the time. If you’re doing that, you are making the local cadres in Shenzhen look good.

He’s able to parlay his brilliant investment strategy, his labor intensity, into free machinery, free tools, more labor migrants, etc., in a way that nobody else is able to take advantage of. Apple didn’t understand Chinese politics until 2013 when they were made to, but Foxconn is their biggest partner and Foxconn understands it very, very well.

What’s tragic is Foxconn was never rewarded very much for this. Their margins fell the closer they get with Apple, but the political connections that Foxconn made were instrumental to Apple’s rise.

Made in China 2025

Jordan Schneider: I want to talk about that — the getting rewarded thing. I asked ChatGPT for the market cap of Apple and all of its near-ish competitors. We’ve got Apple at $3.25 trillion. We have Samsung at $300 billion, Xiaomi at $175 billion. Huawei, no one knows, but maybe $100-200 billion. Oppo and Vivo are rounding errors.

We have this big argument. The central thesis of your book is that this was a dangerous trade for America, but we did get a $3 trillion company out of it, even though there was all of this industrial upgrading that Apple helped China do. Setting aside the getting Chinese people out of poverty angle to this, there’s got to be something to be said for the fact that America is now home to one of the largest companies that the world has ever seen.

Patrick McGee: I’ve tried to answer this. If for whatever reason we were living in a simulation and the game ended now, then obviously Apple got more out of this relationship and it was a great deal for everybody, and we lived through a golden age of Silicon Valley focusing on software and China doing the hardware.

The problem is it’s probably not a simulation. The world continues and we’re now at a point where Apple has no Plan B. China for whatever reason has become more belligerent and wants to be self-sufficient. “Made in China 2025 中国制造2025” is a grand master plan to sever itself from the West in terms of automation, robotics, electronics, and other things including pharmaceuticals.

It seems pretty crazy to me that the world’s most valuable company doesn’t have any sort of Plan B. The Tim Cook doctrine, named in 2010, maybe 2011, was to own and control as much as possible and only enter markets where they could be number one or number two. As Ben Thompson from Stratechery constantly points out, the fact that everything’s manufactured in a fairly hostile country is the biggest violation of the Tim Cook strategy that could possibly exist.

Kyle Chan: Another parallel is the way that all of these U.S. chip designers depend on TSMC. I tweeted earlier — and it’s funny, the numbers still hold a year later — but Nvidia, Apple, Microsoft, Google, Amazon, and Meta have a combined market cap of $15 trillion, give or take some trillions. Yet they all rely on TSMC for advanced semiconductors, for AI chips, for smartphones.

It’s incredible that there’s this amount of value that’s created on the American side from these companies, purely from design. All those companies I’m talking about, maybe with the exception of Tesla, outsource all the manufacturing. For the high-end chips, that goes to TSMC. TSMC itself is probably one of the most valuable companies in Asia, but itself is an order of magnitude less.

There are two big questions. One is, how did we get to this point where we were allowing global risk to be concentrated so much on a single firm or a single country? Same thing with Apple and China. But then on the other side too, do you lose something from separating design and manufacturing?

Your stories about Apple engineers flying back and forth, deeply embedding themselves with Chinese suppliers, bringing the machinery, doing this — you have this phrase, “man-on-mirror” structure that I love. That was very interesting. That was actually for Korea, but a similar model later on for China, maybe 10x. How much can the two be separated and how much can you still be innovating at the cutting edge when you know your manufacturers are somewhere else, maybe in a different country altogether, maybe 6,000 miles away?

Jordan Schneider: I want to push back on that characterization. It’s a misnomer to say NVIDIA is a design firm. They’re constantly flying back and forth to TSMC. The innovation required to create not only the chips but these entire racks is incredibly manufacturing and hard tech intensive. It’s not only sitting with EDA tools and rearranging where circuits go. A similar story can be told from their perspective.

Patrick McGee: Andy Grove, Intel’s co-founder, gave a great interview to Bloomberg Businessweek in 2010, where he lamented that everything had left America’s shores. He said we’re going to miss out on shop floor innovation — that if you’re not in the factory working on the next product, you’re going to lose out. He was concerned about the shortsightedness of it, and that was quite a profound lesson.

I come back to this later in the book to highlight how any number of Western companies completely outsource without knowing how to build things anymore. It’s not clear to me that Facebook has any idea how to build the Portal. The Portal isn’t a device that’s out there anymore, but as I understand it, it was a product that was completely outsourced to Asian companies who knew how to do it.

Apple is in a different boat — they do know how to build things. They have the experiential know-how built on proprietary processes. We know about them doing iOS, but they also do software and operating systems for machines. We don’t know about that because we’re not on the factory lines.

The problem, as I quote from engineer Michael Hillman who has 16 years of experience, is that to execute any of those plans, they need China. The line I often use is that an iPhone has roughly 1,000 components. If you’re building a million iPhones a day, that means you’re managing the logistics, manufacturing, and production of one billion components daily. There’s one country on earth that’s able to execute that. Anyone else will take at least 10 to 15 years to reach that stage. Because China is an increasingly belligerent country, they won’t let that happen.

If you follow high-quality engineering on a map, America had total dominance at the end of World War II. They began teaching the Japanese to build radar and electronics industries. When they hit supply constraints and the yen rose in value, Japanese entrepreneurs went to their former colonies — Taiwan and South Korea — to do the same thing. When Taiwan hit its own constraints and had better relations with mainland China, the Taiwanese entrepreneurs 台商 went to China and built immense manufacturing capacity over the last four decades.

The next natural place to go would be India. Vietnam to some degree, but Vietnam doesn’t have the size. India is the next logical place if you play this game. But no one knows that better than Beijing, and they want technology transfer to be a one-way gate. The information comes in, but it certainly doesn’t go to Karnataka.

That’s where Apple has this big predicament right now. It makes perfect sense to set up production lines in India, but the machinery is now produced in India and blocked by Beijing. The experiential know-how is in the minds of Chinese engineers — from low-skilled workers to PhDs — and they can’t get visas to India. That’s why Apple is captured. I’m not using that as a line to sell books. I don’t know what strategic decision Apple can make that would untie the knot with China. The more plausible scenario is that they retie another knot and end up with a bifurcated supply chain. But that’s not in China’s interest, and if it’s not in China’s interest, then good luck to Cupertino — I don’t know how they’re going to execute that.

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Kyle Chan: This is a very big topic in the scholarly and development world about whether this whole “flying geese” model — Japan, South Korea, Taiwan, China’s moment — whether that ends with China. Apple is perhaps one of the best examples, but there are many other areas where maybe the auto industry will end up in China and there’s no next flying geese destination. Maybe a little bit to Vietnam and Thailand for transshipment to get around tariffs.

India is always the question. India wants to be next and has been waiting for a long time, watching China’s rise in anguish, thinking “that should be us.” They’re making a big push with manufacturing and have their own major industrial policy, especially targeting iPhone and consumer electronics manufacturing. To some extent, there seems to be success on paper — the oft-quoted statistic that 20% of iPhones are now assembled in India.

But there are big questions about how much of the real supply chain can be brought into the country the way China had done, whether that’s bringing in foreign firms to invest in manufacturing or cultivating domestic suppliers.

Jordan Schneider: The case study I’m looking forward to seeing play out over the next few years is wearables. Meta made all of the Oculus devices in China, and a few months ago, they said they’re going to try to get GoerTek, their Chinese contract manufacturer, to do half of it in Vietnam. Good luck with that.

Google’s now getting into the game. They had a big announcement a few months ago and did a big talent acquisition of HTC, which was a Taiwanese-based VR company, and are obviously trying to price all this in and diversify.

But you have six or seven Chinese manufacturers who are ahead of the game when it comes to what’s currently on the market in the West — when you look at Meta Ray-Bans as the main thing people have been exposed to. There’s that dynamic, but beyond creating redundancies around the world, it’s clear that doubling down on China will get you to the frontier of technology faster than trying to be cute in different countries.

The Apple Vision Pro — not a huge commercial success, but an incredible technical accomplishment — give me a break if you think you can try to make that at scale or with anywhere near the level of policy and precision that Chinese contract manufacturers were able to deliver.

Patrick McGee: It’s worth noting that’s Luxshare, not Foxconn — the rise of the red supply chain in action. The other example I’d point out is Sam Altman and Jony Ive coming up with their next device. Where’s that going to be built? If you’re Jony Ive, you might demand the best, and the easy thing would be to say, “Of course we’re going to work with the Chinese partners that he knows from three decades at Apple.”

On the other hand, he must be more awake to the issues I point to in the book than anybody. He might very well know the political agenda of Trump and all the ways that could be used in his favor to build out a nascent supply chain here.

It’s much easier to do when you’re beginning to build units literally in the tens because you’re doing prototypes, rather than in the quarter billion that Apple deals with — Apple’s scale is so big that sometimes you get off by an order of magnitude.

Apple in China, Future Edition 養虎為患

Kyle Chan: The phrase I kept thinking about was “training your replacement.” Apple is different, but there’s this pattern we notice repeatedly where China brings in foreign firms attracted by China’s efficient, nimble manufacturing base. They set up shop, and then — maybe it takes decades — you end up with a whole crop of Chinese competitors that first nibble away at your market share within China, then start expanding and going global.

You see this happening right now with the EV industry and Tesla. There’s a whole debate about how much Tesla turbocharged China’s EV industry or how much was already there, with Tesla playing a catfish role.

Reading your book, Apple had some of this problem. Samsung is the most famous long-term global competitor, but also Huawei and then a whole fleet of Chinese smartphone competitors — Xiaomi, Vivo, Oppo. You talk about how Apple kept trying to innovate on both design and manufacturing to stay a step ahead of the competition, at least up until recently. They were able to maintain their position in the global market, even within China, even with all the pressures of domestic competitors, in the high-end smartphone market.

Could you talk about this problem and how Apple dealt with this feeling of potentially creating the very competitors that become existential threats in other industries?

Patrick McGee: This is a great segue into one of my favorite chapters, Chapter 36, called “Five Alarm Fire”, because this is what happens when Apple realizes the competitors in China have caught up with them.

What’s amazing about the chapter is that it’s exclusively based on court documents that were made public but were never found by another journalist. I found them 16 months ago, but I’m the only person who’s written about them, even since I published the book nobody has gone to do their own deep dive. We’re talking about more than a thousand pages — depositions of Tim Cook and others, internal emails between Tim Cook and the board of directors at Apple, between him and production staff and his underlings.

The entire issue is about how the iPhone XR (pronounced “ten R”) is a dud, and they know it’s a dud. It’s geared toward the Chinese market, yet the Chinese are all deciding to buy a competitor from Huawei. Apple knew this for several weeks and then told investors that everything was fine.

The chapter is called “Five Alarm Fire” because that’s what a VP of Sales or Finance described the situation as — fire department jargon for when at least a hundred people are needed on the scene. The quote from Tim Cook, at least a week before he talks to investors, is: “This is a disaster. We need all hands on deck now.” There are people within Apple who are panicking about this.

What happened is that the tenth-anniversary iPhone is the first one with that infinity pool design — you get rid of the thumbprint and have Face ID. That didn’t ship until November 2017. Then, by April 2018, four or five months later, all four of the major Chinese brands have an infinity pool-like rival. Cupertino was expecting to bask in the glow of this amazing device, and literally everybody caught up.

You realize the Chinese went from mimicry to — maybe they’re still in the stage of mimicry there — but they’re surprising Apple with how quickly they’re able to keep up. Now, fast-forwarding, they’re in a stage where they’re doing things that Apple isn’t doing. The example I always point to is the Mate XT from Huawei, which unfolds twice. There are also silicon carbide batteries in the latest Vivo phones that have better density, faster recharge time, and longer duration.

Apple is no longer the company to pay attention to if you’re looking for the most cutting-edge phone. There’s something disquieting about that, especially because not only are the Chinese manufacturing them, but they’re doing the industrial design and product design. They’ve taken that pyramid structure I described in the book, put it organically in their own companies, and are now outmaneuvering Apple on multiple levels of the pyramid.

Kyle Chan: Now we’re seeing this especially with AI features coming out. Huawei is doing a lot with its Harmony operating system, trying to have AI everywhere you want it — and maybe in many places where you don’t, like summaries where you don’t want summaries, maybe mimicking what iPhone users are getting used to now with Apple Intelligence.

There’s this big question mark about whether Apple will be able to catch up and be on the cutting edge in that space. There are recent issues with linking up with Alibaba, for example, for an AI partner in China. If you don’t have that kind of partnership, whether as Apple, you can still be competitive in the Chinese domestic market.

Patrick McGee: You brought this up because this is mostly post-manuscript for me — it’s not in the book, yet it’s current and dynamic as a discussion. First, Apple has done poorly with Siri. Siri might have been amazing 14 years ago, but it hasn’t kept up. It’s not even a large language model, so it’s not doing the most basic stuff.

Because of Siri’s failure, Apple has to work with a partner. Because ChatGPT or anyone else, such as Perplexity AI isn’t available in China, they have to work with a Chinese partner. In a sense, that’s the closest thing we’re going to see on the product side to Apple having a joint venture — maybe it’s not technically a joint venture, but my book is about how Apple consolidated all hardware engineering into China over the last 25 years.

Are you telling me that, over the next 25 years, they’re going to work hand-in-glove with Baidu or Alibaba and essentially do the same thing with AI?

This is already the stuff of movies regarding existential risk to humanity. We’re talking about the most complex, consequential thing in tech, if not in business or anything writ large. This is up there with fire and the computer. I don’t know how much sense it makes for Apple to be training one of these companies to make their product better, which they would inevitably have to do. They’re not going to use an off-the-shelf AI tool.

Jordan Schneider: I don’t know if they can train themselves to make their product better when it comes to AI.

Patrick McGee: That’s a great point. We are at the stage where you’ll buy your next phone based on the AI features it has, and Apple is very much failing there. We are recording this during WWDC, so who knows? Maybe we’re way wrong by the time this comes out, but I feel like that’s not going to be the case. They’re behind in AI in an embarrassing way.

Jordan Schneider: One more detailed question before we do a closing one or two. The $55 billion annual investment in China — can you deconstruct that number? Where did it come from and what is included?

Patrick McGee: Apple was on the back foot in 2013 when Xi Jinping 习近平 came to power. They’re worried that either their products are going to be blacklisted or they’re going to have to form joint ventures to continue operating in the country. This is total anathema to Cupertino — not what they want to happen.

This team of people that came into the company, either hired or appointed, called themselves “the gang of eight.” They’re the first people who are senior, living and working in the country. This is where you pass the baton from Foxconn to Apple. Apple realized: we can outsource our manufacturing to Foxconn, but we cannot outsource our political relationships.

They take ownership of this and do their own supply chain study effectively in tandem with the government affairs team. What they realized is that they’re investing $55 billion into Chinese factories — into factories operating in the country.

China has this concept called “registered capital.” Apple, in any given year, doesn’t make as much money as Walmart, and Walmart gets 60 to 70% of their products from China. But Walmart’s not making investments in the country. If you’re importing kitchenware and action toys from China, that doesn’t count as registered capital or investment — that’s just spend. You’re buying that stuff, putting it on a ship, and selling it in Arkansas.

If you were Volkswagen or GM, you’re training workers to run a production line. For a certain period — 18 to 24 months — it counts as an investment into the country. The training costs of setting up a production line count as fixed assets, the same way that putting machinery on the production line is counted.

Apple realizes their investment is more like Volkswagen or GM’s than Walmart’s. They’re not sitting in Hong Kong ordering parts from Shenzhen. They’re going into the factory and training them how to do all this stuff. Their training costs, which are effectively wages, should be counted as fixed assets, as registered capital.

But they go further. Unlike Volkswagen or GM, who set up a production line and have it running for seven years because the lifecycle of a car is about seven years, the iPhone never gets to that stage where it’s running. They’re always upending the design of every product in the portfolio. They’re able to count a whole lot of training costs and wages, in addition to billions in machinery that’s put on the production line, as registered capital.

Someone could debate whether all that spending should actually be counted as investment, but it’s not an argument with me — it’s an argument with Apple and with Beijing, which accepted the argument. That’s where the money comes from, why it’s counted as registered capital, and what distinguishes them from other companies that don’t do the training. Other companies are buying off-the-shelf parts, whereas Apple is working hand-in-glove with hundreds of factories.

That’s why they’re able to operate without a joint venture — because they can say, “You have no idea what influence we’re having on hundreds of factories across the country.”

Jordan Schneider: For Kyle and Patrick, the contract manufacturers that Apple shepherded — do you have a sense of how their relationship with Chinese handset manufacturers is similar or different?

Kyle Chan: There’s a lot of overlap. You can break it down — Lens Technology is a supplier not only to other Chinese smartphone manufacturers but to others as well. GoerTek and some of these suppliers supply across the board.

The order of operations depends, but some of them were brought up by Apple and then helped the rest of the Chinese supply chain. Some of them were already serving what were, for them, lower-tier customers like Oppo and Vivo before they got their Apple contract. It’s a mixed bag.

I also love the part where you mention Apple trying to navigate Chinese politics, because good luck to anyone trying to navigate that.

They tried to cozy up to Sun Zhengcai 孙政才, who was the party secretary of Chongqing. Apple tried to invest in data centers there, which at a local government politics level is great — you want to show that you’re bringing in investment, generating economic activity, especially when it comes to anything high-tech. That’s a bunch of gold stars.

That turned out to be a mistake because Sun didn’t end up becoming the successor to Xi — it turned out Xi was the successor to Xi. Sun didn’t even end up in the very top echelon of party leadership.

There are other ways where Apple has been incredibly adept, especially Tim Cook, at navigating Chinese politics and American politics at the same time. It’s not a job I would envy, although he’s probably pretty well compensated.

Mood Music:

This is a repost of an article by Jon Sine of the Cogitations substack.

And Suffering Will Be Your Teacher

Xi Zhongxun was born into a fallen world. That, at least, is something the father and the son, whose youth was forged in the Cultural Revolution, have in common. But if we speak literally rather than metaphorically, the world of the elder Xi was not fallen, but falling apart. He was born in 1913, in the desolate northwest of China, as a scourge of European guns, germs, and steel was unleashing forces that would sweep the world’s great agrarian empires—Ottoman Turkey, Romanov Russia, and of course Qing China—into the dustbin of history. These same forces would pull Zhongxun, like so many young radicals of his time, into the dark vortex from which modernity would crawl. The birth of modernity in China was a bloody and terrifying upheaval. Anything, Mao quipped, but a dinner party.

Modern minds may struggle to comprehend the youthful Zhongxun. One could begin, as The Party’s Interests Come First does, with the shocking story of how he tried to murder his teacher at the tender age of 14. One could describe how famine stalked Zhongxun’s family, distending his belly and those of his orphaned siblings, claiming several of them. One could note that Zhongxun’s first wife was only eligible because her first husband had his head severed from his body by one of the various warlords and militias—and it was she, an eighteen year old girl, who had to find and bury the carcass.

Images of death and suffering have burst on to our social media feeds in the 21^st century. For most of us they disappear as quickly as they arrive, a flash on the screen sent away by the next swipe of the finger. Inhabiting the mindscape of Xi Zhongxun is hard, perhaps impossible—it would require experiencing things we never have, lingering on them for more time than we are comfortable or perhaps capable. Terrible and turbulent days of unceasing insecurity, death, and suffering are mercifully, for most of us, foreign.

But Zhongxun and his revolutionary kin came to know suffering like a first language. It spawned in them a zeal for purpose and meaning; a drive to find something that could not only bring order to a chaotic present, but something that could redeem a fallen world, that could make sense of seemingly senseless suffering. Suffering shaped and inexorably drew people toward causes bigger than themselves. Toward things that, as Viktor Frankl would have understood, transformed the very meaning of suffering. For some, like Zhongxun, suffering became the crucible in which the meaning of their lives was forged.

There was nothing inevitable about Xi’s trajectory, however. Subjected to similar suffering, any number of men or women might have chosen a different path. For Xi, the road he walked was shaped as much by happenstance as by conviction—introduced to the basic concepts of communism, almost by accident, first by a teacher and then by an educated prison mate. As Torigian reveals in his prodigious excavation of Zhongxun’s life, Xi would later recall that he knew nothing of communism when he first joined the cause. It was not the Communist Manifesto, Lenin’s Imperialism, or any other Marxist-Leninist tract that first kindled his passion. It was his own suffering, reflected back to him in the pages of a novel: The Young Wanderer. “If other poets,” the author, Jiang Guangci, would write, “pride themselves on being artists ahead of their time—creators of beauty—then I pride myself on being a true son of the age, a singer of the storm.” Much as Stalin drew strength from Georgian heroic tales (from which he also took a nickname, Koba), Xi, too, found inspiration in literature. By chance and circumstance, his creed became the communist one, and his devotion was given to the Communist Party.

If Zhongxun’s conversion to the communist cause was shaped by chance and far from foreordained, it was also part of a larger pattern. Like the old Bolsheviks profiled in Slezkine’s House of Government, Xi was one of many youths who gave themselves wholly to a cause. And once he made that choice, he never wavered. The many bloody trials and tribulations he endured in service of the Party—the only force he genuinely came to believe that could save China—hardened a commitment that would prove unshakable. Part of this devotion was deeply personal. With both parents dead and little family to call his own, the Party became his surrogate kin. The “forging” he underwent in those early revolutionary years—from infiltrating the Nationalists in his teens and twenties, surviving multiple assassination attempts, to becoming one of the youngest pioneers of the northwest base where the Communists would eventually settle in Yan’an, a place where he would both purge and be purged—took on a fetishistic significance in later memory.

For many Chinese Communists, and revolutionaries the world over, suffering was their teacher. And it taught them that only total devotion to the cause, of which the Party was the sacred embodiment, could deliver salvation. A close reading of Torigian’s biography enables the modern mind to feel this.

Do Not Wait Until The Evening to See How Splendid the Day Has Been

As Torigian reminds us, Zhongxun is often remembered in popular conception as one of the most humane figures the Party ever produced—held up as a symbol of reform at its most principled, a legacy now sometimes invoked to cast Xi Jinping as an unfilial son who has betrayed his father’s path. But as Torigian painstakingly shows, Zhongxun defies easy categorization. The elder Xi’s life, Torigian writes, is “a powerful statement about the misleading nature of grand narratives” (page 535).

Xi the “reformer” initially opposed the household responsibility system. He despised materialism. He railed against the corrosive threat of individualism. As Torigian writes, quoting him intermittently:

“Individualism was a ‘germ.’ Even if small, this germ ‘does not fear the heavens, does not fear the earth, and it is extraordinarily daring.’ He continued, ‘Even if you weigh eighty kilograms, even if today you have only a tiny, tiny bit of individualism in your body, once it develops, it will devour you whole.’” (p. 194)

Zhongxun, for his part, routinely and enthusiastically affirmed his commitment to Deng’s Four Cardinal Principles. The tension between the “Three” and the “Four”—as Torigian frames it, the economically reformist spirit of the 1978 3rd Plenum versus the enduring imperative of the Four Cardinal Principles to uphold the Party’s authoritarian core—runs through the Party as well as Xi.

A Lighter Side to Xi Zhongxun: At Disney Land (1980)

Underlying it all is the deeper tension at the core of Zhongxun’s life—the conflict between humaneness (人性) and Partyness (党性)—between what one thinks is right and what the party demands or deems acceptable. Despite his difficult youth, Zhongxun somehow sustained a gentler, more conciliatory side. It was further honed through years working in the United Front, where he often favored dialogue and co-optation of local power brokers over coercion in dealings with ethnic minorities, religious groups, and other non-Party actors. One striking example comes from policy in Xinjiang, where, as head of the Northwest Bureau, Xi intervened all the way to the top to overturn a hardline approach pushed by Deng Liqun and Wang Zhen, figures typically cast as staunch conservatives. In doing so, he was willing to bear the enmity of Deng and Wang (which would surface in due time) so as to forestall a more repressive campaign against religious believers and nomads there, favoring instead a more peaceful strategy of co-opting and courting local power brokers.

And yet, as the aptly named book reflects, when the Party’s interests were on the line, they always came first. If the Party needed someone eliminated, Zhongxun would—and did—comply. As he did in Xi’an in the early 1950s, fulfilling Mao’s mandated execution quotas, and earlier still during the Shaanxi base area purges of the 1940s, when Xi was county secretary of Suide. Zhongxun also remained conspicuously silent during the Tiananmen crisis, despite holding the prominent, and at the time very relevant, post of NPC Vice Chair—perhaps shrewdly foreseeing Deng’s violent verdict and not wanting, once more, to end up on the wrong side of Party history.

A Tougher Side of Xi Zhongxun: His Portrayal In Hagiographic New 39 Episode Miniseries (2024)

The prodigious depth of Torigian’s research invites comparison with Robert Caro. In Working, Caro recounts a formative piece of advice from his early days: “Turn every page.” Across roughly 2,000 endnotes and an extraordinary range of Chinese-language sources, Torigian shows the same tireless commitment. His book is not only a biography, but a repository of primary sources and a work of translation, with many materials rendered into English in full or in part for the first time.

Amid the mosaic of sources, three stood out to me. First is Xi’s official Chinese biographer, Jia Juchuan, whose three-volume life of Zhongxun is thoroughly mined. Torigian describes Jia as “more likely to omit than mislead,” and his account is triangulated with other key works like The Chronicle of Xi Zhongxun (习仲勋年谱) and Biography of Xi Zhongxun (习仲勋传). Second is Li Rui—former Mao secretary and high-level Party insider—whose private diaries, now archived at Stanford, offer invaluable glimpses into elite politics. Torigian draws on them carefully to add texture and insight. Third is Warren Sun, a towering figure in Australian China studies. Alongside Fred Teiwes, Sun has long set the standard for rigorous political analysis, and has done more than most to recalibrate Deng’s legacy—as both architect of reform and calculating autocrat, including his role in sidelining the more consensus-minded Hua Guofeng.

But if Torigian’s research ethic recalls Caro, his narrative style diverges sharply. There is no luminous epigraph urging readers to “wait until the evening to see how splendid the day has been,” as in The Power Broker. Instead, contradictions are foregrounded, ambiguities embraced, and tidy storylines deliberately refused. This is a book that resists resolution. Considering how often—and for how long—both internal participants and outside observers have misunderstood Chinese politics, such caution is not only reasonable but necessary. So many statements must remain provisional, with multiple streams of evidence pointing in suggestive directions but rarely converging into certainty. Such are the realities of writing about a man operating at the center of a system that is built around secrecy.

One of the central lessons of The Party’s Interests Come First is that the familiar labels used in China-watching—reformer versus conservative, or more morally charged binaries like good versus bad—often collapse under scrutiny. Torigian dismantles these categories, showing how supposed heroes were less heroic than assumed, and villains less villainous. At the top of the regime, everyone was, at one time or another, sometimes simultaneously, a victim and a perpetrator. That is the nature of the Party system. No one’s hands are clean, though some are more stained than others.

Inside the Leninist Machine

A focus on the characteristics and pathologies of Leninist systems, central to Torigian’s excellent first book on succession in China and the USSR, remains at the forefront of The Party’s Interests Come First. This new work, however, offers a more intimate portrait of how easily one can misplay their hand in the murky world of Leninist power politics—a setting in which prestige, manipulation, and coercion prevail. The intentionally hierarchical design of these regimes makes them especially leader-friendly: the top leader reliably stands above the rules and norms, able to reshape them at will. As a result, institutionalization at the apex is exceedingly difficult, if not impossible. Even among the highest ranks, elites operate in an environment of profound opacity, often unsure of the core leader’s true intentions, the current alignment of political forces, or what must be said or done to maintain their position.

Twice in his career, Xi Zhongxun served as a chief implementer to the regime’s chief implementers: first under Zhou Enlai in the State Council of the 1950s, and later under Hu Yaobang in the Secretariat of the 1980s. In both roles, Xi witnessed firsthand how precarious elite politics could be. In early 1958, Mao turned sharply against Zhou for trying to moderate the Great Leap Forward (“Oppose Rash Advance”), stripping the State Council of its economic authority, creating five new small groups to oversee government work, and handing control over the economy to Deng Xiaoping and the Secretariat (who then presided over the most unrestrained phase of the disastrous campaign). Decades later, as a member of the Secretariat, Xi again observed how the Secretariat and the State Council, now under Zhao Ziyang, vied for influence, and how Hu Yaobang—often described as the conscience of the Party—was ultimately purged by Deng. Ironically, as Torigian determines, Deng repeated a pattern he had twice suffered himself under Mao: purging a deputy not for disloyalty or policy differences, but simply because his confidence in him had mercurially wavered (pp. 472–3).

The Old Revolutionaries, Before Their Scattering, On Their Way to Physical Labor

The much-touted “institutionalization” of Chinese politics under Deng Xiaoping is revealed as largely illusory. Torigian’s detailed reconstruction of events surrounding Deng’s autocratic and often arbitrary purges—of Hua Guofeng, Hu Yaobang, Zhao Ziyang (and, as an aside, nearly Jiang Zemin)—paints a far less orderly picture. Deng emerges, in the words of Li Rui, as “half a Mao”: a leader who deliberately preserved a two-line system that concentrated immense discretionary power in his own hands while leaving others to operate in a state of calculated uncertainty. When he did intervene, as in the decision to use force at Tiananmen, it was often abrupt, unconsultative, and final. In this light, elite politics under Xi Jinping appears less an aberration than return to form.

Throughout the book, Torigian revisits key inflection points in Party history: the fall of Gao Gang, the Great Leap Forward, the purge of Peng Dehuai, the emergence of the Special Economic Zones (SEZs), and the ouster of Hu Yaobang, among others. In each case, he draws on an extensive array of sources, often supplemented by anonymous interviews with insiders, to show just how easily both outsiders and insiders have misunderstood events. One striking example is the birth of the SEZs, where Hua Guofeng—alongside Xi Zhongxun in Guangdong—emerges as a central architect. Deng Xiaoping, contrary to the prevailing view, did not formally endorse the zones until relatively late in 1984, after their early success had become evident. “By then,” Torigian notes, “Deng was taking credit for everything. “I proposed setting up special economic zones,” he said. “It appears that the correct path was taken” (page 285). Western textbooks have since gone along with Deng and Party historiography in doing Hua a lasting disservice, reducing him to a caricature as the Maoist ideologue clinging to the “Two Whatevers,” remembered if at all through a dismissive throwaway line.

Factions play a surprisingly minor role in this account, in contrast to works like Victor Shih’s Coalitions of the Weak or Cheng Li’s earlier scholarship, which emphasize the role of patronage networks and elite affiliations. Patronage networks, often assumed to be relatively coherent, emerge here as more fluid and contingent. While factional analysis remains appealing—particularly because ties can be quantified through shared hometowns, schools, or bureaucratic overlap—Torigian shows that many presumed alignments, such as Xi Zhongxun’s with Gao Gang or Peng Dehuai, were overstated, misunderstood, even among Party insiders. Old networks did matter, but they were also often unreliable. Just as typical, power and alignment shifted through opportunism or convenience, as in the case of Ye Jianying’s unexpected role in restoring Xi Zhongxun and landing him in charge of Guangdong, and in the case of Wang Zhen who, despite the seeming historical enmity regarding Xinjiang policy, became the first person to speak up for Zhongxun’s rehabilitation in 1977 (page 251).

Ideology, too, comes in for scrutiny. The arbitrariness of ideological labels often obscures more than it reveals. Party leaders, like the institution itself, frequently held contradictory positions simultaneously. As today, this does not tend to produce dialectical synthesis so much as oscillation and confusion on the part of internal participants and external observers. Torigian is especially pointed in one aside: “Guessing about whether Jinping cares more about ‘ideology/security’ or ‘development’ is a distraction from the basic point that the Party has always cared about both, even though the pursuit of two such goals simultaneously inevitably creates tensions” (p. 543).

What It Is, And What It Isn’t

This is not a book about Xi Jinping—though, if judging by much of the popular media coverage thus far, one could be forgiven for thinking otherwise. There are, to be sure, sections that probe deeply into the younger Xi, most notably Chapter 21, Princeling Politics, which unearths fascinating details about his early rise through the Party in the 1980s. Torigian draws on sources affiliated with the Organization Department and the Young Cadre Bureau (a bureau responsible for identifying and fast tracking promising cadres) to reconstruct how Xi was perceived by contemporaries at the time, including revealing diary entries from Li Rui, who was then working in the OrgDep.

There are also moments of striking personal detail I had never encountered before—such as a scene near the end of the Cultural Revolution, when Xi Jinping visits his father in exile. In a sweltering apartment in Luoyang, where the elder Xi had been sent to labor in a tractor factory, father and son sit smoking cigarettes in their underwear as the younger Xi recites Mao’s speeches from memory, with Qi Xin watching.

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The book does not examine Xi Jinping’s policies today, but it offers a window into how he has internalized his commitment to the Party. Jinping once spoke of confronting profound doubt during his years as a sent-down youth in Liangjiahe. But as with his father, it ultimately appears to not have shaken but deepened commitment to the party. Suffering, for him, became meaningful when understood as a sacrifice. His father never abandoned his loyalty to the Party, despite being purged over a novel, spending sixteen years (1962-1978) in the political wilderness, and suffering greatly during the Cultural Revolution. Torigian counsels: “While some may wonder why Jinping would remain so devoted to an organization that severely persecuted his own father, perhaps the better question is, How could Jinping betray the Party for which his father sacrificed so much?” (p. 539).

Xi Zhongxun and Xi Jinping in Luoyang (1975)

Finally, beyond Xi Jinping, the book is not even best understood as a biography of Xi Zhongxun. Its deeper purpose is in using Zhongxun as a lens through which to examine the history and internal contradictions of the Chinese Communist Party itself. What the book delivers is not just a portrait of the man who fathered China’s current leader, but a window into the moral and political structure of the Party that shaped them both.

Forging Red Genes

If there is a single throughline in Xi Zhongxun’s life, it is this: devotion to the Party above all else. The forging of loyalty through suffering did not remain his legacy alone. It reverberates in Xi Jinping’s own mythology as well. For both father and son, “struggle” and transformation into a loyal cadre take on a near-fetishistic significance, each held up as a model of what a true revolutionary should endure, and ultimately become.

Yet, as Torigian warns, there is no determinism in this process of forging. There is no guarantee that those who “suffer for a cause” emerge more committed. Just as easily, they may come out disillusioned, embittered, or broken. Zhongxun’s own children illustrate this variance: one committed suicide, one became a rule-of-law advocate, several chased money and pleasure, and one pursued power. Xi Jinping may have internalized his father’s legacy—may even have “inherited the red genes”—but the real cliffhanger is whether the next generations can or will.

This remains a central quandary for the Communist Party today: how to cultivate loyalty through struggle in an era defined not by war or revolution, but by peace and development, and how to do so without alienating the very people it seeks to inspire. In China today one frequently encounters the slogan 永远跟党走—“Forever walk with the Party.” But one finds it hard to imagine that China’s increasingly urbane, educated, and independently-minded elite dream of goose-stepping into eternity.

One wonders if Xi Jinping sees the germ of individualism spreading, as his father once did, threatening to devour the party whole. In 2017, a new slogan was popularized: 幸福都是奋斗出来的—“All happiness comes from struggle.” But what kind of meaningful struggle do today’s rising cadres face? What crucible of hardship might shape them into passionately devoted party members, as it once did their leader? And to what lengths might Xi be willing to go to find out?

Coda

Be warned: Torigian’s is not a beginner-friendly book. Readers unfamiliar with the terrain of modern Chinese history or the historiography laid down by earlier giants like Roderick MacFarquhar, Ezra Vogel, and Richard Baum may find themselves overwhelmed by the detail, unsure of the stakes, and unaware of previous interpretations in the field. Likewise, media headline writers and soundbite chasers will find little to grasp onto—and what they do seize upon, as early evidence indicates, may not well reflect the book’s actual content. Torigian refuses sweeping statements, brash generalizations, or seductive narrative arcs. “In many cases,” Torigian writes, “the vagaries of evidence and intention simply cannot bear the weight of the big questions we would most like to ask” (page 536). But those willing to forge insight and meaning out of complexity, contradiction, and contingency will likely recognize The Party’s Interests Come First as a major achievement—one of the finest works on China in the past decade, written by one of the greatest American China scholars of his generation.

Buy Joseph’s book!

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Cogitations

Writing that excavates the social scaffolding.

By Jonathon P Sine

RAND’s Compute Cluster is Hiring

We’re particularly excited about applications from ML engineers and semiconductor experts eager to shape AI policy as well as seeking excellent generalists excited to join our fast-paced, impact-oriented team. Find an overview here. More details below.

The team's work focuses on using compute as a governance tool, but extends to technical AI governance more broadly, including: technical mechanisms for AI governance (e.g., verifying AI agreements, hardware-enabled mechanisms), AI infrastructure (policies, trends, and forecasts), and export controls (designing effective restrictions, assessing their impact, and fixing them). We've achieved strong "product-market fit" for our work—our technical analyses inform major policy decisions and leading AI companies and governments regularly seek our input.

The roles are: Technical AI Policy Associate & Technical AI Policy Research Scientist (senior). Applications are accepted on a rolling basis.

Why China Wants to Steal the Secrets to a Chunky Soviet Hovercraft

Lily Ottinger reports:

Earlier this month, the New York Times obtained an internal document from the Russian Federal Security Service detailing the threat of Chinese espionage. The report specifically outlines a Chinese campaign to snag Soviet aerospace engineers:

China has long lagged behind Russia in its aviation expertise, and the document says that Beijing has made that a priority target. China is targeting military pilots and researchers in aerohydrodynamics, control systems and aeroelasticity. Also being sought out, according to the document, are Russian specialists who worked on the discontinued ekranoplan, a hovercraft-type warship first deployed by the Soviet Union.

“Priority recruitment is given to former employees of aircraft factories and research institutes, as well as current employees who are dissatisfied with the closure of the ekranoplan development program by the Russian Ministry of Defense or who are experiencing financial difficulties,” the report says.

An ekranoplan (literally “screenglider”) is an airplane-esque vehicle designed to fly closely above a body of water, utilizing the ground effect to reduce drag and achieve greater fuel efficiency. From 1966 to 1988, the world’s largest and heaviest aircraft was a classified Soviet ekranoplan dubbed “The Caspian Sea Monster,” which had a maximum takeoff weight of 544,000 kg and a wingspan of 37.6 meters. Since they fly just a few meters above the water, Ekranoplans operate outside the range of detection for many radar systems.

But why is China so interested in acquiring this technology?

Ekranoplans could possibly be used to ferry troops across the Taiwan Strait (the US Navy estimated that some Soviet ekranoplans could carry up to 850 troops or two tanks), although flying over the open ocean can be challenging for ground effect vehicles. The water below the craft must be calm, with waves below 1.25 meters in height; otherwise, the air cushion becomes unstable.1

Regardless, it would technically be possible for Ekranoplan-style warships to fly over the Taiwan Strait on calmer days, and the PLA isn’t considering launching an invasion in the middle of typhoon season anyway.2

With influence from Soviet designs, China has built smaller Ekranoplans like the DXF-100, the Albatross-5 (信天翁5), and the Neptune-1 (海王一号), which can hold 15 to 20 passengers. But it seems that China is more inclined to apply techniques of Ekranoplan design to other technologies. Ekranoplan engineers are intimately familiar with both hydrodynamics and aerodynamics, so perhaps China’s simply believes that these are the most cost-effective engineers to target. But apart from generic overlap with shipbuilding and aircraft design, there is a direct technological crossover between ekranoplans and wing in ground effect drones (WIG UAVs), which are basically like tiny unmanned ekranoplans. The first reports of Chinese military WIG drones surfaced in 2017, and were quickly recirculated by state media rather than being censored. WIG drones are also being developed by Gdańsk University of Technology in Poland and a Danish startup. These drones could be used for naval reconnaissance, transporting goods, or delivering payloads, all while flying outside the range of aircraft detection radar.

While the extent of China’s espionage activities in Russia doesn’t bode well for their partnership (I highly recommend you read the whole NYT article), China appears to have extracted plenty of value from Russian scientists already. Hopefully, Taiwan has a plan to deal with low-altitude amphibious drone swarms. Who knows? Maybe Taiwan has its own team of disillusioned Soviet scientists waiting in the wings.

How China’s Gen Z Is Exporting Chinese Soft Power to the World

Selina Xu is a writer and researcher on technology. She was a former China reporter at Bloomberg News.

Helen Zhang is the co-founder of Intrigue Media and a non-resident fellow in the United States Studies Centre's Emerging Technology Program. She was previously an Australian diplomat.

Since America’s “Liberation Day” tariff blitz, a lot has been said about China’s economic and technological self-reliance, which has given it more leverage in this trade standoff. Under Xi Jinping, China has steadily focused on reducing dependence on Western supply chains and the U.S. dollar, while swamping the world with goods.

Much less has been said about China’s growing cultural self-sufficiency and ability to export soft power. Just a decade ago, Marvel movies topped the Chinese box office while Japanese video games and Taiwanese soap operas occupied the pastimes of youths. In 2025, the highest-grossing movie in China (and in the world) is Ne Zha 2, an animated retelling of a traditional Chinese myth. On Youtube and other streaming platforms, historical costume dramas — often featuring palace intrigue or celestial romance — have gained traction with overseas audiences, especially in Southeast Asia. On phones and PCs, Chinese games like “Genshin Impact” are winning hundreds of millions of players at home and abroad.

The ascendance of domestic content is in part a result of the Chinese government’s push for national rejuvenation through restriction of foreign content—for example, a nearly decade-long unofficial ban on Korean entertainment, including K-pop, when South Korea angered China by agreeing to allow a U.S. missile-defense system on its soil. On April 10, China said it would cut back Hollywood films in retaliation for U.S. tariffs.

But part of this phenomenon is driven by China’s Generation Z, a 270-million-strong cohort born since the mid-1990s, who are more culturally confident and cosmopolitan in their tastes — and willing to pay for good content. Already, Gen Z accounts for 40% of consumption in China, and their influence will only grow, with spending set to surge fourfold to 16 trillion yuan ($2.2 trillion) by 2035.

In recent years, blockbusters like Chang An and Jiang Ziya and popular TV series like Empresses in the Palace and Nirvana in Fire underscore how the youth are gravitating towards traditional Chinese heritage. Some of these draw from epics like Journey to the West, which is one of China’s most-read literary masterpieces, and The Investiture of the Gods, a 16th-century fantasy novel about gods and demons. Others are set in various historical dynasties, but one that comes to the fore is the Tang Dynasty (A.D. 618-907) — dubbed China’s golden age — when its empire was at its most powerful, and when the ancient Silk Road was at its peak. Some have attributed this solely to nationalism, but Gen Z’s love of history is authentic, imbued partly by an education system emphasizing “five thousand years of Chinese civilization.” In 2024, over 62 percent of visitors to China’s national museum were under the age of 35. Wearing hanfu — a style of clothing with flowing robes that dates back more than two millennia — has also ballooned from a niche hobby to a billion-dollar market in China and a global movement on TikTok. When one of us visited Xi’an last year, the ancient capital’s city walls were overflowing with young people dressed in hanfu.

China isn’t alone in indulging in nostalgic, domestic revival — in some ways, this isn’t too different from Donald Trump’s “Make America Great Again,” Britain’s Brexit reminiscence of its pastoral and colonial past, or Putin’s harking back to imperial glory. But Xi Jinping’s ambitions go beyond a mere exercise in nationalism, and should not be construed as isolationism. In his April 16 essay in Qiushi Journal, the flagship magazine of the CCP, Xi wrote, “To build a culturally strong nation, we must more proactively present China’s perspectives, spread Chinese culture, and showcase China’s image — ensuring our soft power matches our hard power, converting our developmental advantages into discourse power.” Beijing is keen on deepening ties with regional neighbors, especially Southeast Asia, which has also been hard-hit by American tariffs but already has a glut of Chinese goods. To bind South-East Asia’s economy more tightly to China’s, soft power can grease the wheels.

One area where Chinese soft power is growing is the gaming industry. By some counts, over 500 million people in China are consumers of anime, comics, and gaming, most of whom grew up watching Japanese anime but are increasingly embracing local content. The rise of the genre can be seen in the trajectory of Bilibili Inc, a Chinese streaming platform that started off as a niche site for anime and gaming fans but has now become a $9 billion public company that dictates mainstream trends — the platform has about 30 million paid subscribers (that’s more than ESPN), who are mostly Gen Z. Young Chinese men are playing “Genshin Impact” and “Honor of Kings” — two of the world’s most lucrative mobile titles and both Chinese-made — while women are playing Chinese otome games that have interactive romance storylines. As local game studios beef up to cater to increasing interest at home, many of these games are also making waves abroad. For instance, the wildly popular “Love and Deepspace” became the most-downloaded and top-grossing interactive story mobile game in Japan last year. Four of the ten top-grossing game publishers in the world last year were from China, according to analytics company AppMagic.

After decades of importing content from abroad, China is now exporting culture to the rest of the world.

China Gen Z’s tastes in apps and brands are also making inroads overseas. Rednote, which has billed itself as a “lifestyle bible” and is especially popular among young women, is China’s fastest-growing social media platform. The company, a surprise winner of America’s early-2025 TikTok ban, has seen global daily active users up 28% in March from last December. On the app, users share lifestyle content featuring a dizzying array of Chinese brands — many of which are now coming to the West. One example is Pop Mart. The maker of Labubu dolls saw its non-mainland revenue grow by 375% in 2024, accounting for about 40% of its total revenue. Another example is Chinese bubble tea — including brands like Molly Tea and HEYTEA — which have popped up on the streets of New York and California, with distinctive aesthetics, lounge-like ambience, and some selling branded tote bags and cups à la Starbucks. In a sign of their growth, at least four Chinese bubble tea brands are preparing to go public in Hong Kong.

To be sure, the government has been a visible hand guiding tastes, though not often successfully. In recent years, alongside a tech clampdown, the Chinese government has tightened its grip on cultural industries, banning “effeminate” men and hip-hop culture on TV, cracking down on idol fangroups, and championing programs that “vigorously promote excellent Chinese traditional culture, revolutionary culture and advanced socialist culture.” More nationalist epics featuring Chinese resistance efforts during the Sino-Japanese War have dominated the silver screens, alongside anti-corruption TV series like In the Name of the People and The Knockout.

As the U.S. turns more isolationist, slashing foreign aid and imposing tariffs on developing countries that depend on export-driven growth, China now has an unprecedented soft-power opportunity to fill the void. While China’s ability to step in could be constrained by the economic challenges it faces at home (the country has scaled back on big infrastructural loans), cultural and technological exports — from games and movies to TikTok and RedNote — will be one way for China to draw closer to the Global South. As Beijing looks to find other outlets for trade, we expect it to wield more soft power, turbocharged by Gen Z consumption, especially in fast-growing markets like Southeast Asia, Latin America, and Africa. After decades of Hollywood and Silicon Valley’s dominance, the world is now standing on the cusp of China Inc.

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Dissecting Taiwan’s Chip Industry

Aqib is a graduate of Harvard University from the Regional Studies—East Asia program. Today, he presents his research on Taiwan’s semiconductor industry.

With waves of export controls from the United States and economic pressure from China, Taiwan’s semiconductor industry — its crown jewel — has been facing the heat from both sides. But headlines often miss the mark by addressing the industry as a monolith. With lengthy supply chains including electronic design automation (EDA) software, equipment, design, manufacturing, and packing, the different sub-industries all have their own economics, and their experiences all vary.

So let’s look at a few examples from the most-discussed sub-industries: advanced manufacturing, mature manufacturing, advanced design, and mature design. Their realities have all been warped in different ways by the recent geopolitical landscape; some have been cruising while others have been collapsing, yet two factors commonly mark their experiences: the tenacity of Chinese companies to get the chips they want, and the AI boom creating profits for anyone who can latch onto it.

Advanced Manufacturing: TSMC

TSMC, has fared remarkably well since BIS export controls. Recent news of the U.S. banning TSMC from all AI chip exports to China in 2024 and a potential billion-dollar fine may seem frightening, but these incidents are overshadowed by TSMC’s continual growth in the Chinese and global market from AI demand. The reason for TSMC’s staying power in the Chinese market (as shown below) is that there is simply no other alternative. If you want to make an advanced chip for AI or other high-performance computing (HPC) applications, TSMC is the only company that can do so. Despite export controls, TSMC’s revenue from China has only increased, and the share of revenue from China has remained relatively steady.

In the face of export controls, how do Chinese designers place orders with TSMC? The answer lies in downgrading and going for so-called efficiency rather than raw power. Chinese AI companies like MetaX (沐曦) and Enflame (燧原科技) reportedly downgrade their chip designs to be just within performance restrictions enforced by BIS export controls. Besides simple downgrading, Chinese companies have begun to focus more on ASICs and FPGAs, less versatile yet still strong chips that can be programmed for specific applications. BITMAIN (比特大陸), which was the cause of TSMC’s recent explosion of sales to China, has been able to buy up leading-edge 3nm chips from TSMC by designing ASICs for Bitcoin mining and AI applications.

How effective these downgraded chips and ASICs are is still an open question. Of course, Chinese companies will say their chips are comparable to GPUs from NVIDIA, and, in theory, Chinese firms can go far with such chips. Basically, instead of asking for a juiced-up GPU that can do everything, they are designing an ASIC that can do a limited set of tasks just as well but flounder at everything else. This strategy could allow China’s AI push to persist despite export controls, especially if they can make up for the weaker semiconductors with better code.

But regardless of whether these chips accomplish their goals, Chinese firms continue to buy them, and thus, TSMC continues to prosper.

Mature Manufacturing: Powerchip

However, the same cannot be said for Taiwan’s mature manufacturing foundries. A perfect storm of COVID-19 and increased Chinese competition has plunged companies like Powerchip into darkness, as the graph below shows.

Mature node manufacturers like SMIC and Hua Hong have been running Taiwanese firms out of business. With subsidies enabling Chinese fabs to cut costs and pressure for Mainland companies to “buy Chinese,” Powerchip is losing the battle for the Chinese market, and Taiwan’s mature chip industry needs to find business elsewhere.

Despite the downturn, Powerchip has found a few growth strategies that serve as a model for Taiwan’s other mature foundries, like UMC. One of these ideas is the Fab IP model. As governments increasingly treat semiconductors as a national security product, Powerchip is attempting to monetize their experience in making and running fabs.

In the Fab IP model, Powerchip signs agreements with other countries and assists in fab planning and operations, while ideally avoiding the construction and operating costs. Powerchip signed such an agreement with India’s Tata Group, which agrees to pay Powerchip royalties for technology transfer while raising the funds for the fab itself. The Indian fab won’t be operational until 2026, but the Fab IP model opens doors for Powerchip’s business. They can no longer compete with Chinese firms on price, but maybe they can compete vicariously through Indian or other foreign fabs. Powerchip is reportedly in talks with Thailand, Saudi Arabia, Israel, and Poland over similar agreements.

Powerchip’s other method for survival is latching onto the AI boom. For TSMC to make AI chips, they require CoWoS packaging technology, which relies on relatively unsophisticated silicon interposers. With CoWoS demand greatly surpassing supply, Powerchip has been able to insert itself into the AI supply chain. In 2024, PSMC opened a new fab in Tongluo, Taiwan, dedicated partially to manufacturing the silicon interposers required for CoWoS for TSMC. Thus, PSMC can still ride the advanced manufacturing AI wave. Advanced packaging demand has shown no signs of slowing down. With TSMC intending to ramp up CoWoS nearly threefold by 2026, Powerchip’s Tongluo fab will certainly be needed.

Advanced Design: Alchip

Taiwan’s advanced design industry has been able to thrive despite export controls. Let’s take Alchip, Taiwan’s #1 AI company, as an example. Their revenue has skyrocketed in recent years, and they have been able to pivot from the Chinese market to the American one as an engine for its growth. (This pivot accelerated when the U.S. placed their biggest customer, Pythium, on the Entity List in 2021.)

Alchip’s success is partially based on its unique position as an ASIC designer during the AI boom. Chinese customers, particularly automakers, still like to use Alchip, since their products are usually not restricted by export controls. However, although the cost of designing a leading-edge chip can run hundreds of millions of dollars, other Mainland designers exist at the leading edge.

Besides its specialty in ASIC design, Alchip has found success through a partnership with TSMC. As a “pure-play design company,” Alchip maintains a close partnership with TSMC, a pure-play foundry, and the design company has a knack for reserving limited fab capacity at TSMC. In particular, Alchip has often been able to gain “capacity support” for the critical CoWoS packaging mentioned earlier.

As American companies are chomping at the bit for AI chips, Taiwanese design benefit from being right next door to TSMC. Alchip has assisted Amazon and Intel in designing their own AI chips to compete with NVIDIA’s GPUs. For the next two years, Alchip orders are skyrocketing with chips for just these two companies, and these orders enable Alchip to keep pushing to the next node.

Taiwan’s advanced design companies have lost out on Chinese business either from customers getting Entity Listed or from Mainland competitors, but these losses have coincided with explosive growth from AI demand. The growth has greatly outweighed the losses, and advanced designers do not seem to be under fire.

Mature Design: Weltrend

The tragic character in Taiwan’s semiconductor soap opera is the island’s mature design sector. This sub-industry has historically been the most reliant on the Chinese market, and these firms are the ones facing the toughest fallout from Chinese competition.

These companies have limited options for survival. Some are attempting to switch to using Mainland fabs to manufacture their chips, risking unintentional technology transfer for only marginal benefits in cost. Mainland competitors can sell chips at a price that would only cover the production costs of Taiwanese mature firms, thanks to subsidies and government help. Taiwan’s mature companies are not as easily able to pivot to the world market either — in the mature chip market, cost is everything. No one wants their TV or microwaves or other analog products to be more expensive.

So how can these companies survive? Taiwan’s Weltrend puts forth one route for relief: taking advantage of the AI boom. Unable to design leading-edge GPUs or ASICs, though, Weltrend is attempting to cement its niche in server cooling fans.

By offering the best chips for server cooling by combining their design skills with developed algorithms, Weltrend hopes it can raise sales for its products as the rest of AI sales go up. These server cooling chips are needed in every data center. This kind of niche in the AI periphery is what some mature firms call the “garnishes for the steak.” They cannot compete with advanced nodes to be the main show, and they cannot compete with China on price. But by finding an irreplaceable position in the AI ecosystem, perhaps mature companies can survive.

Is This a Problem?

Is the collapse of Taiwan’s mature design companies a crisis that must be averted? Depends on who you ask. When speaking to some representatives of advanced design companies, I’ve heard people say that they “want mature designers to die” so that profitable companies can soak up their valuable talent. If this is the case, then perhaps it’s okay for mature designers to dwindle. Maybe Taiwan is simply moving up the supply chain to advanced nodes and leaving the cheaper mature nodes to China.

Of course, mature design companies don’t see it that way. Many are convinced that mature chips must be afforded the same protections as advanced chips. Perhaps it is a national security risk if all our server cooling chips can only be made in China.

If mature chips are just the garnish, then maybe it’s okay for them to fall, as long as we have the steak. But mature chip companies also tend to liken the industry to cars. The car needs its hood and headlights too, not just the flashy engine.

This plight opens new questions for policymakers in the U.S. and Taiwan. Should we be protecting mature chips? If so, how can we protect mature chips? It’s hard to ban based on performance without banning everything under the sun, so policymakers will need to find creative ways to protect the industry.

Tariff-proof Tea

Bryan Cheong is from Singapore, and lives and works on software in San Francisco. You can follow him on X here.

Most of the overseas tea merchants with sources or warehouses based in China that I love have paused their shipments to the United States after the latest tariffs were imposed and the de minimis exemption was struck. But the US has no shortage of tea collectors who have amassed vast stores of aged tea, who found customers even from across the Pacific. Two such collectors are based in the California Bay Area. Probably the second-largest of these belongs to Roy Fong, the founder of the Imperial Tea Court in San Francisco’s Ferry Building, who counts among his stores a 1980s puerh collectionfrom the Menghai Tea Factory, which crossed the border more than 40 years ago and is safe from additional customs and duties. This does not mean that the tea is cheap — aged puerh tea has been prized particularly by the Cantonese in Hong Kong and Southeast Asia. Roy Fong had also previously invested heavily in trying to grow tea cultivars in California, but the arid conditions of the state proved a difficult environment for the plants to flourish in. Nevertheless, tea is an adaptable plant, and forcing it to try to grow under new conditions is how we get new cultivars like Taiwan’s high mountain oolong bushes. Fong might have succeeded eventually, but alas, a fire in 2017 destroyed most of his tea plants and a portion of his puerh collection, so California’s aspirations for domestically producing tea will have to wait for another pioneer. Notable among the Imperial Tea Court’s offerings are the Special Reserve Ripe Puerh, available in cake form and loose, which have been collected and stored in California for the last 40 years. Puerh tea is made from the large-leaf variety of the tea plant, and is grown in Yunnan province in China. Yunnan is the ancestral heartland of the wild tea tree, and ripe puerh is an artificially fermented tea that mellows the large and astringent leaves into an earthy plum-coloured brew. The Special Reserve Puerh can be ordered online, but if you are in San Francisco, I invite you to try it in person at the Hong Kong-style teahouse at the Imperial Tea Court. On the nose, it is like dry leaf litter mingled with moss, sprinkled with a dusting of Ceylon cinnamon. On the tongue, it is sweet and clean, its age has mellowed any muddiness or bitterness and turned the tea rich and smooth with mineral undertones, and it does not turn bitter no matter how long you steep it. In the stomach, it is comforting and warming. The leaves will survive many, many steepings.

I spent two weeks in May visiting family in Tel Aviv. What follows are some scattered impressions.

A week before my flight the Houthis hit Ben Gurion airport so all flights were cancelled except El Al’s. Half the gates were unused at the airport and there were no non-Jewish tourists.

Houthi missiles were better from a lifestyle perspective than Hezbollah or Hamas ones as you get five minutes’ warning instead of just 60 seconds. It surprised me how diligent most people still are in going into shelters. Waking up at 3am is no fun but at least the baby’s crib was in the shelter already.

I met up with an Israeli-American reporter who covers politics for western media. “When my mom in Maryland calls me up to complain about what she saw Trump doing on MSNBC, I pat her on the head and let her know how much worse it can get.”

The hostages occupy enormous mental headspace in every Israeli. Murals and bumper stickers drape the physical space of the city, parents and relatives are constantly on tv. The hostages and their stories seem like a shared language (like how this book review characterized the Marvel Universe today) where first names hold totemic value.

At a playground one day a helicopter flew over and everyone got concerned as they knew it was a military medical transport flying back from Gaza.

Vibes

Is there a city that does good weather better than TLV on a Thursday night? Restaurants and bars pour out into street after street, you see groups of 20+, often intergenerational, out together. Fridays are much quieter as many go home to see their families. Does Israel have the answer for the loneliness epidemic?

No international djs come anymore. Boiler Room memory holed the shows it put on in Israel, but they’re still getting protested because they got bought out by KKR who is apparently too pro-Israel for their audience.

Tel Aviv needs to get abundance-pilled. Rent and housing costs are both maybe 85% of new york city.

Cigarettes are everywhere. Ten percent of Israeli teens smoke, not France’s 15% but far higher than America’s 1.5%. Fancy restaurants have outdoor smoking and non-smoking sections.

Folks called up from reserve duty go out with their gun in flip flops because they have to report the next day and it’s more convenient to carry around.

Taxis charge a 25% surcharge on shabbat.

I ran into one Chinese guy, maybe 30, who’s in town to sell lightbulbs (“we’re midmarket, can’t compete with Philips in America but too fancy for Africa and LatAm!”). He had no idea about the missile warnings.

Food

I do not like salads in general but immensely enjoyed every one I had in TLV. Dishes were always just on the edge of being over-salted. The country has share plate-maxxed.

The burger culture is extremely strong. The most outlandish attention-getting twist on the formula I saw was one shop sprinkling sugar on the bun.

Many restaurants were short-staffed due to reservist call-ups.

Babies

Secular Israelis have more babies than any other comparably rich country. You feel it in the street with lots of families and young children everywhere with even upscale restaurants all welcome to kids. I wonder just how having such ultra-fertile religious sects pushes these numbers up.

People are far friendlier to my 9-month-old than in new york and they’re also more than happy to tell you how to parent. I got told off three times for having a Doona stroller as apparently it’s bad for babies’ backs?

Seeing my child play with other kids too young to know war when Gaza is a 90 minute drive away redefined cognitive dissonance for me. While I was there, former Prime Minister Ehud Olmert published an oped saying that “What we are doing in Gaza now is a war of devastation: indiscriminate, limitless, cruel and criminal killing of civilians…. Yes, Israel is committing war crimes.”

And speaking of war crimes…

Books I Read

Arendt—Eichmann in Jerusalem

I would have read this years ago if anyone told me how funny it was! As she wrote to a friend, “You are the only reader to understand what otherwise I have never admitted—namely that I wrote Eichimann in Jerusalem in a curious state of euphoria.” It shows and is so much better for it.

World-historically funny.

And now a little darker…

This is in dialogue with what Olmert said on Ezra recently.

You have to change the nature of the dialogue and the appeal to the Israeli people and start to talk in a different way. Instead of warning us all the time that we are on the verge of destruction, which is what this government is doing now for 15 years, not just in the last couple of years.

I remember the days when I was fighting Hezbollah. After my war against them, everyone said how we failed and so on and so forth. But a few years later, I started to hear that they are so powerful, that there is a danger to the very existence of Israel if Hezbollah attacks Israel. And we keep hearing all the time that Iran is threatening the very existence of the state of Israel. And we hear also about Hamas today — these days, when Netanyahu talks, why does he need to explain the war? Because Hamas can become a danger to the very existence of the state of Israel.

This has to change. You have to open a dialogue with Israeli society on a different basis, on the basis of hope — something which will change the lifestyle and the hopes of the younger generations. Then we will not have to fight all the time.

“Look, the guy keeps winning, he must be doing something right!”

On the moral hollowness of the generals who waited until 1944 to turn on Hitler.

Career myopia, Nazi-style

Can’t stop pulling quotes from this book it is just too perfect. Of course, literally no-one who made it to Nuremberg has enough guts to defend Nazi ideology—otherwise they would have stuck it out in the bunker.

She closes chapters better than anyone I’ve come across. “Totalitarian domination tried to establish holes of oblivion into which all deeds, good and evil would disappear, but holes of oblivion do not exist. One man will always be left to tell the story.”

TLV Restaurant Recommendations and some more clown excerpts from Eichmann in Jerusalem

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Eva Dou is the author of The House of Huawei, an excellent book covering the personal, economic, and geopolitical arc of Huawei, China’s most important company.

We discuss…

• The life of Huawei’s founder, Ren Zhengfei, who rose from Cultural Revolution disgrace to become one of China’s richest businessmen,

• How Ren built Huawei, and what makes their corporate culture unique,

• Huawei’s strategic entry into developing and high-risk markets like Libya, Iraq, and Iran, and whether the controversial deal with the UK is a threat to national security,

• How Huawei outcompeted Chinese state-owned telecom companies and eventually achieved national champion status,

• How Ren’s personal interest in foreign art, music, and architecture advances Huawei’s market share.

Co-hosting today is Kyle Chan, a postdoc at Princeton and author of the High Capacity Substack.

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Forged in Fire 浴火重生

Jordan Schneider: Eva, let’s start with the Cultural Revolution. How did it impact the future founder of Huawei, Ren Zhengfei, in his early years?

Eva Dou: Huawei’s founder, Ren Zhengfei, comes from quite a humble background. He grew up in rural Guizhou Province, where both his father and mother worked as schoolteachers. His father eventually became a principal, and they instilled in him the importance of learning and a love of reading that continued throughout his life.

At the same time, that academic background made them a target when the Cultural Revolution came around during Ren Zhengfei’s teenage years. His father had worked briefly for the Nationalists earlier in his career, making him one of the many people targeted during the Cultural Revolution. He was struggled against at his school, criticized by students, and eventually put in a labor camp.

This affected his entire family — Ren Zhengfei and all his siblings. It impacted their work prospects throughout his early career. He would later complain that he was unable to get the promotions that his peers received, no matter how hard he worked. His company Huawei is now considered case number one of a national champion in China, but he really started out on the outside of the system, looking in. That’s part of what makes his story arc so dramatic — how far he came.

Jordan Schneider: There are a number of passages that were really evocative for me. There’s this theme of suicide that runs through the book. Ren Zhengfei is an incredible workaholic with multiple divorces who at one point said he was excited to use Chinese national holidays to travel abroad and get more work done.

This connects back to his father’s experience during the Cultural Revolution. You have this line that said Ren Moxun 任摩逊, his dad, also considered ending his life, but he didn’t want to die before his name was cleared, as it would leave his wife and children with a cloud over them. Ren Zhengfei explained that if his father died, his children would have to carry this political burden. “He endured 100 tortures, but would not kill himself.”

Later, Ren Zhengfei said, “The Cultural Revolution was a disaster for the nation, but for us, it was a baptism. It made me politically mature so that I wasn’t a simple bookworm”

When you look at Huawei from the outside and see the handsets, AI accelerators, and base stations, at its core is this stupendously driven human being who was shattered to his core. There are many business stories in China where people come out of the Cultural Revolution — Xi Jinping as well — forged into these super-driven individuals. But obviously tens of millions of people didn’t turn out that way. Even the ones who did end up succeeding beyond their wildest teenage imaginations carry very deep scars that play out over the subsequent decades of their lives.

Eva Dou: Many people have pointed out that Ren Zhengfei, as an entrepreneur and business person, carries this pessimism with him that some attribute as one reason for Huawei’s success. He’s always looking at the worst-case scenario that could happen to his company. Even in the years when business was flush, he would warn his employees that something bad could always happen — they could go bankrupt at any moment and had to be prepared for anything.

These early experiences of facing life-and-death stakes and seeing how fickle the political environment and business can be really did inform him. In many ways, it helped make Huawei a company that could survive unexpected things, which we’ve seen through two Trump administrations and many unexpected developments.

Jordan Schneider: There’s a bit you have later where you talk about how he painted black swans everywhere once he built this giant campus. The Cultural Revolution was the ultimate black swan. Once you live through that, what’s a couple of sanctions violations?

Another illustration of the psychological jumps you have to make to process and move forward from living through that time comes from this incredible quote from his dad when reflecting about his experience being struggled against in middle school. You write: “One day, one of his old students visited him and recalled the struggle session where a classmate had beaten him with a wooden stick until it broke. Ren’s father smiled grimly. ‘I have to thank that piece of wood. Had it been sturdier, I surely would have been beaten until something was wrong with me.’”

It’s a lot. Kyle, are there other business stories that come to mind — aside from Xi Jinping and Ren Zhengfei, which we’ll be exploring in an upcoming episode with Joseph Torigian — about this kind of dramatic arc for Chinese business people?

Kyle Chan: What’s really interesting is that there’s a strong parallel between Ren Zhengfei’s worldview and the view of many Chinese entrepreneurs during these tougher years, as well as Chinese political leaders in their attitudes towards China’s development. This idea especially that we are operating in a very tough world, that we have to rely on ourselves, that there’s danger at every corner and risk, and what to do about that preemptively.

Jordan Schneider: On the arc towards being a national champion, Ren works for the PLA as an engineer for a few years, finally makes it into the party — which was a dramatic arc in and of itself — and then gets invited to this famous Deng National Science Conference in 1978. There, Deng Xiaoping essentially blessed everyone, saying it’s okay to start businesses and do science — you don’t necessarily have to live inside the system to serve the country. That was a big psychological unlock, almost in the way you describe how he reflects on that. Can you talk about these years? Let’s bring the timeline up through 1978.

Eva Dou: The first part of Ren Zhengfei’s career was as an engineer in the engineering corps for China’s military. During this period, he was largely low-key. Occasionally he would gain kudos from superiors for his work, but he wasn’t anyone famous by any means. He probably thought that’s where he was going to stay for his entire career, his entire life.

This abruptly changed because Deng Xiaoping decided to make this switch to begin the capitalist experiment in China. This was coupled with a dramatic downsizing of the military, and he was laid off from the military and sent to Shenzhen to work in this burgeoning private sector.

He’s talked about feeling very disoriented at the time. This was similar to the experience of many people in China who had been in a system that was only a planned economy and suddenly it was all different. They had new ideas, new fashion styles, and new trends coming in from Hong Kong over the border to Shenzhen. He had this sense that he was really far behind — he was already almost 40 at that time — in trying to adapt to this totally new world.

Jordan Schneider: You have this quote where Ren would later tell his colleagues that he’d wasted time during those years when he was outside the establishment, not as a party member. You can read this quote two ways: “I was a soldier for all those years I didn’t join the party. My life was full of adversity. When I think of all that wasted time, I wonder how could I have been so naive and ridiculous that I didn’t understand it all being about compromise and shades of gray."

On one hand, I see that as maybe this guy’s still kind of pissed that the party ruined his parents’ life. But also, there was no way he was going to be accepted as a party member, even though he was an engineer for the PLA, because of his class background — his nationalist background. What’s the right way to understand that quote, Eva?

Eva Dou: I agree, it’s a bit ambiguous. He does give this kind of counsel to his staff repeatedly through the years, advising them basically that politics is not fair. He’s told them straight out that life isn’t fair and you have to keep in line with the political system that we live in. He said Huawei is a Chinese company and it’s a requirement to be patriotic to be part of the company.

That’s informed partly by his earlier experience with the Cultural Revolution. But there’s another part that isn’t talked about much, which is the Tiananmen democracy protests in the late 1980s. It’s remembered largely as an event in Beijing at Tiananmen Square, but these protests were going on across the country. Some of the largest ones were in Shenzhen, where the young people there were very progressive, international, liberal, and bold. They held some of the largest protests.

That was at the time that Ren’s daughter, Meng Wanzhou, was in high school and about to go to college in Shenzhen. Those protests were quashed in Shenzhen as well as Beijing. That also informs the approach and worldview of Ren Zhengfei and other business people of his generation. They remember these things.

Jordan Schneider: It comes back to the thing that Kyle brought up earlier: to what extent does he really believe the nationalist stuff versus just being a business person who wants to do cool science and compete with Ericsson because that’s cool and will make you money and make you remembered?

You have all these quotes where they’re laying it on too thick at times with how much they’re using the nationalist angle and the national strengthening angle to motivate employees. But for anyone in that generation, there has to be some kind of internal narrative that not all is right in the state of Denmark. I don’t really know where to go with that.

Eva Dou: There is one comparison that I look at in the book. Before Huawei in the 1980s, China’s most promising tech company was this company called Stone Group. The founder of that company was bold and radical in his political beliefs. He actually supported the pro-democracy protests at Tiananmen, and it basically ended up with his company being wiped off the map in China.

He ended up having to flee the country shortly after the Tiananmen crackdown. He was never able to return to China again and has lived as an exile ever since. Ren Zhengfei’s generation of entrepreneurs grew up revering this company and these entrepreneurs, and they saw what happened there. Since then, it’s been taken for granted that you have to bend the knee to the political line to build a successful business in China.

Jordan Schneider: One of the interesting leitmotifs of this book is Huawei’s relationship to the state. The story that you talk about, and that Doug Fuller goes into more deeply in his book, is the fact that Ren actually kept the state at much more of an arm’s length than many of his competitors in the 90s and 2000s. He focused on export discipline and investing in R&D as opposed to the cheap, easy money that you can get from government contracts. That was the way he kept Huawei advancing at the technological frontier.

Let’s give a little sense of what the industrial upgrading arc that Huawei went on in the 80s and 90s looked like, and what decisions they made different from competitors who ultimately weren’t able to achieve the levels of greatness that Huawei did.

Kyle Chan: Just to jump in with some broader context here: with China’s effort to develop its own telecom equipment industry and its broader tech industry, there’s this really interesting connection between the role of the state and the role of these different businesses. At various times you have other companies, other state-owned enterprises like Great Dragon that were the real national champions originally. There’s this idea that some companies were seeking to form connections with the state, while others were actively presented as the spearhead for China’s technological and economic development versus Huawei at this time.

Now we know Huawei as playing that role much more prominently. But back in those early days, Huawei was one of many competitors and was actually the underdog. To build on what Jordan was saying, Eva, you had a great passage about how Ren Zhengfei was even worried about taking loans from state banks, wary about becoming too entwined with state interests and all the strings that are attached. Could you elaborate on some of those early years and eventually reaching that status that we now associate with Huawei of dominating the industry? Really, in those early days, that was a story that was still unfolding.

Eva Dou: Especially in those early days, China’s state sector — these state-owned enterprises — had a reputation of being very sluggish and uncompetitive, basically a place where people knew they would stay employed whether they worked or not. This was something that Ren Zhengfei knew meant the death of his company if they became like that. He was quite wary of being too intertwined with the state, especially in Shenzhen, which is where this capitalist experiment was beginning in China.

They saw themselves as different, as forging a new kind of business system than the rest of China. They would call the rest of China “the inland.” Huawei was very aggressive, very vicious in how they went about doing business and also in their expectations for their own employees. They were notorious for firing people summarily if they didn’t meet expectations.

For a while they were doing joint ventures with state-owned companies across provinces in China to try to expand their footprint. That was a big culture shock for the state-owned employees. You have these stories that they were used to taking their daily naps during the day when they got sleepy. Then the Huawei management would come in and clean house, and things would be totally different.

Jordan Schneider: I love the part where, when they start winning, the state-owned company is like, “Hey, come on, this is a private company. Why are we letting them win these contracts?” Can you tell that story? I really liked it.

Eva Dou: It was one of the local officials in Shenzhen who had written a memoir after he retired with some of his recollections of dealing with Huawei and these other companies. He talked about how the state-owned companies after a while started coming to him and complaining that he couldn’t just be supporting Huawei, that he should be supporting them too. He put them in their place and said, “Well, you guys have been getting these subsidies and all these benefits for so long. If you can’t compete with Huawei, you have to look at yourself and see why that is."

Jordan Schneider: They sell cheaply to get market share. Someone at Great Dragon complained to Shenzhen’s Science and Technology Bureau that the local government shouldn’t just support privately owned enterprises. I mean, sorry man, sucks to suck. You could have been Huawei in the 80s, but instead you let Ren do the thing.

We’re in the 90s now. Huawei is a going concern, on the up and up. There is this fascinating blend of Western culture and PLA culture that Ren tries to inject into the lifeblood of how Huawei operates. Can we talk about the different influences that he tries to incorporate and put into his company and how it does business?

Eva Dou: He and his deputy team really felt that they were forging a new kind of business model in China — one that was not the state-owned enterprise and also not purely the Western style of private enterprise. He was seeking wisdom from all different places in the mid-90s and late 90s when he was working on this.

Famously, IBM was the Western company that they hired as a consultant to teach them how to transform from a startup into a multinational company. There were just many things that Ren Zhengfei knew would take them too long to figure out on their own: How do you meet production schedules year after year? How do you plan product launches to remain on schedule? How do you manage your supply chains? They went to IBM and some other Western companies to try to learn this as quickly as possible. At the same time, he was also meeting with leading Chinese entrepreneurs to try to understand what the relationship to the state should be at that time.

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Jordan Schneider: In 2017, I was at PKU in grad school and they have all these recruiting events. Of course I’m going to go to the Huawei one, and they hand out this book that they put out, “The Huawei Way,” where it’s these chapter-long essays of employees reflecting about their experience in the culture. I’m sure you’ve read it.

It’s funny, Eva, because usually when you see business people and they’re defining a new corporate culture, it’s bullshit and they just want to look back on themselves as intellectuals and business innovators. But in all of my reading about Huawei and diving into this book, I mean it is a weird artifact, right? This company and the way it goes about things.

His openness to Western management practices, the eagerness to go overseas and localize while at the same time the wolf warrior, hardcore zaibatsu energy but also up-and-out and “we’re going to fire you if you don’t deliver" — all of that is not something that you see anywhere else and only comes from Ren personally pushing to synthesize his personal experiences and his drive to synthesize a new way of being from a corporate perspective. That’s one of the most fascinating parts of his story and your book in particular.

Eva Dou: In most countries, there are older businesses, businesses that have been around for many years to look back to. In China, just because of the Cultural Revolution, that was all wiped out and there was a sense they’re starting again and have both the privilege and the responsibility to build a new model. Ren has said many times that he wanted to build a company that could last for 100 years. It’s been very much an open question how you do that. It’s only been a few decades since the end of the Cultural Revolution really, so it’s still an ongoing experiment of building a private enterprise in China that can last for a century.

Jordan Schneider: Kyle, do you want to do the East Asia comparison? I think Samsung is kind of the closest analog from a crazy founder, hardcore founder perspective. What other parallels do you see?

Kyle Chan: There are other ones too, like the founder of Honda and also the founder of Toyota, breaking the rules in the early days, not being allowed actually to have a license to produce cars but defying that and then eventually becoming the star player in the industry. You see this again and again, and actually another strong parallel is just the expectations — these sky-high expectations that you get now in Silicon Valley.

I jokingly have talked to people about this book and said, “Wow, Elon Musk would love this approach to just hard charging, ‘Go to Mars’ mentality that Huawei seems to instill in its work culture.” Some of this is nuts and bolts of how you run an organization, but some of this really seems to be, “We can build, we can defy the EUV lithography export controls” — which we’ll get into later. But all those things are just mere speed bumps along the way to these greater global ambitions.

Jordan Schneider: When you read the early Apple stories of just the intensity and the near-death experiences, you get a bit from Steve Jobs at his most unleashed peak. But I really think Samsung is the closest comparison. They have a similar story in their arc to the one that you wrote about, Eva, where everyone signs their resignations and says, “I will sacrifice.” The importance to the country arc that ends up developing is not quite as present in a Tesla or a Honda as it is in a Samsung, which modernized an entire country for better or for worse.

Eva Dou: That’s interesting, the comparison to Samsung. Huawei’s mission has shifted over the years in that in its early days it was not trying to be a company like Samsung. In fact, Ren was very adamant that they were going to be very narrow in what they did — that they were just going to do telecommunications equipment. They didn’t want to be this sprawling multi-armed conglomerate because they felt they would end up not being good at anything.

It’s been a process where they’ve gradually expanded. During the 2000s they began making mobile phones and then smartphones. That was something that generated a lot of debate inside the company. Ren at the beginning was against it. He thought they were diversifying too much and was eventually won over by some of his deputies that this was the way to go. More recently, because of sanctions, they’ve been forced to make more of the nuts and bolts themselves, especially chips.

By how this worked out, they’re now a much more direct comparison to a company like Samsung — they have so many different lines of business. What’s interesting is they didn’t start out that way, and for many years that’s not what they wanted to become.

Jordan Schneider: It’s interesting also because this happens over the course of Ren getting older and older. He has this great line where you said he suspected that smartphones were overhyped. “We believe that the Internet has not changed the essence of things,” he told staff. “A car must be a car and tofu must be tofu."

But if he succeeded, which he did, in hiring all of these hard chargers who are going to want to spin up new industry verticals or whatever — just having them all fight for the same three slots running different verticals in telecom — is actually not sustainable. One of the remarkable things is that he was not stubborn enough to shut down these new business lines. His commitment to investing — what’s the number? Like 30% of annual revenue into R&D — some crazy stat which basically no other Chinese company did in the 90s and 2000s and even into the 2010s — is something where if you’re going to end up doing all that, then yeah, you’re going to end up wanting to branch out into new businesses and grow in different directions.

Kyle Chan: Speaking of branching out to new businesses, I was wondering if you could say more about this moment in Huawei’s rise where they’re getting into a whole bunch of different areas. While they began with switches and telecom equipment, they really started to expand into everything from undersea cables, and then eventually EVs, AI, and semiconductors. Actually, your book points out that Huawei was working on semiconductors from a very early stage and was quite important in China’s broader push into semiconductors. Could you say more about that period and what drove some of that expansion? What was that like for a company that began with such humble beginnings? This is part of the arc leading up to a $100 billion per year revenue business.

Eva Dou: One way to look at it is that their customers — their international customers — are often buying all these different things. From that sense, it makes a certain logic. Smartphones and telecom gear seem so different — one’s very specialized, one is for the consumer — but it actually ended up being a savvy way for them to get their foot in the door into markets where it was quite difficult to sell their telecom gear, such as Europe, because smartphones were seen as much less sensitive technology.

In countries where they weren’t able to sell telecom gear directly at first, they were able to sell small, cheap smartphones or mobile phones. Actually, the customer is the same — it’s these telecom operators who run these mobile shops, where, as a consumer, you would go in and buy a phone. That allowed Huawei to develop these relationships with these companies. In some cases, once they were selling phones, they were eventually able to sell the telecom gear.

Chips are a little different. It started out partly for cost reasons. For some cheap chips, they found they were able to save costs significantly if they were able to produce them themselves instead of relying on foreign suppliers. There’s probably a security component to that too. He said from an early time he’s pointed out the national security implications of telecom gear, and it probably helped assure Chinese officials if they were making some of their own chips. In fact, their early chips were often used for surveillance cameras. That was one of the early lines of business for their chips.

They’ve gradually found that one line of business can help the other line of business. They’ve expanded probably beyond what Ren would have been comfortable with back in the 1990s.

Spare Tires and War Zones

Jordan Schneider: I love this line from the head of HiSilicon in 2019, which is Huawei’s chip development arm, who said, “For years, the unit had worked on spare tires 备胎. But now, today is the decision of history. After Trump’s export controls on the company overnight, all the spare tires we built have become the main tires. Our years of blood, sweat, and tears have been cashed in overnight to help the company fulfill its commitment to keep serving customers."

It’s very emotional working at this place. On the one hand, you have these stories of people — one of the executives talks about how his annoying family will never forgive him for missing the birth of his two children. But on the other hand, it’s clear that for these employees this is not just a paycheck. There is a lot of life fulfillment and meaning that these folks derive from this work. Maybe I was a little too dismissive earlier about them laying it on too thick because, look, we’re in a country where religion isn’t really a thing and you’ve got to find it from somewhere to get you motivated enough to work 80, 100-hour weeks past the point where you’ve already met your creature comforts.

Eva, what are your thoughts on Huawei as a spiritual totem for its founder and employees?

Eva Dou: Definitely, part of Huawei’s success has been very much its founder’s charisma and his ability to motivate his employees to work incredibly hard and sometimes take enormous personal risks in working for this company. There is a spiritual component to it where he is telling them they can find meaning in helping their country become technologically sufficient in key technologies. The United States has been this bugaboo throughout its history that’s held up as a country that is hostile to China’s development, that wants to hold the country back and that they at Huawei would have to surmount.

Through the years some of that has sounded melodramatic and overblown. When the sanctions came down during the first Trump presidency, that made people believe that Ren wasn’t just overly scared, that he had indeed been preparing for what was going to happen.

Jordan Schneider: Another Elon parallel, right. The American company that gives the most spiritual energy to its employees to work really, really hard is SpaceX, with this incredible vision of making us an interplanetary species.

My favorite illustration of the truly devoted service to customers — not just the Chinese government — is during the Libya civil war. Literally everyone and their mother was pulling out of the country. The Chinese diplomats pulled out. Same with Bahrain when they were going through their civil disturbances. But Ren Zhengfei and Huawei were like, “No, we’re going to keep our engineers here. We signed some contracts. We’ll just have two businesses, one for the government, one for the rebels."

You have this great interview with the wife of one of these engineers saying, “Yeah, every time we call him, we hear gunshots in the background.” Libya is not this huge growth market, but it is a fascinating illustration of just how committed this company is to expanding and succeeding.

Kyle Chan: This is a really interesting segue because so much of this book is looking at Huawei’s trajectory over time in parallel with China’s. Some of these twists and turns and even geopolitical strategy at the company level mirrors that of China’s approach. Huawei, especially in the early days when it was really trying to establish itself internationally, was entering these markets that were a bit too risky or too volatile perhaps for some of the more established players. It gave Huawei an opportunity to start working outside China.

It parallels China’s efforts to develop relations with different parts of the Global South — Southeast Asia, Africa, Latin America, Middle East — while gradually seeing ties with the West as being a longer-term project, but one that would be much harder to tap into early on.

Could you talk more about this opportunistic phase in Huawei’s trajectory in terms of its global expansion? Later on, when you see one of these maps of where Huawei ended up, it’s all red Huawei or ZTE 5G equipment all over the world. That’s the later endpoint, but along the way, what was Ren Zhengfei trying to do and how were they trying to make inroads piece by piece into the international market, culminating with the British Telecom contract, which gave them that kind of legitimacy that parallels China’s quest for legitimacy on the international stage?

Eva Dou: Certainly. Huawei’s international expansion can very much be seen as a proxy of China’s broader international relations effort over the decades. The company was founded in 1987, and at the beginning they only focused on the domestic market. Then in the mid-1990s, they started looking overseas.

At the very start, Russia was one of the first countries they looked at. That was partly through diplomatic help — the Chinese Foreign Ministry helped them go over for a trade show and helped smooth the way to their first very small contract there. At the same time, they were looking to countries in the Middle East and Africa in the early days.

There is some history of their eventual run-in with sanctions issues with the United States, which is that some of their earliest customers were countries where the major Western companies were a little more reluctant to go for whatever reason. That included Iraq, Iran, Afghanistan, North Korea.

Then you get to the point where China is entering the World Trade Organization in the early 2000s. Huawei jumped on this trend of internationalizing. That was when you saw them start to push into developed markets, into Western markets more aggressively. Of course, it took many years for them to be established in Europe. But if you look today, there’s hardly any country in the world that doesn’t use Huawei telecommunications equipment to a greater or lesser extent.

Kyle Chan: In parallel with this rise, what’s really interesting is that as Huawei is expanding globally and as Huawei’s star is rising in China as a symbol, you have growing suspicions from the West, especially from the US, about what Huawei is doing and what its real relationship with the Chinese government is. There are concerns about surveillance technology. You have the rollout of smart cities and safe cities programs from Huawei. This ties into the very markets that Huawei is deciding to enter.

In the early years, as you mentioned, Iran and Iraq were some of the earliest cases of Huawei coming on the map in terms of US concerns about security. How did you see this reaction to Huawei’s expansion, especially from the US? You have congressional hearings later on, which is a high point of the book, a point of high drama, where Huawei and ZTE executives are brought in front of Congress to testify and answer basically a pretty tough interrogation session. Something similar happens with British Parliament to a certain extent.

There are growing suspicions rising almost right alongside Huawei’s growing prominence on the world stage. Could you describe some of that and where it’s coming from? Obviously Huawei’s own activities within China contribute to this. It’s not just what Huawei’s doing abroad, but later on, you were one of the earliest reporters on use of Huawei surveillance equipment in Xinjiang, for example. Could you tie all those different pieces together?

Eva Dou: The first incident where Huawei really got on the map for the US government was in Iraq in the early 2000s. Huawei was helping the local government and military build a fiber optic telecommunications network. If you think about it, these older systems where they’re using radio communications — that’s something that is more easily surveyed or hacked. That’s what the US government had been doing. They’ve been using it to keep track of what Iraq’s military was doing. Suddenly those conversations were going underground. Huawei was helping them build these fiber optic lines that ran underground and that were much more difficult to tap.

That was when George W. Bush gave the order to bomb those installations, which would force Iraq to use radio again. This was later explained by some US officials. That was something Huawei was doing for governments around the world, helping them build these more secure communications networks that were harder to survey for Western governments. That was how they came into conflict with the US at the start as a national security concern for the United States.

Later on this became other things. You mentioned Xinjiang and surveillance. Their surveillance systems became a significant line of business for them, both domestically and in countries around the world. These are the modern surveillance systems for an entire city. There are video cameras, but more importantly, there’s the software on the back — there’s facial recognition, there are AI algorithms to help track trends.

That is a more recent iteration, and what sparked the sanctions was the 5G generation of networks being laid out around the world and Huawei seeming poised to win an enormous chunk of those orders. That set off alarm bells in Washington at the time.

Kyle Chan: This gets to a whole question about the role of technology today and to what extent can we separate some of these core functions of what telecom equipment is supposed to do versus issues of data privacy and national security. I wanted to read a quote from the head of global cybersecurity for Huawei at a UK parliamentary hearing. He’s asked about whether Huawei’s telecom equipment could be used for surveillance and data collection and sending that back to China. His answer is: “It therefore does know where you are because it knows where the information is coming from. In that context, telecommunications networks from all vendors know where you are so as to connect you to those networks. Huawei’s equipment is no different from anyone else’s equipment."

This was just a question about whether Huawei’s telecom equipment can track you. His answer seemed to be, “Well, in order for a cell tower to work, that’s really what it does. It has to triangulate your position and make sure you receive and get the signal."

How much of this seems to become only a bigger issue over time? Now we have a whole bunch of questions about not just telecom equipment, but this has entered into many different domains. Everything from TikTok to connected vehicles, DJI drones. The latest one was TP-Link routers. It’s this growing concern from countries like the US about what will happen with data that’s passed through or collected through these systems.

Is there anything that Huawei could do to reassure the outside world, especially in the West? There was a really great example where Ren Zhengfei or a Huawei executive offered to share source code or do a tech licensing deal to just put it out there and say you can look through our source code and see what’s going on, if that’s any kind of reassurance. There are different ways of trying to deal with this issue. But to what extent is it just something like a Gordian knot that can’t be untied?

Eva Dou: The comparison to how US and UK policymakers have looked at this issue is pretty interesting, because until recently, they’ve taken very different approaches. The UK has taken the approach that these security risks can be mitigated, and we are comfortable with it. The US has taken the approach that this is an intractable problem — these security issues cannot be mitigated.

Cybersecurity experts in both countries receive very similar training. Ultimately, it is kind of a political question and a political answer of what kind of relationship you’re willing to have with China, what level of “risk” you’re willing to take on, and to what degree do you see China’s government as an enemy that needs to be blocked by all means necessary?

Until recently, the UK approach had been that they have this center where Huawei has its source code for its products and where UK officials, including UK intel officers, can go take a look at the back end and comb through it and resolve any cybersecurity concerns that they feel they have with it, and they were okay with it. Actually, today, a number of other countries do use this model, and they feel that mitigates whatever hacking risks that they feel there are.

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The US has been on the extreme end of the spectrum compared to other countries in feeling that these are unmitigatable risks that they cannot — that we just can’t use this equipment. That speaks partly to just how the US and Chinese governments see each other, that they see each other as direct rivals, whereas for other countries, it’s not the case.

Jordan Schneider: It’s funny, because there is kind of this spectrum, right, where you have these African countries and Malaysia being like, “Whatever, spy on me. What do I care? It’s not like I could stop them anyway. Might as well save the money with the Huawei kit.” Then we have the UK kind of in between. You’ve got this great back and forth between John Bolton and a senior UK security official saying, “What I don’t understand is why out of all the things — chips, AI, rare earth minerals, whatever it is — your administration has decided that a modest amount of base stations on hilltops in England is the epicenter of your new declared war on China. Why?"

"You got to pick something,” John Bolton replied, but that feels like a facetious response. The deeper one, which is the one you alluded to earlier, Eva, is that losing this entire industry of telecom broadly and base stations in particular to a Chinese player is something that the US couldn’t really countenance as the country that feels like it has more to lose from being spied on by China than even folks who maybe aren’t all the way at the side of Malaysia, but the UK that feels like they can kind of deal with it. Even if they can’t, how bad is it going to be? It’s not like they’re the ones upholding the industrial base of the liberal democratic order or what have you. Kyle?

Kyle Chan: It does tie into this question from the US side too of what are the motivations for each of these things? I see a lot of parallels for the EV industry. There’s a lot of debate about to what extent were the Biden era tariffs on Chinese EVs and then later on the connected vehicles ban motivated by security issues and to what extent was it motivated by economic competition issues about worrying about what will happen to American automakers and US auto jobs along the way.

That just puts the US in a different position than other countries when it comes to its relationship with China and Huawei and a lot of these other rising Chinese tech firms that seem to be now entering into spaces that US companies were comfortable being dominant in for a long time. There’s also that parallel with Europe too, taking a different approach, again with EVs. They have similar concerns, but there seems to be at least a greater interest in investment and production of Chinese EVs within Europe. All of that is just to say it’s a lot messier than merely “let’s block everything Huawei” or whatever, “anything goes.” There’s a full range of different approaches out there across the world.

Jordan Schneider: I want to talk a little bit about the organizational, senior management structure and how it pattern matches to the way the Communist Party structures itself. Can you talk a little about that, Eva?

Eva Dou: Huawei has for years adopted this kind of collective leadership model, which in many ways is similar to how China’s government is run. There’s a senior group of officials, both explicit and also unofficial, semi-retired officials who all have a role in deciding the direction of this company. On purpose, it is a little vague exactly where those lines are drawn of who’s in charge of what.

For now, Ren Zhengfei is still the top guy. He’s talked for years that he’s going to be retiring one day and now he’s in his 80s, and it’s still unclear when he’s going to be retiring. That’s going to be the big test for Huawei, of course, for any company — that initial, the first handover from the founder to the next generation of leadership and if they can keep the company running to the same degree of success.

Jordan Schneider: I want to close on the human arc a little bit. A lot of Western media makes fun of the Huawei campus. The fact that it’s kind of this Disneyland — it has a Versailles, it has a Kremlin, it has all these international styles. This moment that you write about, about him moving villages in middle school, you write that he was astonished when they moved to the county seat and saw a department store. It was the first time he saw a two-story building.

Then, a few decades later, he goes to the US for the first time, sees Las Vegas and thinks it’s the most beautiful city he’s ever seen. These giant buildings and the pyramids and whatnot. Then he builds this incredible company and decides that he wants to replicate all of these architectural wonders from the West. Not really from China, but from the West.

Just that arc of this boy whose dad was principal and was beaten to within an inch of committing suicide during the Cultural Revolution to go from having this really complicated, admiring, but also rivalrous relationship with the rest of the world and looking up to so much that the West has brought, but also really wanting to be able to compete and strive to stand at the same level, if not necessarily playing by all the rules that the Western countries and companies would want them to — that’s just a remarkable arc. That is probably the thing that’s going to stick with me most from this book. When Ren, who’s pretty old now, does end up passing from the scene.

Kyle Chan: This image of him from his early childhood days, really the rural boy from out in the provinces to then later on being able to be this savvy political operator at the national and international stage and basically getting on side with multiple Chinese leaders over time. You write about how he is going out doing deals with, from Jiang Zemin, Hu Jintao, and now Xi Jinping.

We recently had that big meeting with the tech executives, Chinese tech executives meeting with Xi Jinping. Who was there, sitting in the very front and center, was Ren Zhengfei himself. Who could have imagined, probably not him from his early days, that he would be at the center of so much of the Chinese leadership’s ambitions, US-China competition tensions, and part of this story of China’s rise over time.

Eva Dou: It is kind of staggering, the distance he’s traveled since his childhood to where he is today, both personally, his company, and also China, that China is now a true technological competitor on the world stage. That’s part of what interested me in this project — just understanding how much has changed and how it changed.

As far as the palaces that you alluded to that Huawei has built on campus, Ren has said — it’s not only the Western media that critiques it, sometimes his own employees do. He’s talked about this and said, “You guys can gripe about these palaces, but we build them for the customers."

It’s not just him himself. This has been China’s experience, broadly, this transformation. When they bring government officials and telecom officials from across the nation to the campus, this is the same transformation that they are experiencing themselves. It is appealing to a certain part of his customer base, all the glitz and glamour. Most of his international base is the developing world. Huawei is famous for bringing foreign officials on these junkets and wowing them with both the campus and the food and the hospitality.

Jordan Schneider: Eva, are there any stories you want to share from the reporting of this book? In particular, I’d be curious about, in reading a lot of these memoirs and Chinese coverage of the company, what are the narratives that get a lot of play in mainland China that you don’t end up seeing written up much in the Washington Post?

Eva Dou: The most fun part of this was doing archival research for me and trying to find sources that even in China are a bit obscure. You do have the easy narratives, both the international ones about Huawei being a national security threat and within China, Huawei being this great company that’s getting better and better. Part of what I try to bring to this is the smaller voices.

I really enjoyed reading some local government officials’ memoirs in China. As Huawei has interacted with so many officials both within China and around the world over the years, I wanted to bring some of their recollections of the experience of meeting with Huawei, both good and bad. In China, as you know, there’s pretty strict censorship. In memoirs, when people are late in their life and no longer worried about keeping their job, they are a little franker sometimes in their recollections. That’s been an enjoyable part of this process.

Kyle Chan: I was astonished looking through the sources that you cite and the amount of material that you had to go through. I’m sure the sources that you cited are just the tip of the iceberg for everything that you were wading through and trying to sift through. You even chased down a Harvard Business School classmate of a Huawei executive and interviewed them. I was astonished by the lengths you went to really get to all the details of this story, including a ton that just has not been talked about before.

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Eva Dou: Thanks so much. The process of digitization of archival material around the world was really helpful in this project. So many times during the process, I thought about how if nothing was digitized and I had to go in person and just read each page one by one, how long would this project take? It would have taken years and years more than it did. It really gave me an appreciation of the earlier generation of researchers who were doing everything in analog, in person, archival research.

Jordan Schneider: But they didn’t have Twitter to distract them. Eva, how long do you think you’d last at Huawei?

Eva Dou: Oh my goodness.

Jordan Schneider: Say your 24-year-old self. We’ll give you a little boost of energy.

Eva Dou: Well then good. I probably could hack it a couple years, but they are ferocious in weeding people out.

Jordan Schneider: They’d catch on to you eventually.

Eva Dou: Yeah, probably.

Jordan Schneider: Is there a moment or a meeting that you wish you could have been a fly on the wall for?

Eva Dou: There are a few points in their early history where they changed the company’s structure or ownership and I’ve always been pretty curious about what exactly those conversations were. They started out as a private startup — it was a pilot program for private startups. No one knew how long that would last. At some point they shifted to where they were almost more state-owned for a few years and then they went back to being a private corporation.

Kyle Chan: One funny thing that stuck out to me is that Eva, you have pointed out the pronunciation of Huawei among Americans. So many people say “Wawei” instead of “Huawei.” Once you pointed that out, I can’t stop hearing that. People do it all the time and I don’t know where it came from.

Eva Dou: Part of it is the company itself. At some point their PR team was going around teaching people to say the company name this way.

Kyle Chan: That’s so interesting.

Eva Dou: Which is a curious thing.

Kyle Chan: Wow. It reminds me of Hyundai trying to be like, “We’re not Honda, we’re not ’Hi-yun-dai,’ it rhymes with Sunday.” It’s tough.

Eva Dou: They thought about changing the name in the early days when they realized it was so hard to pronounce for international audiences and they batted a few different things around. But in the end it seemed too difficult to change, and we’re stuck with Huawei.

Jordan Schneider: One of the daughters is a singer, right? We have to do that as our outro music. But are there — did Ren ever talk about liking music? Did he have any favorite songs or genres or anything?

Eva Dou: Interesting. I don’t know off the top of my head about music, but he’s always been an admirer of the arts and that comes from his parents and this desire to be a cultured renaissance man. That’s something he’s really encouraged with his employees — for them to spend their spare time cultivating themselves, listening to different types of music, looking at fine art, things like that.

Jordan Schneider: Cool. Aside from the architecture thing, which people are clear on, are there painters or writers? Give me a sense of the Ren Zhengfei cultural constellation.

Eva Dou: Well, classical style art is something he quite appreciates. There are stories of him collecting paintings from around the world and having his employees help him bring oil paintings over from abroad. He’s talked about his family quite liking Europe, liking to go to Europe on vacations. His youngest daughter grew up largely between the UK and China. He often talks about these cultural things to make a point, as part of his outreach to different markets. He talks about international culture that he likes probably more often than domestic.

Renaissance Philanthropy — in my opinion, the most exciting philanthropic venture in the US — is getting a one-year check-in. Kumar Garg first appeared on the show right before I went on paternity leave, and now we’re back for round two. Before founding Renaissance Philanthropy, Kumar worked in the Obama Office of Science and Technology Policy and spent time at Schmidt Futures.

We discuss…

• How Renaissance catalyzed over $200 million in philanthropic funding in its first year,

• The goals of the organization and how it has responded to Trump’s S&T funding cuts,

• What sets Renaissance apart from traditional philanthropic organizations, and lessons for China-focused research foundations,

• AI applications in education, from tutoring to dyslexia screening,

• Donor psychology, “portfolio regret,” and how to build trust within a philanthropic network.

Listen on Spotify, iTunes, or your favorite podcast app.

The Hedge Fund Model of Giving

Kumar Garg: I like that this is becoming an annual tradition.

Jordan Schneider: Yeah, we've got to set goals this year, and we can hold you to them in 2026.

Can you start off with the 101 of Renaissance philanthropy, and explain how the thesis has played out over the past year?

Kumar Garg: I’m grading myself here, so this is a biased view, but it’s been a very strong year. When we were launching the organization, we were trying to do something different.

Most philanthropic organizations exist in a single model — they work for a single donor. That donor has resources, whether they sit in a foundation, in their DAF, or as personal wealth. The organization works for them, asking how much money they want to give and on what topics, then runs their philanthropic giving.

There’s another class of organizations that are basically the people spending the money — researchers running labs and doing high-quality research. The philanthropic system has mostly operated with givers and takers — folks operating these organizations and folks doing high-quality work.

The idea behind Renaissance Philanthropy was to sit in the middle and style ourselves more like an investment fund — more like what happens in the world of finance. The folks who are the holders of capital, who have the money, mostly don’t spend their time trying to directly deploy that money.

If you work as an LP for a family office, you might have a team of 10, 20, or 30 people, and you’ve got billions of dollars to deploy. What do you do? You go out there and find intermediaries — private equity funds, hedge funds, venture capital funds, or other experts in particular sectors and areas. You give them the money, and they deploy it on your behalf to help you earn a return.

Philanthropy has mostly operated differently. It’s odd, but it’s historically contingent. The investment world moved toward specialization from the ’70s onward, while philanthropy went in the direction of direct giving. You have really large philanthropic organizations, often well-staffed by experts, that do the giving.

The challenge is that there’s a subset of donors who want to build large organizations, and there’s a large set of donors who don’t. The ones who don’t have been sitting on the sidelines. What ends up happening is maybe when they retire, they build an organization, or when they die, they bequest it to a nonprofit or university. That leaves a lot of value on the table.

The idea of Renaissance was, on various science and tech topics, can we do what an investment fund does? We write down a thesis for three years, five years — we want to achieve this goal. We recruit a field leader to run that fund, then treat the donors almost like LPs in a philanthropic fund. We’re not giving them a return back, but they’re putting money to work against that strategy.

A year ago, when I told this story to people — “I’m going to create an organization that does this” — the operative advice was, “Good luck.” You’re going to cover the waterfront across AI, climate, and economic social mobility. You’re going to take on this massive fundraising goal. That seems like a very hard way to operate. You have no natural advantages — you’re not spending one person’s resources. You have to raise the money and deploy it. It seems doubly hard.

What I was interested in was growing the pie — can we use this model to bring new donors in?

A year in, the early grade is strong. We’ve been able to stand up multiple philanthropic funds. We have a fund using AI to accelerate the pace of math research. We have another fund using AI to deliver public benefits better. We recently launched work on climate emergencies — can we solve for runaway climate risks and increase the technology readiness level of various climate technologies?

We have different funds in various areas. Each has this basic structure — they have a thesis they’re driving against, a field leader running it, and we’re recruiting donor money against that strategy.

What I’m hoping for is that this starts to become — not the only way philanthropic giving happens — but a much more credible path. This allows more donors to be active without necessarily having to take on all the operational load themselves.

Jordan Schneider: You’ve launched this in a particularly precarious time for the future of science and research in America. We’ll get to your takes on the policies in a second. But I’m curious from a donor appetite perspective — what has all the tumult in universities and government funding done for those billionaires sitting on the sidelines, giving just 1.2% of their assets annually to philanthropy?

Kumar Garg: That’s a great question. I don’t have one system-level answer — it’s a frequent question I get about how donors are interacting with the environment. They’re interacting the way most people are — there’s an incredible amount of chaos and news every day, leaving many frozen in place.

It’s relative. Government has pulled back on research funding in the short term, causing significant churn. Industry is also holding back as companies figure out what’s happening with tariffs and everything else. Philanthropy, comparatively, is cross-pressured but hasn’t engaged in the same pullback.

There are donors we interact with who are certainly reformulating their strategies. There are others who, as I mentioned, are interested in compelling ideas and looking for those just like anything else. I haven’t seen an overall pullback — just more of a sense of “Is this idea good in itself, even if government didn’t help at all?"

Jordan Schneider: Can you put in order of magnitude the hope of the new model you’re trying to manifest against, I don’t know, NIH budgets being cut by a third?

Kumar Garg: There’s no world in which philanthropy fills the gap. If you step back and ask how the US built its lead — well, the US spends on the order of $200 billion a year on R&D. Once you include basic and applied research across DoD and civilian agencies, that’s an order of magnitude more than philanthropy spends on research.

The place where these new models will get traction is that how you organize scientific organizations has suddenly become much more of a jump ball. It used to be that the academic bundle — being at a top university — had everything stacked on top of itself. You could get really good talent that way — graduate and post-graduate talent, great students. You build your lab there, do cutting-edge work. Usually, the university gives you flexibility to do many things on top of it. If you’re an academic doing well at cutting-edge research, you could do that within the four walls of a university.

Some researchers have left universities and built what are basically academic research labs outside the university. You’ve got the work that Patrick Collison is supporting around the ARC Institute, the Flatiron Institute that Simons supports. You’ve seen the FROs that Convergent Research proposes. For a long time, that’s been a very alternative path — rare to do, often requiring you to figure out what happens to your university affiliation and how it changes your career path.

If you’re a researcher who’s ambitious and wants to do big projects, whether you’re doing them within the four corners of the university or in your own nonprofit research lab and partnering with universities becomes more of an open question — especially in a world where university funding might fluctuate based on political developments.

I don’t know how that will play out over time, but we’re three months into a deeper shift in how institutional financing will happen. That could have big implications generally. On net, if the federal government doesn’t play its important role in funding research, it’s all a net negative. If federal funding returns to a healthy level, researchers will still take this as a wake-up call to think about structuring their research organizations to be more resilient against systemic shocks.

This episode is brought to you by ElevenLabs. I’ve been on the hunt for years for the perfect reader app that puts AI audio at the center of its design. Over the past few months, the ElevenReader app has earned a spot on my iPhone's home screen and now gets about 30 minutes of use every day. I plow through articles using Eleven Reader’s beautiful voices and love having Richard Feynman read me AI news stories — as well as, you know, Matilda every once in a while, too.

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Jordan Schneider: I observed the EAs being very excited about how many lives they save based on the bed nets they bought. Then you net that out against USAID no longer existing and all the human suffering that’s going to come out of that. The correct calculation may have been to spend all your money lobbying Congress to get people to focus on this.

I think both of us are pretty aligned — we’ve done other shows on immigration policy, university funding, and what’s happening to NSF and NIH budgets going forward. But why do Renaissance philanthropy when Kumar could be spending 100% of his time in D.C. banging on doors and trying to make it 5% more likely that we get an extra $10 billion a year for this stuff?

Kumar Garg: That’s a great question. Being policy-adjacent is generally very high ROI. No matter how you run the numbers, policy advocacy — especially on science and tech topics — punches above its weight, regardless of what you’re doing. It’s probably why I spent time in government as a policy staffer. It’s partly why, no matter what I’m doing, I’m constantly interacting with policymakers and making the case. It’s also why, when funders ask to what extent advocating on behalf of the research community should be part of their work, I’m strongly supportive.

The reason we structured Renaissance this way is that I wanted to specifically think about growing the pie of philanthropic funding because I thought no one was doing it. There are organizations working on policy advocacy. Very few organizations were trying to bring new donors into the mix.

We would be failing as an organization if we weren’t constantly thinking about how our work could impact shaping the debate on the future of R&D funding. We try to be in conversations with both Congress and the administration, as well as policymakers up and down the ladder, to say, “Here’s why this work matters, here’s why the future matters.”

Part of the new models we’re funding — whether it’s things like FROs or AI accelerating science — is to make the case for why investment should happen. Many of the ideas I’ve funded over the years, you can see echoes of in the new Heinrich legislation around accelerating science through AI, where they’re talking about ensuring these AI investments can actually accelerate the pace of science using new models.

Philanthropy, when done well, opens the aperture for what funding could do. Hopefully we’re playing that role. One area I’d like the conversation to reach is moving beyond this dialectic between “science is important” and “science needs to be dismantled because it made mistakes.” I’d like us to reach a place where we recognize there are important things we can do to help reform how we do science. We should bring more discipline to trying out new ideas, bringing in new funding methods and new voices, and reflecting on past mistakes — while also remembering that the investment agenda around science is critical for its utility. Hopefully we can be part of that dialogue.

In some ways, you’re pushing on something I think about all the time — I am a policymaker at heart. The deep utility of that shouldn’t be forgotten in my story.

Jordan Schneider: All right, I think the answer I would give to you is this is the federalist model of policymaking almost — as you said, the inventiveness that you guys can come up with from a form factor and discipline perspective when it comes to doing science and technology research is the type that’s weird enough that it’s not happening in government. But also, two, three, four years down the line, once you guys have some really awesome case studies, these are the sorts of things that can then get 10x or 100x in our gorgeous NSF circa 2027 that has been remade to fully align with the Kumar vision of how change gets made.

With that stance of optimism, let’s talk a little more in detail about some of the projects you guys have stood up. Take us on a little tour, Kumar. Where do you want to start?

Kumar Garg: I’ll go through a couple of the funds and projects we’ve launched. Just to give people a taste of how the model works, let’s start with our work in AI. Our operating theory in AI is that we’re living through a period of huge capability overhang. The idea is that the core technology is rapidly developing, but the number of people, projects, and overall work that actually applies these tools toward actual hard problems in society is really small.

I’ll give an example. We have an AI and education fund specifically focused on how AI can accelerate the pace of learning outcomes. If you follow social media and others, there are many people who write and talk about AI in education. It would give you the sense that a lot of people are working on AI in education. But if you actually dig into the space, the number of actual technical experts who have knowledge of both how education works and how AI works is still shockingly small.

We run something called the Learning Engineering Tools competition — an annual competition that invites tool developers to present cutting-edge ideas that use AI to actually advance learning outcomes. We’ve been running this competition for a couple years. I started it even before Renaissance and then brought it into Renaissance. That competition is the only large-scale ed tech competition in the world. It still blows my mind. No one is out there in a systematic way asking for sets of ideas from people who want to build AI for education.

We have another part of our AI education portfolio that specifically thinks about moonshots — what’s a really hard problem in education that AI could solve? We picked middle school math. It’s really important for advancing to future degrees, and students really struggle with it. We said, can you actually emulate the results of high-dosage tutoring, which the number of studies that J-PAL and others have done show can really double the rate of learning for students in math? Can you do it under $1,000 per kid — bring it under what would make it such that you could offer it to every kid?

We have that running as a program. We have seven teams in the program. We have two teams that are actually on track to potentially accomplish this goal.

Jordan Schneider: Which is wild, right?

Kumar Garg: When those teams are working on it and we ask them who they’re collecting lessons from, there’s not a big field they can go out to. When they go out and interview the AI labs — the ones that get written about every day — those AI labs talk about education, but they don’t have in-house education teams that can actually help these teams.

The biggest piece I would always say to people is that at the coal face, there’s tons of room to do work because when you actually start to work on it, you realize that the number of people who are actually working on it is shockingly small.

We’re now starting to explore our next moonshot area — should there be something that basically looks like the intersection of AI and early learning? Can we actually build a universal screener to best guess if a child is off track when it comes to early language development by having them speak into a device? There’s a bunch of interesting work happening in this area, but we don’t actually have a way to diagnose early learning challenges like dyslexia just by having a student speak into a device. It could vastly increase our ability to help them get to a speech pathologist, get back on track, and be reading by third grade, which is critical to future reading and learning.

That’s just one track — AI and education. That’s just one compelling thesis.

Jordan Schneider: Obviously AI is going to matter for education. Hard to find people to argue about that. Talk a little bit about finding the donors and finding the teams. What was the work that you guys had to do to make and launch this work?

Kumar Garg: What’s been interesting is it has been hard work for us to build out the team because the number of technical experts who actually know both things — AI and education — is small. We have slowly built out a team of ML experts who have educational backgrounds, basically. We call it a hub model. We basically have created an engineering hub and we recruit technical experts into it that specifically have this technical background.

I have somebody on my team, Ralph Abboud. He has a machine learning PhD, and he did his thesis on graph theory. He’s not an education expert, but we brought him onto the team. He has been working with a lot of these educational teams that we brought in. What’s interesting is that his ideas on what kind of language models they should be building are really good. It took him some time to level up on the education side, but now he is one of their highest value contributors, even though he sits on our team and he’s contributing there.

There is this transition where you can build up talent that sits across these two areas. But in AI and education we had to mostly build it. It was hard to immediately find directly. Now we have a constellation of these AI and education experts, some of which sit on our direct staff, some of which sit inside these teams that we’re betting on. It’s been great. Now we have a field team that can really go after more problems.

On the donor side, we’ve really lucked out. We found that our core donor for a lot of this work has been the Walton Family Foundation. They have a long history in funding education. What’s been interesting is that they’ve been interested in investing more in what they call their innovation portfolio, but didn’t know how to necessarily bridge that technical divide — if we’re going to do more in this area, who are going to be the technical experts who will actually do it? That had actually kept them more experimental. But their partnership with us has meant that they have become way more ambitious on how much investment they want to make on this technical AI and education lens.

That’s our core thesis — can we be the permission structure for donors to go much bigger on innovation? We’ve seen that in other areas. Slowly their support is causing other donors to come in as well. That’s basically whether you’ve been a long-standing donor but not active on science and tech topics, or you’re an early donor altogether.

Jordan Schneider: What’s the RenPhil management fee?

Kumar Garg: That’s a good question. We build our cost recovery into each fund. Usually the way that works is if we’re operating multiple funds, each fund has money going out the door for actual deployment grants, but then we’re building in our cost for the actual staff operating the funds, whatever services and technical support services we’re providing, the work we’re doing to partner with various funders, as well as our overall studio support. It varies fund to fund, but donors have found it — compared to having to try to do this themselves — much more actionable. For us, we want to build a thriving organization. We don’t want to cut corners. We want to build an organization that can both operate those funds and also be looking for the next ones.

Jordan Schneider: Does anyone complain about that?

Kumar Garg: The way it comes up is there’s a type of donor who actually has the answer in their mind. They’re thinking, “I think this needs to happen.” Really, what they’re looking for is an operating partner to just do that — “I want a conference, I want a workshop, I want to fund these three organizations.” Our model is we’re the product. You’re actually hiring us to go build out the strategy, recruit the team, deploy. If you actually have the answer in your head, we often tell them we’re way too fussy for that model. You should just — there are much simpler ways you can operate. That’s where the delta comes in. If you already have the answer in your head and you’re just looking for a partner to execute for you, we’re probably not the right fit.

Jordan Schneider: Yeah, you said this on another show. You were like, “We are for donors to take off the cognitive load.” The idea of being: yes, if I have $10 billion, maybe I’ll allocate $1 billion investing in stuff I know and think I have some subject matter expertise in, but I still have to put the other $9 billion somewhere — probably not cash. Yes, I am comfortable paying a hedge fund or financial advisor a management fee to do that.

Kumar Garg: A big part of it is opt-in. People don’t know what journey they’re on, but what they worry about is: am I going to feel stuck? A lot of folks end up not getting active philanthropically because the decision feels weighted by getting stuck. “Okay, if I hire somebody, and then six months from now, I decide maybe I want to change direction. Now I’m going to have to let someone go.” People hate that.

Or, “I met a researcher. I liked their research. I gave them one grant. But now they’ve reached out and said, ‘There’s so much happening in the world — I’ve lost funding from the government. Can you double the grant?’ I was just giving them a grant because I met them and I thought they were great. But now they’ve sent me a note that they might have to let go of postdoc students. Now I’m in this uncomfortable situation. If I say no, I feel I’m hurting them. If I say yes…”

People have all these experiences where they feel uncomfortable with the relationship they have around their resourcing. Rather than causing them to work through it, they actually hold back. One of the things we say to them is that our model is one where we’re the ones making the decisions. We’re going out there, finding researchers, finding projects, developing strategies. You can be as involved as you want. You want to be meeting the researchers? That’s great. You want to be learning from the strategy so you can do direct giving down the road? That’s great. But if you also take six months off and decide, “That was great, I learned for a few months, now I’m off doing something else,” — nothing will stop. We’re a fully operational organization that will execute on everything we said we were going to do, whether you’re involved or not.

It just takes the pressure off. You can opt in if you want to learn and be involved, but you can also choose not to. That actually frees them up to want to learn without the “Am I about to get stuck?” That sounds very psychological, but people forget how hard it is to get going on things — “I’m going to start to work out more. I’m going to start to do this.” Starting is hard. We want to make starting easy by saying you can provide a lot of value into the system without necessarily having to own all of that execution.

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Jordan Schneider: There are a lot of pieces of people’s jobs that seem like more and more AI can chip away at or enable or launch or whatever. It’s interesting because some of the things that you guys are doing — you have these seven playbooks, ways you can tackle problems — I would love to upload seven of those to ChatGPT and say, “Here’s my problem in the world,” and the AI can help me pick through which one. But talking someone who’s really rich, who’s feeling uncomfortable about giving money, into starting to donate philanthropically in a serious way for the first time seems like one of the more human things where there’s really going to need to be the friendly Kumar Garg, who now has a nice microphone he can do Zoom calls with to — what did Derek Thompson say? — whisper the dulcet tones of comfort and competence in their ear in order to get them on this path. I don’t know, it just seems like a very human thing that you’re engaging in on the donor engagement side. I’m curious for any reflections you have on that.

Kumar Garg: We are very curious about how much of our own internal processes we can automate. Why not? We sit next to AI, we should be thinking, we should be dogfooding. The place where we’ve seen it already provide some value is just what you would consider baseline automations. There’s a lot of grantee reporting that you should be able to do automations on. We’re definitely interested in: hey, we have a hunch around a thesis in this area. Can you do a research report and tell me what’s the relevant stuff to know? Scoping. We’ve even used it for, “Hey, we might do an RFP on this topic. Who are some researchers who should apply?” Sometimes we found some interesting suggestions for researchers that we should affirmatively reach out to.

I will say that we’re still far away from it actually helping on anything that we would consider high stakes. As you’re saying, a huge amount of what we’re doing is making something that feels like a trust fall. Hey, this is an important decision, but one where people who take their job very seriously and put their own personal legitimacy behind the work is an important part of it. When we screw up, it’s on us. We stand behind all of the work. People appreciate that these are serious people who stand behind the work they’re putting before them. They’re not some faceless intermediary. I don’t think maybe that will change, but that’s an important part. Even on the information you should know about various people and stuff, these current AI models are not that great.

The place where I — we have this intuition that there should be parts of being a program leader that you should be able to have an AI assistant for. Right? You take more and more of the task of being a program leader or fund leader and be able to say, “Okay, I want to do a workshop on this topic. Generate me an agenda for how you would run the day.” It generates based on — it takes a bunch of your past workshop flows and generates a sample workshop design. How much of that can we create so that we really could get to a point where a program leader or fund leader is basically able to operate without that much additional support? Obviously we need to create some cross-cutting support that I’m interested in. But the chance that we’re going to get to an AI advisor — we’ll have to wait.

Jordan Schneider: The trust fall works in multiple directions. You need researchers to give up their PhD programs or leave their current positions to spend half their time with you, while simultaneously needing donors to provide funding. Having a recognizable face with a proven track record and skin in the game on the other side of that equation is something that won’t disappear anytime soon.

Kumar Garg: One thing we debate internally is that much of my workflow relies on tacit knowledge. When I’m talking to somebody about their work, twenty minutes into the conversation, I’ll say, “Tell me more about that. Why is the field stuck on this point?” They start describing it, and I realize that if there were a canonical dataset with specific dimensionality, it might solve the problem. When I ask why that doesn’t exist, they explain it’s locked up somewhere.

Part of me constantly strives to figure out how we can make this process more explicit. When we recruit somebody new to the team, they ask if they can sit in on my calls and watch me work through problems with researchers. There’s something that feels wrong about just saying, “You develop this intuitive feeling for opportunities — just pull on that thread.” The more we can transition from tacit to explicit knowledge, the better. Right now, we operate on an apprenticeship model where people learn by doing and being embedded in these structures, but I don’t think that has to be the endpoint.

Jordan Schneider: Much of what you do involves human matching — putting people in touch with each other. While you could potentially feed all your past calls into an AI system, there’s an emotional and personality matching component that you’re handling. That remains very much a human process that current models aren’t quite ready for yet.

Kumar Garg: The matching capability changes over time, but I think what people really value when I connect them is that I took time out of my day to think the two of them should know each other. That’s the actual signaling value — that my time is precious.

Jordan Schneider: Slight tangent, but if people want to establish trust and rapport, the first thing they should do is spend $150 on a microphone for their Zoom calls. That’s my recommendation for everyone. When I do my calls, I sound the same as I do on my podcast, and people respond positively. You feel like an embodied person rather than a compressed, distant voice through AirPods. It’s advice for anyone who wants to make connections and raise money from billionaires on Zoom.

Kumar Garg: I’ll echo that point, though I haven’t practiced it myself. There’s an old political adage about microphone technology. If you look back at politicians historically, there was a time when microphones couldn’t pick up subtle intonations well — speakers were just projecting loud sound. Once microphones could capture subtle intonations, politicians who excelled at that style of speaking began to dominate.

People point to President Clinton as an example — he was exceptionally skilled at subtle microphone use. I remember reading a paper arguing that this was possible because the technology had improved to support that communication style. Politicians offer good lessons here because ultimately, communication is central to building trust with the electorate. [Here are papers that explore this]

Jordan Schneider: Absolutely. If you listen to old clips of Warren Harding or Teddy Roosevelt speaking, they’re basically screaming into microphones — which was necessary at the time. Teddy Roosevelt was exceptionally good at that style of projection. You needed to be very loud to stand on a soapbox and reach people twenty rows back. Now we have the dulcet tones that modern microphones enable.

Here’s another fun fact, Kumar — the microphone I’m using has been manufactured for sixty years. It’s remarkable that microphone technology for voice pickup has essentially reached its peak — we’ve basically maxed out the capability.

Kumar Garg: I should try to find that paper I mentioned. I wonder if it’s about mobile situations — being in some random union hall where you need to set up a handheld mic in front of a politician. Perhaps that’s why microphone technology improvements became so important. That’s an interesting angle.

Jordan Schneider: I’m curious about that. Alright, shifting topics — Yascha Mounk recently wrote on Substack about attending gatherings, conferences, and dinners where leaders of America’s biggest foundations have been strategizing how to defend democracy. Few were as openly devoted to extreme forms of identitarian ideology as they might have been a few years ago, but the reigning worldview at the top of the philanthropic world assumes little has changed since summer 2020.

The general consensus holds that voters turned to Trump because American democracy failed to deliver for the “historically marginalized,” and the solution supposedly revolves around “mobilizing underrepresented communities.” The most urgent imperative is to “fight for equity” and “listen to the global majority.” I find this perspective fascinating. Kumar, as someone who’s a new entrant to this world, how do you interpret this?

Kumar Garg: Several different dynamics are happening simultaneously. Some philanthropic responses resemble dinner table conversations — people sharing hot takes about why the election unfolded as it did and offering their views on America or the American people. Much of this sounds as random as hosting a dinner party where guests share their political opinions.

There’s also a genuine state of confusion about what’s happening. The first hundred days of the Trump administration have been exceptionally active across a range of unexpected areas. Many people expected it to feel similar to the previous Trump presidency, so they examined their portfolio of issues and anticipated certain outcomes — but that’s not what materialized.

Regarding how much people are actually rethinking their approaches, that’s a valid question. The most immediate reconsideration I’m seeing centers on identifying what we’re missing. This is particularly evident in the science community, which is confronting devastating across-the-board cuts. Researchers are losing funding, university funding is being paused, and graduate students working on topics relevant to competitiveness are having visas revoked.

The community is asking, “We don’t remember this being a major campaign debate topic, so how exactly did we become a political football?” There’s extensive questioning about what we’re missing — whether there was a conversation we weren’t invited to where we were being discussed, and what we’re failing to understand.

While donors with certain political orientations likely won’t change their fundamental positions, the confusion centers less on American domestic politics and more on why certain issues became contentious. Foreign aid is a good example. The extent to which US foreign aid posture and system effectiveness became campaign issues wasn’t apparent during the election cycle. People are asking whether we missed a major debate that suggested the United States should dismantle its leadership on these topics overnight. What policy debate did we miss? That’s where much of the confusion originates — donors being puzzled about the sources of these developments.

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Jordan Schneider: There’s an interesting dichotomy between foundations with living leadership and those with deceased benefactors. Gates recently indicated he would spend down his wealth faster than previously planned, presumably responding to recent events. When foundations have active leadership that engages with current events, they can be more responsive.

However, when you have flagship philanthropists who died seventy-five years ago and organizations that have built programs around worldviews that are no longer relevant or don’t meet current demands, pivoting becomes much more difficult. You encounter institutional blockers, boards, and established structures, whereas a living person with decision-making authority can simply redirect resources.

Kumar Garg: That’s definitely part of it. The piece I’d add, which connects to our Renaissance model, is that people underestimate how much philanthropic organizations become tied to their existing programs. This isn’t necessarily negative, but consider the process: you spend two and a half years scoping a program, conducting field research on topics, then executing a national search for program leadership. You recruit and convince someone to relocate for the position, provide coaching for test grants, and they’re six to twelve months into the grant cycle.

If you then decide the world has changed and want to cut the program — after issuing press releases announcing this as a major new strategic direction — it appears chaotic. People develop what I call “portfolio regret.” If they could start fresh today, they’d create different programs than what currently exists.

One argument we make to donors is structuring themselves more like limited partners, deploying money into funds where all capital remains fresh and available. You avoid the incumbency problem where team members question every pivot attempt because they have specific responsibilities you hired them to fulfill.

Flexibility requires both mindset and structure. Donors sometimes create substantial built-in costs and barriers to pivoting when they could maintain lightweight, flexible operations if they chose to do so.

Jordan Schneider: That’s fascinating because you’d think giving money away would be straightforward — you should be able to distribute funds however you want. But the emotional sunk cost around philanthropy wasn’t something I had necessarily considered.

Kumar Garg: This creates a situation where people spend enormous amounts of time operating like a duck swimming on water — their feet are moving rapidly beneath the surface while they try to keep the strategy looking consistent above water, all while changing the actual content underneath to pivot to current circumstances. This leads to significant conceptual confusion because you claim to have always had this program, but underneath, the program is completely different because the situation changed.

Part of why I favor the philanthropic fund model is transparency — what’s on the cereal box is what you get. It’s a three-year fund with specific objectives that will begin and end. Maybe it’s not perfectly timely, and that’s fine, but your new program can be timely. The alternative — constantly maintaining broad programs that you’re perpetually reworking underneath — makes evaluation nearly impossible. If I ask whether a program has been successful, people respond that the program has been changing constantly. This makes it extremely difficult to evaluate it as a focused initiative that ran for a specific period with defined goals. Did we achieve those goals? People simply don’t engage in these basic evaluations.

For example, I was speaking with a donor and pointed out that in the investment world, people prominently display their successes — putting “first check into [major company]” in their Twitter bios to demonstrate their betting acumen. I asked, “Who are the ten best program officers in America? Who on the philanthropic side has been the most effective check writer?” They responded, “How would we even know that?” Even with qualitative measures, wouldn’t you want to identify the best check writers?

A fund model, even for philanthropic goals, enables more honest assessment. You can say that fund paid out successfully, that one was moderately effective, and another one failed completely. The person who led that fund can then take that track record to their next position as a legitimate career advancement. We deny people this opportunity when we maintain the fiction that we’ve always had these programs run by different people with slightly different strategies. This obscures rather than clarifies outcomes. We could simply be honest: we executed that fund, now we’re doing something new with a clear beginning and end.

Improving China Research + Why Bother?

Jordan Schneider: It’s remarkable. I’ve spent considerable time on foundation websites researching whether organizations like the Ford Foundation might fund ChinaTalk. They have mission statements about “democratizing equity,” which is admirable — I agree we should advance democracy and create more opportunities for people. However, the problem arises when you’re only a passive recipient of pitches. You’re essentially letting grantees define what success means, and the counterfactual becomes very difficult to assess. The organizations you’re funding would probably exist whether you give them $100,000, $500,000, or nothing at all.

The alternative approach would be starting with specific objectives — “We are trying to achieve X by Y timeline,” then working backward from that goal orientation to identify the people and organizations who can take your money and provide the highest probability of achieving that outcome. This approach is far more strategic, and my frustration isn’t about the politics of how they set their goals — it’s that they need to engage more seriously in the process.

Kumar Garg: Let’s work through this together. Imagine you and I were designing a fund model versus a program model for increasing collective intelligence on US-China relations.

There’s a vague way we could structure this — “This is the US-China program. It will have three tracks — funding scholars studying China, engaging policymakers about those insights, and warehousing data and research publications on these topics.” This resembles how most programs operate: they establish a broad framework with several tracks, then people apply under those categories. But if I asked what constitutes winning or how we’d know this program succeeded, you’d probably say, “Well, people applied and we distributed grants."

You could execute the same concept with much sharper focus by asking, “What would success look like in three years?"

Jordan Schneider: Exactly. I want ten books written that are so thoughtful and essential to the future of US-China relations and American policy that Ezra Klein would be compelled to feature these authors as guests because the thinking these grants produced is indispensable. Then we work backward from that goal to determine the budget.

We’d estimate the costs — ten books, assuming a one-in-five success rate for people with strong proposals to execute effectively, calculate the pipeline requirements, and arrive at a number that gives us a 75% confidence interval for producing those ten books by 2029.

Kumar Garg: Exactly. That approach feels like a sound tax strategy built on what resembles a very tight OKR, which you may completely fail to achieve. You might be wrong, but it’s precise. Then you build your strategy around that goal.

You find someone to execute it — let’s call it the Jordan Fund. If you succeed, people ask, “Jordan, how did you pull that off? You wrote down this ambitious goal, built a strategy around it, and executed successfully. You’re clearly skilled at this.” When you pursue your next initiative, you can say, “I ran this fund called the Jordan Fund. We set this audacious goal to produce ten bestsellers on US-China relations, and we achieved it."

This feels much more tangible as an actionable strategy — something that field leaders can point to as real-world impact, even if it fails. Let’s say you only achieve partial success — you still have concrete lessons. Compare that to “the US-China program makes some awards and does some things.” How do I assess whether that’s working?

Jordan Schneider: It’s remarkable because the market is so powerful — you can’t get away with this approach when running and scaling a business, especially when taking other people’s capital and trying to generate positive returns for them.

What’s curious, Kumar, is that very capitalist people become surprisingly touchy-feely when it comes to philanthropy. There’s an emotional layer where they think, “This is giving, so we shouldn’t apply business mindsets and OKRs.” It feels somehow dirty to them.

Kumar Garg: Here’s what’s important — we need to distinguish between current donors and potential donors. People focus extensively on today’s active donors, but if you examine the statistics on potential giving, current donors might represent only 1-2% of the actual addressable universe.

The question becomes, would we attract an entirely new class of donors if we brought this level of rigor, precision, and targeted approach to philanthropy? This would feel much more familiar to their professional experience.

Why don’t existing donors demand this rigor? I believe there’s significant pent-up interest in this approach. People oscillate between thinking, “Since this isn’t about making money, we’ll substitute with having a really complicated theory of action — that’s where we’ll apply our intellectual capacity.” I often say that just because something has numerous boxes and slides doesn’t substitute for having a clear attack vector.

Jordan Schneider: Exactly — rigorous thinking. The median nonprofit worker is about five times more likely to be socialist than the average person, so perhaps people more attracted to touchy-feely logic are simply concentrated in current organizations.

Kumar Garg: Sometimes the nonprofit and philanthropy sectors spend too much time engaging in collective mission statements, as if shared purpose alone is sufficient. But we actually have distinct roles to play, including making high-quality decisions about where to deploy finite resources. Because money is limited, you must make decisions strategically and place informed bets.

This may feel reductive, but it’s actually the responsibility inherent in this work. You must be a responsible steward because high-quality decisions produce more good. People sometimes struggle with that reality.

Jordan Schneider: Without high-quality decisions, you end up with USAID getting canceled. That’s our current reality. Organizations that weren’t evidence-based and couldn’t effectively justify their impact had some good projects and some poor ones. They faced criticism from small but vocal movements — organizations like Unlock Aid, whose founder we featured a few years ago and will have on again — arguing for more rigor because there was substantial waste and inefficiency.

If you let these issues fester too long, consequences follow. I don’t want to say universities, the NIH, or the NSF “had it coming,” but one of the best defenses you can have is a tight, well-justified organization that can stand up for itself.

Kumar Garg: I don’t want to engage in victim blaming, and I don’t want to excuse what I consider sometimes bad-faith behavior. However, your point about systemic advantages is valid — caring deeply about systemic impact and bringing that rigor and constant evaluation is useful for the work itself, but also valuable when those political fights emerge. You can say, “Look, we’re building something substantial."

In some of these cases, who knows what impact rigorous evaluation might have had. We’re living through unusual times, but I believe we’re gaining traction because there’s significant pent-up demand for this approach.

Jordan Schneider: Good. That makes me feel somewhat better, I suppose.

Kumar Garg: What should donors know about China? That’s my question for you.

Jordan Schneider: The original impetus for ChinaTalk was thinking about long-term national strategic competition and competitiveness from an industrial systems and technology perspective — identifying things people could do to nudge outcomes in liberal democracies’ favor. During the Biden era, I observed errors that legislation and executive action could fix with modest improvements — 5% here, 10% there. A sophisticated understanding of what’s happening in China could meaningfully help squeeze that extra 10% out of various decisions.

However, the policy changes we’ve witnessed over recent months regarding long-term strategic competition — how the US relates to allies, approaches to global nuclearization, science and technology funding, and immigration — are much more fundamental. Getting to a better place doesn’t require understanding what made BYD successful, how SMIC is developing its chips, or even China’s new AI policy. These are much more basic issues.

The thesis I operated under during the Biden era was that deeper, more considered understanding of China would lead to smarter policies. That’s now become a sideshow compared to more fundamental questions. If we accept the base case that science is important and immigrants are crucial for better science, then we should pursue those priorities directly. I would choose that approach ten times out of ten.

Returning to the order-of-magnitude questions I asked at the beginning, I would choose a NATO that functions as a genuine alliance ten times out of ten over determining the right tariff level for Chinese electric vehicles or batteries. That’s why I lean toward “be nice to allies” bumper stickers and NSF funding advocacy rather than tightly nuanced “we need to better understand China” approaches when considering ChinaTalk’s decadal competition mission.

Kumar Garg: One thing I’ve been considering, though I don’t have the answer yet, is what new institutions we need. Much of what I care about regarding how science operates in this country has been overturned. The idea that we’ll navigate this period with identical institutions seems unlikely — whether it’s who makes the case for science, who serves as science messengers, or how we conduct science itself.

This raises questions not just about policies, but about institutions themselves. Obviously Renaissance is part of that response, but I have broader concerns. We’ll probably need new institutions because the players on the field will have to change. Systemic change of this magnitude requires that everything else engage in significant adaptive change for us to succeed. That seems unlikely with current structures.

That’s a major meta-question I’ve been asking the team, “We won’t be able to handle everything directly, but what institutions would restore us to better footing? Do we have them? Do we need to create them?”

Jordan Schneider: I’m starting to focus my energy differently because I’m uncertain whether additional ChinaTalk podcasts about the importance of allies will accomplish much. However, one constant you can expect over the next four years is AI development and rapid technological change.

Regardless of controversial Trump policies, the Defense Department will persist, and America will still need to protect itself. America engages in conflicts approximately every three years, so that pattern will likely continue. Perhaps this is just me entering a kind of intellectual monk mode after dynastic change, but I’ve been reading extensive military history and examining periods of rapid technological change — specifically, what it means to deploy these tools more effectively than adversaries.

This doesn’t directly answer your question, but I’m pursuing intellectual journeys rather than policy ones.

Kumar Garg: Here’s what I’d say, which connects to the role you and ChinaTalk are playing. One thing I mentioned to Jordan before we started is that frequently when people reach out to me, they reference hearing a great ChinaTalk episode. You may not have set out to do this, but you’re playing a valuable role in shaping how other people — especially technical professionals — think about problems worth solving and their mental frameworks for our current age.

People are seeking understanding and meaning in this moment. The question isn’t about marginal additional podcasts, but whether you’re providing people with new vectors for their lives and careers. When we first met, you described yourself as a nerd passionate about these topics but uncertain where to channel that energy. You’ve created something quite distinctive.

We might be living in an era of unusually shaped careers, and we need to give people more space for that kind of professional evolution.

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Jordan Schneider: That’s fair. Some of this material feels obvious to me but may not be obvious to people who don’t live and breathe these topics daily. It’s strange because I don’t feel like I’m part of some resistance movement — I’m just a guy with opinions on various issues. Some days I wake up feeling helpless, others I feel genuinely empowered. This isn’t a direct response to your question, but that’s my reality.

Kumar Garg: You’re reasoning in public. You’re expanding people’s understanding of how to think through these complex issues and broadening their sense of who engages in this work. What I consistently observe is that people operate in highly siloed environments. They’ll mention their sources, and I immediately know exactly who they’re reading or listening to.

If you can expand their perspective while providing actionable next steps, that’s valuable. Part of my goal is always emphasizing that there are numerous hard, interesting problems to solve across every arena. No arena is the wrong one. People who dismiss politics are missing a crucial point — we’re all living within political systems whether we acknowledge it or not. Don’t dismiss any arena; simply understand that there are multiple dimensions to engage with. There are challenging problems to solve, and nobody benefits if you just remain a passive observer in the cheap seats.

Jordan Schneider: Perhaps the way I justify all my World War I reading is that no one else is doing this specific work. I’m bringing historical insights to current issues as someone who also reads contemporary news and has the freedom to spend ten hours weekly on intellectual journeys exploring topics I consider relevant to today. That seems like a natural conclusion.

Kumar Garg: We’ll do an update in a year. Hopefully, the republic endures.

Jordan Schneider: Kumar, you need to set ambitious goals for yourself — accomplish so much that I have to bring you back in six months.

Kumar Garg: Absolutely. One of our primary goals is becoming more international. We have a partnership with the British government to develop their R&D ecosystem, and we want to expand that model to additional countries. We’re building an organization that continues to internationalize because science and technology are inherently global.

I’m hoping our fund model will attract new donors who have never engaged in philanthropy before. Beyond discussing our approach, I want the actual work to manifest tangible results in the world.

Jordan Schneider: Contact info@renphil.org if you’re wealthy, have innovative ideas, or simply have a technology-related challenge you need help addressing.

Kumar Garg: I’m also available on LinkedIn — please reach out. We consider ourselves fundamentally a talent network, so I’m always eager to connect with people who have compelling ideas.

Jordan Schneider: We should do a little parent corner. We’ll keep this as part of the annual check-in. We talked about slime last year.

Kumar Garg: We did. Here’s something we discussed before we started recording — I asked you about sleep training, and you mentioned being hesitant to push sleep training advice on others. I’m strongly convinced that sleep training is a gift you give your children. We had twins and committed to sleep training. They’re eleven years old now and remain excellent sleepers today. We attribute this directly to that early sleep training.

For any parent listening who’s on the fence and wants random advice from someone they’re hearing — I can’t offer this to everyone, but I usually tell people I know that I’m always happy to be anyone’s texting buddy, providing extra support to get through those terrible first few days when it feels like you’ve made a horrible mistake. On the other end, you have children who can sleep well, which benefits everyone.

Jordan Schneider: I’m with you. I outsourced this decision to my mother — maybe one of the best decisions of my life.

What’s a cute development we’ve observed recently? I bought a ukulele two years ago, thinking it would be nice to play with my kid. What’s been charming is that my daughter is nine months old now, and there was a period where her manual dexterity only allowed her to grab the strings and pull them. But one day she figured out plucking, and now she’s actually plucking the strings. It’s such a cool activation moment for her — realizing “I make the sound now” instead of just dragging this thing around the room.

Kumar Garg: The period from nine months to eighteen months is truly remarkable. You’re approaching walking and first words, then vocabulary takes off exponentially. It’s incredible developmental progress, so I’m very excited for you.

Jordan Schneider: Perfect. Let’s wrap it up there. Kumar, thank you so much for being part of ChinaTalk.

Kumar Garg: Thank you for everything you’re doing. I’m excited to have participated and look forward to future conversations.

Today we’re running an interview of Huawei founder Ren Zhengfei that made it to the front page of yesterday’s People’s Daily, the premier Party outlet.

What struck out to me in the Q&A was just how hard he hit on the importance of basic research to long term competitiveness. “Without basic research,” Ren says, “there are no breakthroughs, and we’ll never catch up with the U.S.” The People’s Daily giving Ren Zhengfei the airtime to promote this view underscores just how central China’s leadership today sees this work.

We’ve covered the US side of how the Trump administration may be killing our golden goose in this regard with its treatment of the NSF, NIH, university ecosystem and immigration system in recent episodes on America’s R&D Reckoning, our interview with Josh Wolfe of Lux, and a recent op-ed on the war on S&T talent.

This translation also serves as a reminder to subscribe to ’s excellent and meditative daily People’s Daily recaps in his substack Tracking People’s Daily.

"The more open a country is, the more it drives us to progress" — A Dialogue with Ren Zhengfei

By reporters Hu Jian and Chen Jiaxing People's Daily (June 10, 2025, Page 1)

Recently, at Huawei headquarters in Shenzhen, focusing on some hot topics of public concern, a group of People's Daily reporters had an in-person interview with Huawei CEO Ren Zhengfei.

Q: Facing external blockades and pressure, encountering many difficulties, what are your thoughts?

A: I haven't thought about it—thinking about it is useless. Don't think about difficulties—just get on and do it [干就完了] and move forward step by step.

Q: Ascend chips have been "warned on" about usage risks [BIS . What impact does this have on Huawei?

[BIS in mid-May warned firms anywhere in the world that using Huawei Ascends, which were almost certainly fabbed by TSMC under false pretenses, would be considered a violation of export controls. The Information recently reported that “The fallout [from this BIS action] was swift: one Chinese data center firm promptly halted even the small order of Huawei chips it had planned to make, while its legal team scrambled to understand how it could comply with the regulations, according to one person with direct knowledge of the change. Meanwhile, executives at ByteDance and Tencent, both of which have significant business footprints outside China, worry adopting Huawei chips would invite scrutiny from the U.S. government, according to people familiar with their thinking.”]

A: There are many chip companies in China, and many of them are doing quite well—Huawei is just one of them. The US has exaggerated Huawei's achievements; Huawei isn't that formidable yet. We need to work hard to live up to their assessment. Our single chips are still one generation behind the US.

[The incentives are interesting here. On the one hand you have Jensen Huang going around saying Huawei is an enormously powerful competitor who dropped Nvidia’s China market share from 95% to 50%—even though, as the Information very generously put it, “Market share data to confirm Huang’s statement is hard to find.” Jensen, of course, wants the US government to lift export controls not on semiconductor manufacturing equipment but his ability to sell AI chips and racks into China.

The Chinese government and Huawei have every incentive to sandbag Huawei and SMIC’s capacity to compete. They’ve deeply internalized the backlash from Made in China 2025 and want the Trump administration to think that easing export controls on inputs to semiconductors and not investing in the state capacity to enforce the current ones is less of a give than it appears.]

We use mathematics to compensate for physics, non-Moore's to compensate for Moore's [用数学补物理、非摩尔补摩尔], and cluster computing to compensate for single chips. In terms of results, we can still achieve practical applications.

[For more color here, see SemiAnalysis’ coverage of the CloudMatrix 384, Huawei’s answer to Nvidia’s rack solutions]

Q: If there are difficulties, what are the main ones?

A: Difficulties are just difficulties—when hasn’t humanity faced them? Wasn't slash-and-burn agriculture difficult? Wasn't the Stone Age difficult? When humans used stone tools, how could they have imagined high-speed rail? China has opportunities in mid-to-low-end chips, with dozens or hundreds of chip companies all working very hard. Especially in compound semiconductors, the opportunities are even greater. For silicon-based chips, we use mathematics to compensate for physics, non-Moore's to compensate for Moore's, utilizing cluster computing principles to meet our current needs. Software cannot be strangled [卡不住脖子]—it's mathematical graphical symbols, code, and advanced operators and algorithms stacked together, with no barriers blocking it. The real bottlenecks lie in education and talent pipelines. China will eventually have hundreds or thousands of operating systems supporting progress in Chinese industry, agriculture, healthcare, and more.

Q: Huawei is getting a lot of praise and public recognition these days.

A: Praise brings pressure. A bit of scolding keeps us clear‑headed. We make products; once people use them they will criticize—that’s normal. We allow criticism. As long as people tell the truth—even if it’s negative—we welcome it. Praise or blame shouldn’t matter; what matters is whether we can do our job well. If we do, there’s no problem.

Q: From your attitude toward difficulties and criticism, we sense you have a strong inner core—not caring whether it's praise or criticism, but firmly doing your own work well. This should be an important reason why Huawei has come this far.

A: There's still too much praise for us. People should pay more attention to understanding those engaged in basic research. They are highbrow and solitary [曲高和寡—literally ‘difficult songs find few singers’], ordinary people don't understand them, and it takes decades or centuries to see their contributions. Groundless accusations against them are detrimental to the country's long-term development. We need to understand and support those doing theoretical work. We need to understand their broad-mindedness—their great anonymity is our country's hope. Don't elevate one while suppressing another; those engaged in theoretical research are the hope of our nation's future.

"Basic research scientists are lonely—we must have strategic patience and understand them"

Q: How do you view basic research?

A: When our country possesses certain economic strength, we should emphasize theory, especially basic research. Basic research doesn't just take 5-10 years—it generally takes 10, 20 years or longer. Without basic research, you plant no roots. And without roots, even trees with lush leaves fall at the first wind. Buying foreign products is expensive because their prices include their investment in basic research. So whether China engages in basic research or not, we still have to pay—the question is whether we choose to pay our own people to do this basic research.

Q: Regarding basic research, people might not understand the point of it.

A: Scientific breakthroughs—there are inherently few people in the world who understand them, so those who don't understand shouldn't evaluate them. Einstein's discovery that light bends was only proven a hundred years later. In Guizhou, there's an agricultural scientist named Luo Dengyi. In the 1940s, when analyzing the nutritional components of fruits and vegetables, he discovered a wild fruit called cili [刺梨] with very high vitamin content. China was still in the Anti-Japanese War period, education levels were low, and few understood. Later he wrote a paper saying cili was the "King of Vitamin C." After nearly a century, Guizhou has made it into a natural vitamin-rich cili beverage, a luxury item among vitamin drinks at nearly 100 yuan per bottle, highly sought after. The cili industry has become a channel for farmers to escape poverty and become prosperous. Only then did people truly recognize Luo Dengyi, who worked at a broken table during the flames of the anti-Japanese war.

[A deep cut by Ren Zhengfei here but this does look incredibly tasty!]

Q: Many results that look irrelevant at first yet turn out to be hugely useful.

A: Theoretical scientists are lonely; we must have strategic patience and empathize with them. Tu Youyou’s discovery of artemisinin is one case; So was Huang Danian, who embodied "exploring innovation and serving the country with utmost sincerity." The symbols, formulas, and thinking in their minds can only be communicated with by a few people in the world. We must respect theoretical scientists because we don't understand their culture. Society must be tolerant, and the nation must be supportive.

Q: Basic research takes a long time, but companies must deliver returns.

A: We spend roughly 180RMB billion a year on R&D; about 60 billion goes to basic research with no KPIs, while around 120 billion is product‑oriented and is assessed. Without basic research, there are no breakthroughs, and we’ll never catch up with the U.S. [没有理论就没有突破，我们就赶不上美国].

Q: That’s true long‑termism. We heard Huawei even has a “Huang Danian Tea‑Thinking Room.”

A: Professor Huang was a great scientist. China noticed him during the Gulf War: the U.S. used a pod under helicopters to detect Saddam’s buried weapons and destroy them instantly—that pod had been developed by Huang at a UK university. He later resigned from his UK university position and taught at Jilin University. He spent his own money to get a 40 m² room, offering free coffee so students could “absorb cosmic energy over a cup of coffee.”

[Honestly this looks pretty lame, Huawei didn’t do the guy justice with this underwhelming study hall]

We have his family’s authorization to use his name for a non‑profit online platform—the Huang Danian Tea‑Thinking Room—where anyone can freely access global scientific information.

We also keep the “mouth of the funnel” wide open for basic research, partnering with universities. These are strategic investments with no performance metrics. Internally, we accept that we don’t know when theoretical work will bear fruit and impose no demands on the scientists.

“One purpose of socialism is to advance society”

Q: [A cringe leading question here…] Economist Richard Wolff and others argue that the U.S. lacks a high‑speed rail system because capitalism demands profit, while China’s socialist approach values social benefit: high‑speed rail, heavy‑haul lines, advanced power grids, expressways, rural cement roads, irrigation works, power plants… none make money directly, yet they underpin modernization. Competitive goods, meanwhile, are market‑regulated. What’s your view?

A: Why is it that only socialism tackles unprofitable tasks? One goal of socialism is precisely to develop society. China’s socialist market‑economy model is a magnificent undertaking. In infrastructure we had to follow this path—otherwise high‑speed rail, expressways, dams and so on would never have been built.

Q: What’s your outlook on AI?

A: AI might be humanity’s last technological revolution—barring perhaps fusion power. It will take decades or centuries to unfold. No need to worry; China has many advantages. [This line made leadlines in non-Party media]

Q: What advantages?

A: Hundreds of millions of young people—they’re the nation’s future. The General Secretary has said a nation’s strength rests on cultural flourishing. Technically, AI hinges on ample electricity and advanced networks. China’s power generation and grids are excellent; its communications network is the world’s most developed. The “Eastern Data, Western Computing” vision can become reality. [For more, see ChinaTalk’s past coverage of EDWC.]

Q: Anything else?

A: Chip worries are unnecessary: with stacking and clustering, our computing outcomes match the state of the art. As for software, open‑source ecosystems numbering in the thousands will meet society’s needs. [Wait, earlier in this interview I thought we were stressed about how behind Chinese chips were…?]

Q: How do you see China’s future?

A: After leaving our company, Tom Friedman bought a second‑class high‑speed‑rail ticket on his own to experience China. He later wrote, “I’ve seen the future, and it’s not in America.” [See ChinaTalk’s interview with Ezra Klein where I discuss this Tom Friedman piece with him. I, for one, would not take cues on analyzing China from Tom, who said in his Ezra interview that “Whether I’m writing about China from Washington, or whether I’m writing about China from China, I’m always just writing about America. My goal is to use China as my permanent Sputnik.”]

Q: Friedman said in that piece: “What makes China’s manufacturing juggernaut so powerful today is not that it just makes things cheaper; it makes them cheaper, faster, better, smarter and increasingly infused with A.I.”

A: Fundamentally, algorithms aren't in the hands of IT people, but in the hands of electrical experts, infrastructure experts, coal experts, pharmaceutical experts, and experts from various industries. At the practical level, Chinese manufacturing's application of artificial intelligence is very rapid, and many Chinese models will emerge.

Q: What support do private enterprises need from the state for their development?

A: Rule of law and marketization, with government administration according to law and regulations. Enterprises should focus mainly on value creation, technological breakthroughs, law compliance, and legal taxation. This harmonious development model will gradually release economic vitality.

Q: How do you view openness and development?

A: The country is becoming increasingly open, and openness will drive us to greater progress. Under Party leadership, the nation is administratively unified with smooth policy implementation. The gradual formation of a unified large market is possible and will certainly break through all blockades to achieve great rejuvenation.

[Ren Zhengfei of course got the seat of honor during the the Feb 17 Symposium featuring Xi which doubled as the Party’s olive branch to its leading S&T firms. We covered this meeting here on Xi’s Hard Tech Avengers.]

For more, see other core Ren Zhengfei speeches we’ve translated.

Read more

Has America already lost its dynamism in basic research? Josh Wolfe, co-founder of Lux Capital, joins the podcast today to discuss.

We get into…

• Why the Trump-Elon fallout matters less than you probably think,

• How much payoff corporate leaders are reaping from their campaign to appease Trump,

• The erosion of the U.S. research ecosystem, and how we should think about philanthropic giving amid that chaos,

• Parenting, strategies for emotional resilience, why short videos aren’t terrible, and the history of the machine gun

It’s a good interview. Listen on Spotify, iTunes, or your favorite podcast app.

Dreams of the Tech Right Meet Reality

Jordan Schneider: We have to start with Trump and Elon. I’ll let you pick the frame.

Josh Wolfe: I’m going to take a contrarian position — it’s irrelevant. It’s irrelevant because it dominates front-page news and captures everyone’s attention. I joked yesterday that if you were planning fraud or were a terrible company with bad news, yesterday was the perfect day to release it while everyone focused on this inevitable outcome.

People were making predictions six months ago — over/under bets on whether it would last three months or maybe a year.

Jordan Schneider: There were actual betting markets created for this.

Josh Wolfe: Exactly. You were betting under a year, maybe over three months, but none of this was surprising. This was an unstoppable force meeting an immovable object — kinetic chaos was inevitable. Elon served as a useful foil for Trump and did an excellent job helping him win the election. They were strange and unusual bedfellows.

Trump has historically been a strong China hawk, albeit with nuanced moments regarding Xi Jinping. Meanwhile, Elon depends heavily on China in ways people don’t fully appreciate — particularly Tesla’s production levels and the profit margins China contributes.

Jordan Schneider: Well, the China Talks audience understands this, but perhaps not everyone does.

Josh Wolfe: Right, not the broader ecosystem. This creates a significant vulnerability. You’ll see Elon Musk historically position himself as an outspoken advocate of free speech — though whether Twitter was genuinely about free speech is debatable. I’m more cynical about his true aims.

What you’ll never see him discuss publicly is anything about China. He’ll never criticize Xi for human rights abuses in Xinjiang province or regarding the Uyghurs, and he’ll never mention Tiananmen Square. Nothing. It’s “Free speech for thee, but not for me” when it comes to China.

Inevitable clashes were bound to occur. Was this really about the spending bill, or something deeper? When the leaks started — clearly planted by the White House over the past five days about drug use, and then the Epstein connection — it became salacious and interesting for everyone, but none of it was surprising.

My position is that it doesn’t matter. It’s similar to tariffs — Trump campaigned on tariffs, Democrats attacked him, saying he’d implement tariffs that would be economically troublesome. I don’t understand why these developments are surprising when they shouldn’t be.

Jordan Schneider: Speaking about your profession, many people in the tech ecosystem — particularly with the rise of the tech right throughout 2023 and 2024 — pinned their hopes on this man, similar to how Elon did. They hoped that by being inside the tent, they could influence policy trajectory. From my perspective, benchmarking to June 6, 2025, this has been pretty dramatically disappointing.

What are your reflections on that psychological arc? Are these guys all just patsies?

Josh Wolfe: During November and December of 2024, I remember peak rhetoric around the zeitgeist of America’s golden age. All you could hear was “we’re back, baby” and these ridiculous 1980s Top Gun-infused, Hulk Hogan maverick-style videos celebrating America.

Jordan Schneider: Sure.

Josh Wolfe: I told my wife, who runs an activist public hedge fund and manages our personal money, “We need to buy long, deep out-of-the-money puts” because all I heard was “to the moon” and “American greatness.” It felt like an echo chamber of optimism.

Two to three months ago when the tariffs hit, those positions performed very well in our portfolio. We’ve been relatively unaffected on the venture side.

One area where real change is happening — and it’s always dangerous to say “this time is different” — but it feels very different: defense. We’re seeing a combination of a nearly trillion-dollar budget and a huge shift toward autonomous systems, AI-driven software systems, and space satellites. Remember, Space Force was an absolute joke eight years ago.

Jordan Schneider: Okay, we’re pivoting a little…let’s stay on track.

Josh Wolfe: But this is where the venture world has made noise and impact. There are sympathies, appreciations, and influence, particularly in tech and defense.

Jordan Schneider: Sure.

Josh Wolfe: Regarding everything else: you had everyone pledging fealty, taking a knee, and donating a million dollars to the inauguration campaign. Zuckerberg, Bezos, Satya, Sundar — they were all paying homage to Trump, hoping to escape DOJ, FTC, or antitrust scrutiny. How that plays out remains to be determined.

The Trump-Elon situation was both weird and destined to end inevitably. There will be some strange reconciliation, and they’ll be bros again. But I don’t think this is just about the spending bill — it’s much deeper.

Jordan Schneider: One of the things the tech right didn’t price in is what’s happening around immigration and the basic research ecosystem. Let’s start with basic research. There’s this argument that we don’t need the NSF or NIH because corporate R&D has increased significantly over the past 30 years and can drive innovation forward.

As an investor who focuses on scientifically ambitious investing, what do you think the economy gets from basic fundamental research that happens in labs and universities versus corporate R&D?

Josh Wolfe: Long-term: everything. Short-term: it’s hard to see the value. For policymakers looking at budget cuts — particularly those focused on short-term gains — these programs seem like easy targets. This isn’t just a Trump phenomenon. In 20 of the last 22 years, we’ve had federal cuts to federal science funding.

Jordan Schneider: We had a brief moment with the Endless Frontier Act.

Josh Wolfe: Right, it started with Endless Frontier, which referenced Vannevar Bush’s work from around 1945. Then you had “The Gathering Storm” by Norm Augustine, the former Lockheed executive, warning about America’s talent base and cultural shifts in what people were drawn to and celebrating.

What they didn’t mention in that report — now over 20 years old — was this anathema, this zeitgeist against the military-industrial complex, precisely when China was not only embracing but mandating military-civil fusion.

Over the past two to three months, we’ve witnessed a perfect storm. Now you have the politicization of academia. Harvard sits number one in Trump’s crosshairs — some speculate because Barron applied and didn’t get in, creating some Shakespearean vendetta. Whatever the reason, while anti-Semitism was the stated concern, it was far worse at Columbia, right here in New York City, than at Harvard.

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According to Nature magazine’s rankings — which publish various metrics including H-index measurements — when you look at the most important scientific publications by institution, the top 10 includes Harvard at number one, but positions two through ten are all Chinese universities.

Fifty percent of AI graduates worldwide come from China. Thirty-eight percent of the AI and computer science workforce here comes from China — not native-born Americans. They’re outpacing native American citizens by 35-37%.

We’re losing the talent game. What should we do to win? What we did in World War II and beyond: attract the best and brightest. Create brain drain from other countries because people are repelled from their home nations.

Eastern European Jews in the 1940s established the Institute for Advanced Study and brought Einstein here. Having the atomic bomb developed here rather than Germany was a net positive for the world. Soviet émigrés in the 1980s escaped communism for capitalism during the Cold War.

We should be stapling visas to every Chinese, Indian, Pakistani, Israeli — anyone who wants to come here. We should help their parents immigrate too, because often family remaining in authoritarian home countries becomes leverage that governing regimes use to control whether these individuals can leave or return.

The last Republican I remember discussing this was nearly 20 years ago: Newt Gingrich, who called for tripling the NSF budget. He understood that everything from Genentech (which emerged from the UC system) to Google (from Stanford) was premised on long-horizon scientific research.

This isn’t just computer science — it’s chemistry, physics, materials science, and all the breakthroughs that emerge from these fields. If we knew what those breakthroughs would be, we’d fund them today. But we don’t. We rely on this rich ecosystem in our own self-interest to support brilliant people who generate breakthroughs.

These breakthroughs often result from combining insights from one department with research from a different university. More than ever, this cross-pollination is critically important. We’re ceding academic and intellectual leadership to other countries. China will likely be the greatest beneficiary.

International students used to comprise roughly 25% of our student body. Now it’s down to 12-15% and falling. China is actively recruiting with programs like their Thousand Talents initiative.

This represents the greatest self-inflicted wound Americans have created in several generations.

Jordan Schneider: You had this line: “If the Politburo were drafting America’s self-sabotage plan, they would politicize science and freedom of inquiry, starve young and ambitious investigators of funding, and discourage the best immigrant minds."

To recap for everyone: the NSF is spending at half the rate it was in 2024, despite authorized funding. The new budget dramatically cuts science and research spending. Universities have been cut off wholesale from billions in research dollars. Johns Hopkins is laying off 1,000 people because they’re worried grants won’t materialize.

Trump said yesterday that we actually want Chinese students, which creates bizarre mixed messaging when his administration simultaneously tells Harvard they can’t admit Chinese nationals.

Josh Wolfe: Some of these grant cuts are both tragic and absurd. There was a researcher studying neurotransmitters for neuroscience whose grants were cut. They couldn’t understand why until they realized the word “trans” triggered a five-letter string search that flagged anything with “trans,” “DEI,” or similar terms.

Now researchers have to change grant language — writing “neurons firing intracranially” instead of “neurotransmitters."

Jordan Schneider: That’s not funny, though.

Josh Wolfe: You’re right. It’s tragic.

Jordan Schneider: Why don’t you talk about the $100 million pool you launched?

Josh Wolfe: It’s specifically not grants because we’re not trying to substitute the charitable giving of our government — funded by taxpayers — which actually makes America great when we have scientists working on breakthrough research.

Historically, about 10% of our investments are de novo new companies, and most emerge from academic labs. We find a principal investigator — a fancy term for a scientist at an academic institution — whether at Harvard, Princeton, Yale, Georgia Tech, Cornell, or elsewhere.

The early 1980s Bayh-Dole Act, sponsored by Senator Evan Bayh and Senator Bob Dole, allowed universities to own intellectual property created with federal taxpayer research funding. When a scientist at these institutions files a patent, the university becomes the assignee while the scientist remains the inventor.

We, as a venture capital firm, can license that technology. There’s a well-established deal structure involving licensing royalties and equity — the scientist typically gets about 25% ownership. This mirrors Google’s “one day a week” policy, allowing employees to spend time on personal projects, but applied to exclusive company work.

This approach for launching companies from academic labs is well-established. Professors often stay at their institutions while postdocs handle translational research and join the company. We’ve created about 25 de novo companies this way, spanning everything from 4D lidar for autonomous vehicles to digital olfaction — essentially “Shazam for smell” — to cancer therapeutics and Nobel Prize-winning work from the Howard Hughes Medical Institute that enables real-time cellular imaging.

Historically, this represents about 90% de-risked investment, meaning we take roughly 10% scientific risk. Now, with grant cuts and layoffs at institutions like Johns Hopkins, exceptional research is being abandoned — like proverbial Rembrandts in the attic. Scientists are wondering what to do next. If they wait six months for resolution, they need to find work elsewhere, whether in academia, nonprofits, or the private sector.

Our response is the Lux Science helpline — a bat signal for struggling researchers.

We’re dedicating $100 million from our latest $1.2 billion fund to double down on early-stage science risk. Instead of taking 10% science risk on 90% proven concepts, we’re willing to take 50% science risk on half-baked ideas.

We’ll help license patentable work into our existing companies or arrange sponsored research to continue funding relevant projects. For example, someone contacted us about novel materials for radiation hardening in space. We have 17 companies across the space ecosystem that could sponsor continued research.

Other scientists ready to enter the private sector can work with us to start new companies around their expertise. We’ll license their work, assemble their team, build laboratories, and launch them.

This is just a drop in the bucket — we can’t do this alone. We need dozens, if not hundreds, of other VCs to recognize the value of funding early-stage scientific work. It’s profitable, beneficial for national security, and good for business. Our $100 million allocation, while significant, isn’t sufficient by itself.

Jordan Schneider: I’ve received numerous emails from intelligent people essentially doing backfill work for USAID funding cuts. While it’s admirable that people are donating $10 million or $50 million, tens of millions of people will suffer, and we’re delaying future breakthroughs because we’re not conducting this research. The laboratory animals aren’t being fed, and you need the time, energy, and tacit knowledge built over years of lab work to accomplish meaningful research.

Josh Wolfe: Absolutely. This isn’t purely black and white — there are legitimate concerns about USAID politicization and questionable funding destinations. There are appropriate and inappropriate uses for that money.

My main criticism of the NIH isn’t to strip their funding, but to bias toward young investigators. Too much grant money goes to, frankly, older researchers. Older scientists can be set in their ways and resistant to new approaches.

You need that potent combination of naivety and ambition that drives both entrepreneurial and scientific discovery. Young researchers have the arrogance to say, “I know better than you — why wouldn’t we try this?” while older researchers respond, “Why would you do that? I’ve tried it ten times and it never works."

I would restructure the NIH budget and federal funding to favor younger investigators.

Jordan Schneider: I wonder to what extent the Silicon Valley tech ecosystem that embraced Trump and the DOGE energy — which led to all these cuts — stems from the fact that for the past 20 years, you could make the most money by being 19 and writing software. That’s not something you necessarily need a PhD for. The social returns to that work are very different from what you see when making novel materials and drugs.

Josh Wolfe: Absolutely. Even the term “engineer” shifted from physical engineer to software engineer. For at least 20 years post-internet boom — through the SaaS enterprise boom and cloud boom — that was the dominant paradigm.

Lux was on the periphery of that trend because we don’t really fund software. About a third of our investments focus on healthcare, biotech, robotic surgery, and medical devices. Another third covers aerospace, defense, manufacturing, and industrial applications. The final third is what we call “core tech,” defined more by what we don’t do — very little internet, social media, mobile, or ad tech.

Great fortunes were made and great companies built during the software boom. Interestingly, there’s a China parallel here. Fifteen years ago, Xi Jinping designated software as a domain China would fund heavily. This created incredible companies and ecosystems, and many US investors funded them, believing China was a democratizing, growing market. Knowing what they know now, it would be difficult to justify investing in companies like ByteDance.

Jordan Schneider: Unless you’re Bill Gurley [who recently funded Manus AI].

Josh Wolfe: I love Bill, and he’s not necessarily part of the partnership decision. We’ve discussed this, and he would argue there might be scenarios where teams like Manta are trying to exit China. I think this deserves more study rather than just criticism. However, I personally wouldn’t invest in Chinese companies that are part of CCP military-civil fusion.

The shift also happened within China. At the last Politburo gathering about a year and a half ago, the people close to Xi weren’t software engineers or computer scientists — they were from space, biotech, rockets, and defense. All hard sciences.

This coincided with when Jack Ma went to “spend time with his family” and when entrepreneurs were capped at $9.9 billion. Anyone exceeding that threshold was essentially decapitated — they could start schools or enter education, and either they or their family could leave the country, but not both simultaneously.

The new directive became hard sciences. I used to joke that if you wanted to make money, the greatest capital allocator wasn’t following Warren Buffett or Seth Klarman or other great value investors — it was listening to what Xi Jinping was funding, because that’s where the world was heading.

I agree that for the past 10-15 years, the focus has been software. Many VCs, including Marc Andreessen who said “software is eating the world,” were drawn to Trump partly because they felt rejected by Biden. They were spiting Biden and possibly spiting themselves long-term.

I still believe the greatest entrepreneurs don’t really care about political developments or the 10-year interest rate. They’re building something because they have a chip on their shoulder — and as I always say, chips on shoulders put chips in pockets. They’re driven by private ambitions with timeframes that supersede one, two, or even three presidential cycles.

I remain bullish on great entrepreneurs. There’s simply a shift from software to hardware.

Jordan Schneider: Something worth exploring is the importance of tacit knowledge in hardware versus software and the learning that happens almost entirely in universities during master’s and PhD programs. When you’re doing actual scientific work, you need some sense of navigating the dark forest.

Josh Wolfe: That’s absolutely true. This applies even to semiconductors and manufacturing. TSMC’s Arizona facility is starved of talent — not just union workers doing physical assembly, but specialized expertise. There’s a scarcity of talent because much of that tacit knowledge remains in Taiwan and is difficult to transfer here.

You see this dynamic in companies working on the most sophisticated technologies. My partner Sam Arbesman, who you know or have spent time with, is a brilliant scientist-in-residence here. He has a new book coming out called “The Magic of Code,” and his previous book “Overcomplicated” offered a modern version of “I, Pencil” — the thought experiment about complexity.

If you were to make a semiconductor today, or an Apple iPhone, consider the number of components, the tacit knowledge required, the number of countries and companies involved — it’s extraordinarily complicated. No single person can make a pencil, let alone a semiconductor, chip, GPU, or field-programmable gate array.

Culturally, we get what we celebrate. For 25 years, we at Lux have complained that American culture celebrates celebrities — the Kardashians, the Hiltons, and similar figures. You see this manifested in TikTok and what gets fed to American users versus what’s not even allowed in China and what China celebrates in terms of STEM education.

We’re losing this battle terribly. Looking at the labor pool: we have 300,000 undergraduates in science here. China graduates approximately 1.2 million. Half of our 300,000 are foreign students.

This represents a cultural crisis regarding what we want our children doing and celebrating. We don’t need more people in marketing, advertising, or selling products. We need people inventing things that everybody else in the world wants to buy.

Jordan Schneider: And podcasting.

Josh Wolfe: But you produce intelligence and insight, which is valuable. It’s unique insight because, as you noted, people who follow China Talk understand things that others don’t. That’s an advantage — you produce something intellectually valuable.

Jordan Schneider: Back to the narratives. There was this fascinating Twitter exchange a few days ago. You mentioned the atomic bomb and the Apollo program, and J.D. Vance framed it as “we didn’t need foreigners to do this — we had 600,000 Americans weaving the wires to connect everything together."

Both perspectives are true: his narrative about American workers is accurate, and your narrative about leading lights of both the rocket and nuclear programs coming from Europe is also true. But this narrow-minded “you have to be born here to be part of the circle” mentality — let’s discuss what that means.

Josh Wolfe: This created a significant fissure. People entering the administration who were immigrants from India were being lambasted by these self-described “heritage Americans.” Elon defended them because he’s an immigrant himself — not the classic immigrant from poverty in India or Russia, but an immigrant nonetheless.

He argued there’s a distinction between immigrants crossing the border and taking blue-collar jobs — who may not conform to American society and could include criminals or drug dealers — and brilliant people making extraordinary contributions. For example, the recent genetic medicine breakthrough that cured a baby using one of the first in vivo genetic editing approaches involved two scientists, one whose parents arrived from India 40 years ago. Thank God those individuals came here and had children.

We want this brain drain — from World War II through the Cold War to our current version of Cold War competition. I don’t understand why people consider “immigrant” a dirty word. Immigrants literally are the fabric of this country.

One of my mentors who put us in business, Bill Conway, who founded the Carlyle Group, focuses his philanthropy on addressing one of America’s biggest problems: nursing shortages. He says if you’re anti-immigrant, good luck getting sick, because our entire healthcare system depends on immigrants playing critical roles — from hospital orderlies to doctors to neurosurgeons.

We want the best and brightest coming here. It’s a complete self-inflicted wound to say “America First” means shutting out talent. America First doesn’t mean America Alone, as Scott Bessent has said. Scott is one of the great adults in the room and a friend.

People ask why Scott doesn’t speak out more publicly on these issues. Scott is a student of markets first — he understands currencies and countries — but he’s also a student of human nature. He understands in a Shakespearean way who his boss is, who he works for, and how to manage that relationship. We want him doing exactly that because we don’t want him out of the job.

Jordan Schneider: We discuss immigrants and science frequently on China Talk from a US-China competition perspective, and that’s all valid. But the fact that people want to come here is remarkable. Look, at the margins there are legitimate concerns about completely open borders, but limiting human flourishing by building walls and splitting families is just —

Josh Wolfe: I’m going to be blunt because I come from Brooklyn: this approach is counterproductive and self-defeating. The idea that we’re limiting the immigration of brilliant people who could make this country better is fundamentally wrong.

Our greatest export isn’t our music, Hollywood, fashion, high-tech companies, banking system, or rule of law — it’s the American Dream. The American Dream is arguably our greatest export; it’s what everybody wants. The measure of a great country is whether more people want to enter than want to leave.

Walter Wriston said, “Capital goes where it’s welcome and stays where it’s well-treated.” This applies to both money flows and people flows. I hope the rhetoric will change and that there will be enough great American leaders to counter jingoistic “America First” voices.

There’s a delicate balance: we must remain that shining beacon on the hill, attracting people while distinguishing between good people who genuinely want to build better lives here — who want to embrace the American Dream and become proud Americans — and bad actors who want to undermine the country. Many of the latter are coming through our university system and may be funded by foreign actors, but that’s a separate issue.

There’s virtue in virtuous people coming here and the American Dream being upheld and celebrated. Right now, we’re casting shadows on that dream.

Jordan Schneider: You opened by saying the Elon-Trump fight is noise. But the signal is that people around the world would rather live here than in China.

Josh Wolfe: They still do. My wife mentioned recently that many countries hate us right now — Canada, tourism is down — and there’s probably some schoolyard “arms crossed, I’m not playing with you” attitude.

Jordan Schneider: Sure.

Josh Wolfe: The reality is, I read about how Canada supposedly hates us, then the next headline I see — because I read many papers each morning, including the Globe and Mail — is “Canada wants in on Iron Dome."

The rest of the world, even if they hate us, still wants our superior military technology. The zeitgeist of popular antipathy will fade, but people will still want our materiel — our military materiel.

Jordan Schneider: We’re recording this a few days after the Tiananmen anniversary. The fact that hasn’t happened here — the fact that there is free speech, elections, due process, and habeas corpus — represents incredibly powerful long-term advantages. These aren’t just abstract principles — they’re things that make life worth living and make you excited to get out of bed in the morning.

Josh Wolfe: I remain relatively optimistic personally. I’m always optimistic about technology, science, and ultimately the human condition. I’m always skeptical about people because I’ve read a lot of Shakespeare. Technologies are amazing, science is amazing, and both will continue to progress. People generally disappoint because they’re vainglorious, full of ego, petty, jealous — they connive and deceive.

People ask how I can be optimistic yet cynical. That’s the pairing — I’m optimistic about science and technology, skeptical about people. I love Tom Wolfe’s answer when asked why he writes about space, astronauts, and moneyed Upper East Siders but not politicians. He said politicians are like passengers on a train, and the country is the train. The tracks might go up and down, but it’s generally heading in the right direction over time. Inside the train, there are clowns on one side in red and clowns on the other side in blue, throwing pies at each other nonstop. Every four years, the engineer changes, but the train stays generally on track.

I take that view: the real thrust comes from people, values, that great beacon on the hill, the American Dream that attracts people here. We shouldn’t deter them from building here on that track. Most entrepreneurs couldn’t tell you much about the political system or what’s happening at the Fed or Treasury — they’re focused on building.

Jordan Schneider: But the fact that they have to worry now, that they have to fear their visas getting revoked — look, in other moments that might be manageable. But within our range of expectations, there are definitely scenarios where an executive acting alone can really bend those train tracks.

Choosing Optimism + Parenting

Jordan Schneider: Speaking of Shakespeare, we did a show with Eliot Cohen about his wonderful book The Hollow Crown and another episode as a Biden emergency discussion. The Trump-Elon situation probably deserves its own Shakespeare emergency episode.

told me to ask you this question — does America need a Gen Z Marsha Linehan?

Josh Wolfe: Marsha Linehan is one of the founders of CBT — Cognitive Behavioral Therapy.

I love Derek. I got into psychology maybe five or six years ago. My kids are 15, 12, and 9. My oldest daughter is much more like me — emotionally volatile. I’ll have high highs (not bipolar…emotive!) then calm down. My wife and middle daughter have slow burns with grudges lasting three or four days.

We learned CBT and DBT techniques as a family. Derek’s question is whether Gen Z needs this — I think they do. CBT is essentially Stoic philosophy in a clinical psychology setting. I wish I’d learned this 20 years ago as a kid or teenager — I would have had healthier relationships. I wish I’d learned it 15 years ago before my first child was born — I would have been a better parent. We have a better marriage, family relationships, and even professional interactions because of these principles.

First, avoid extremes like “you always do this” or “you never do that.” If I said “Jordan, you’re always late for podcasts,” your first reaction would be defensive because it’s not true — nobody “always” or “never” does anything. People shut down and become defensive. You want to find the dialectic, avoiding black-and-white thinking. “Sometimes I feel frustrated when you’re late” is much more effective.

Second, when someone has an emotional outburst, they’re dysregulated for various reasons — hunger, a bad day, a lack of tools. If my daughter has a fit, she’s not thinking “I really want to have a tantrum and lose my phone for a week.” You appreciate that they’re doing their best with what they have — they just lack the tools.

Third, validate emotions. When someone’s really upset about something, you could say, “That’s ridiculous, it’s just a math test, you’ll get an A.” But explaining away someone’s feelings doesn’t help. People need validation. They become more emotionally frustrated when they don’t get that release valve. Saying “I can see you’re really upset” sincerely can help reduce their emotional burden.

Returning to Derek’s question about Gen Z, many people seem massively oversensitive. I grew up in Coney Island, Brooklyn, where people talked trash to each other, were rough around the edges, and the world wasn’t safe. You could say all kinds of things. I’ve raised my kids similarly — I don’t want them so soft that when someone says something offensive, they appeal to authority, running to school or teachers saying “he said this” or “she said that.” Take care of it yourself. Have a conversation. I’m not advocating violence, but handle yourself.

My kids have experienced this and tell us about various scenarios. The younger generation — whether you call them far left or woke — has lost some ability to engage with people. When encountering ideas or comments they disagree with, there’s hysteria.

I was a center-left Democrat my entire life. I didn’t vote for Trump, but I also didn’t vote for Kamala. I voted for Bloomberg-Romney, which was not a ticket, but that’s where my values aligned, in a non-swing state where my vote didn’t matter. I had the luxury of voting with my conscience.

I believe many center-left Democrats didn’t move right because they were attracted to the right. They were repelled by the histrionics, noise, whining, and complaining from the left. Enough was enough.

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Jordan Schneider: Let’s stick with parenting. You mentioned earlier that Steve Jobs accomplished incredible things, but everyone around him in his personal life had a totally different experience.

Josh Wolfe: They hated him. This is a fascinating phenomenon.

Jordan Schneider: This really resonated for me when I was reading a biography of Richard Holbrooke — the most storied American diplomat of the second half of the 20th century, though perhaps not well-known in the Asia-watching community. There was a line where his kid said his father wouldn’t recognize his grandchildren in a toddler lineup.

Growing up, I dreamed of being Secretary of State or a diplomat, but trading family relationships for that achievement gave me pause. Many people choose one path over the other. What are your reflections on this dynamic of accomplishing big things while being awful to the people closest to you?

Josh Wolfe: I used to debate this with one of my best friends, a famous journalist, who talked about how great Jobs or Elon were. My response was that the people around them — their families — hate them. They’re celebrated by strangers, feeling love from millions of people they’ve never met who celebrate a caricature of who they actually are. Meanwhile, their true character is loathed by those closest to them.

I’ve admired something I have to admit I’ll never achieve — I am too rough around the edges, have burned too many bridges, and have been abrasive to too many people. When Warren Buffett gave the eulogy for Coca-Cola CEO Don Keough, he summarized it in three or four words — “Everybody loved him.” I thought that was beautiful.

People will not say that about me, but I can control the decisions I make regarding my children. Will my kids feel that way about me?

I experienced something very salient and memorable involving my grandfather, who raised me. I grew up in Coney Island, Brooklyn — my mother, grandparents, and I shared a two-bedroom, one-bathroom apartment. We were very poor. My grandfather wasn’t my biological grandfather; he was my grandmother’s second husband, but he treated me like his son. He delivered the Daily News at night and was the most important man in my life.

He passed away the month before September 11th. At his funeral, his biological son was present. During the Jewish ceremony, when family members put dirt on the grave, his biological son approached with such animus. It was like “good riddance” — he took the shovel, threw dirt on the grave, and walked away. That sound still echoes with me.

I’ve always loved this quote from Carl Jacobi, the 18th-century mathematician: “Invert, always invert” — flip it on its head. My father wasn’t present in my life, so I became the father and husband he wasn’t. But watching that funeral moment, I resolved that would never happen to me. I never want my kids to feel that animus and animosity, wanting to dump dirt on my grave and walk away saying “good riddance."

The most important thing to me is what Adam Smith wrote about — not just the invisible hand, but the idea of being lovely and being loved. That second part, being loved, is scarce and valuable.

Scott Galloway recently gave a rant — I believe it was on Piers Morgan — where he talked about our obsession with Elon, innovation, and money while ignoring people who are hurting and suffering, including those losing USAID funding. He asked what it means to be a man. In his view, it wasn’t toxic masculinity — being a man means being able to take care of people.

We’ve lost that. There aren’t great male role models in public life today that young people celebrate for being good men through self-sacrifice. Everything centers on self-aggrandizement.

Regarding how to encourage or discourage people on certain paths: I want my kids to be truly happy. I ultimately don’t care where they go to college — the world has changed significantly. I don’t care what they do professionally. I want them to find purpose and meaning.

This relates to something interesting. Dan Senor works at Elliott Associates but is very active in Jewish and Israeli life. We attended Shabbat dinner at his house. I’m not religious — I’m an atheist but a tribal Jew. He blesses his children, and what struck me was that the blessing wasn’t about success, money, or career achievement. The blessing was “I want you to have a life full of meaning and purpose."

I thought that was beautiful. That’s what I want for my kids.

Philanthropy, Parenting, Short Videos

Jordan Schneider: We have five minutes for five quick questions. Take your pick — future of media advice for China Talk, New York mayoral race hot takes, what you’d do with a $10 billion philanthropic foundation, or something else.

Josh Wolfe: I don’t know.

Jordan Schneider: Where do you want to go?

Josh Wolfe: Mayoral race. I really hope Cuomo wins.

On advice for ChinaTalk, people get the audiences they deserve, and you have a smart, sophisticated, engaged audience looking for signal among the noise. Keep doing what you’re doing — your combination of Substack, podcasts, video content, periodic pieces, and great guests works well. I feel privileged to be here with you and enjoy reading your work.

Just maintain it because it’s a high-signal, no-BS voice. These things aren’t linear — there are step-change functions where suddenly something goes viral and you gain another thousand or ten thousand subscribers.

You should periodically write op-eds in major publications like the Wall Street Journal or Financial Times, sharing insights from your work. There are proxies like Stratfor and others in popular geopolitics, but you own a valuable niche. Over time, whether you do it or someone else does, there will likely be aggregation and acquisition — a China expert, Africa expert, defense expert — building a new media ecosystem where you could benefit from that outcome.

Jordan Schneider: Second and third questions — you’re pretty wealthy and likely to become wealthier. How do you think about big philanthropic investments beyond what you’re doing today?

Josh Wolfe: There are two aspects I really admire. Take what Bill Conway did — he’s not pursuing vainglorious naming opportunities. He literally identified deficits. His late wife was focused on nursing, so they fund nursing schools and programs because we have absolute scarcity there.

Considering the arc of AI, I believe in abundance and scarcity dynamics. What’s abundant will be machines helping with intellectual tasks — white-collar jobs will be hit while blue-collar jobs will surprisingly be safer than people think. The care aspect of healthcare will be critical.

If you ask what I want my kids doing: I grew up playing extensive video games and watching tons of TV, and I allow them that — not Monday through Thursday, but weekends they can play games, watch TV, engage in pop culture, watch sophisticated content like Fareed Zakaria and Jeopardy.

But I want them fully versed in AI. My 9-year-old is better than my wife at ChatGPT queries and Midjourney prompts for images. It’s creative expression.

Jordan Schneider: That’s a great age for it, right?

Josh Wolfe: Absolutely. My oldest daughter had to do an evolution project in seventh grade by hand — organisms with sharp teeth survive candy rain while weak-toothed ones die. She drew it manually. My current seventh-grader in that same class is using one of our companies, RunwayML, for AI video generation, creating full videos of different organisms in her scenario.

I want them totally versed in AI because ultimately — and you discussed this recently, maybe with Wang — the power isn’t in who has the chips, but who’s using them. Similarly, power isn’t in who has the applications, but who’s using them.

There’s a significant push for the world to use US-driven open-source or closed models rather than China-driven models that approach an asymptote of truth but never discuss Tiananmen Square, Xinjiang, or Uyghurs. We want the Global South influenced by American ideals of truth, Popperian hypothesis, conjecture, and criticism rather than Chinese systems.

But I want my kids using all these tools and understanding them. What will be scarce against all that abundance is human connection. They need to understand people, make eye contact — you’d be amazed how many kids, because of screens, have awkward, almost autistic interactions.

Being able to connect with people, understand them, read Shakespeare — that’s timeless. People change, costumes change, stages change, but human nature hasn’t changed since the Pleistocene African savannah.

That’s what I’d fund philanthropically. Derek mentioned CBT programs for young people earlier. I started a charter school 17 years ago in my native Coney Island, Brooklyn. We began with 90 fifth-graders in the projects. Now we have 1,000 scholars, 200-plus faculty, 100% college acceptance rate for first-generation college students. Eighty percent of families qualify for free and reduced lunch — a euphemism meaning a family of four makes less than $30,000, which is insane.

These families lost the ovarian lottery — the classic John Rawlsian veil of ignorance. These kids are no less intelligent than those born in Greenwich, Connecticut. But there’s no Army recruiting station on Greenwich’s Main Street — there is one on Cropsey and Stillwell in Coney Island. That’s not fair.

Those are worthy targets for philanthropic dollars.

Jordan Schneider: Okay, but let’s start from a $10 billion bucket. What are we talking about here?

Josh Wolfe: Where would I give? I would fund universal CBT for everybody in the country. I don’t know that it needs that much money — it just needs celebration in the country that helps people become more emotionally regulated and be their best version of themselves. It will reduce problems in our criminal justice system. It’ll reduce problems in corporate America. It’ll reduce a lot of problems across the board.

Jordan Schneider: Not to rag on you too much — you give very sophisticated answers to how to invest in the future of science and technology. That was a fine answer. But a lot of people, at a certain point in their life, switch from the sort of answers we discussed in the first 80 minutes to the question I just asked you. I’m curious: do you see the future differently when it comes to philanthropy?

Josh Wolfe: Where we give philanthropically right now reflects things that we prioritize. For me, complexity science through the Santa Fe Institute — brilliant people. I love it. I believe that’s a source of tremendous value. I’ve been part of that for 10 years as a trustee and believe deeply in it.

The charter school movement — I believe deeply in that because it’s a form of civil rights for people. My mom was a public school teacher, so this hits close to home.

Jordan Schneider: Let me try one more time. This is more of a meta question. The sort of investigation that you need to understand how to use philanthropic dollars efficiently and effectively — I’m curious how similar or different you think that is from investing?

Josh Wolfe: The only similarity is finding an amazing social entrepreneur. It’s like when we started the charter school — we basically backed this guy Jacob Newkin, who was starting the school. It’s the same thing. I used to talk publicly about Jacob: he’s the greatest social entrepreneur that I’ve backed by spending my time and money with him.

But we weren’t doing analysis on the market and the unmet need and that kind of thing. It tends to be something personal. For my wife, it’s the Center for Reproductive Rights. She’s on the board there, making sure that women have access to contraception and abortion and autonomy over their bodies. That’s a really important thing to her.

She’s not doing an analysis of where’s the best place to give or whether we should give more. It’s just: Roe v. Wade got overturned. There are women who are going to die in certain states because they can’t get abortions. What can we do about that? She gives a lot of money.

Jordan Schneider: Maybe we’ll close on this topic. If we’re entering a world where science receives less funding — Danny Crichton, who works for Lux Capital, wrote a really interesting piece about this — when the total amount of science that the US funds decreases, there’ll be a little spillover to China and the EU, but we’ll just have less science overall. Beyond CBT, what encouraging developments do you see for science and technology’s future? What basic research do you think people should be funding — the stuff that’s too risky for any venture capitalist to invest in?

Josh Wolfe: This might be controversial, but people should be spending far less money on climate philanthropy. The answer lies in what I call elemental energy and nuclear power. All that money should be redirected toward early-stage science and psychological and behavioral health research, because that will make society better.

The Gates Foundation, Bloomberg Philanthropies, Ford Foundation — these organizations were captured by the climate movement over the past 15 years. Honestly, I don’t know what it’s accomplished. It’s been a colossal waste of money.

Jordan Schneider: Speaking to the culture issue you raised earlier — it’s striking to me. I worked at an organization that was half nonprofit, half research fund, focusing on China and climate. On the climate side, they could get money to fund literally anything.

Josh Wolfe: It’s popular and makes you feel good. You go to a cocktail party and say, “Oh, I’m funding climate research.” Great, you’re doing wonderful work — Al Gore would be really proud. But the money is misplaced.

Jordan Schneider: It’s almost downstream of the culture. Who are the funders and trustees, and what’s popular with them? They’re not scientists conducting expected value calculations on human flourishing or whatever. Not to disparage anyone, but it’s something that resonates with them personally.

Josh Wolfe: Look, Sam Bankman-Fried was the emblematic figure of this, but the effective altruism movement was rational in trying to determine where we can do the most good. They approached it economically, looking at low-probability, high-magnitude events and identifying opportunities where small amounts of money could have significant leverage.

Going back to Conway’s nursing initiative — that’s not popular. People don’t get excited about addressing the massive nursing shortage. But he identified this as crucial, and they’re putting several billion dollars behind it. That’s noble work.

Bloomberg’s urban initiatives and charter school funding are excellent. People funding the arts because of personal passion — that’s great too. But we have massive problems with criminal justice reform and behavioral health domestically.

I’m not talking about everyone needing mental health days, but implementing cognitive behavioral therapy in schools at a young age. Before children’s prefrontal cortex develops at 25, we could help them develop better self-regulation. The world would be a much better place.

It would be tremendous to see philanthropists return to funding institutions like the old Cavendish Laboratory — putting billions of dollars into institutes that enable knowledge discovery.

Jordan Schneider: Rockefeller University — that’s incredible work. People need to get with the program.

Josh Wolfe: Carnegie Mellon, exactly. These institutions started with robber barons who decided to redirect money into academic institutions. This will happen again.

If you examine philanthropic funding historically, it began with private individuals, then government labs like Los Alamos, followed by Bell Labs (born from monopoly), then IBM Research. IBM centralized initially, then distributed with locations in Zurich and Almaden. Then came Google, Intel, and Microsoft Research.

Some of these corporate labs are under pressure now because they haven’t yielded significant results. But we’ll see the rise of private labs. You can see this already with the ARC Institute.

Jordan Schneider: Absolutely.

Josh Wolfe: The Collison brothers are major supporters there. The Chan Zuckerberg Initiative represents major scientific initiatives comparable to Howard Hughes — himself a former defense contractor who invested enormous amounts into what became the Janelia campus, now one of the great sources of Nobel Prize winners.

Jordan Schneider: That’s a nice place to close. 50% of Howard Hughes researchers came to the US on visas! Joshua, thanks so much for being part of this.

Josh Wolfe: Great to be with you, man.

Jordan Schneider: Awesome. We’ll do this again in 10 years, and then you’ll be saying, “Here’s this philanthropic vision — look at all these molecules I found."

Josh Wolfe: I believe mostly in free enterprise, science, and technology. Early-stage ventures will handle a lot of that, but not the basic science research. There’s no market for that.

Bonus Riffs on Books

Cool. What are you reading? Anything good? Binge-watching anything inspiring or fun?

Jordan Schneider: Two books. I’m a new parent — I have a 10-month-old at home.

Josh Wolfe: Boy or girl?

Jordan Schneider: Girl. First child.

Josh Wolfe: Wow.

Jordan Schneider: I read all these books on paternity leave about “How I Raised My Child in X Country.” They were not good. But one was excellent: Italian Education. It’s by a cranky British guy who married an Italian woman and raised his kids in late 1980s-90s Verona. All these other books are basically backhanded critiques of American parents from whatever direction. But he’s just observing this really interesting, weird society where you have very tight connections between parents and kids — for better and worse, from my perspective, across many dimensions.

It was engaging, funny, smart, with nice vignettes. Each chapter stands on its own, which is good for 3 AM reading.

Book number two — A Social History of the Machine Gun by John Ellis.

The book tells the story of the machine gun through different lenses. He’s a military historian who wrote about World War I and World War II tactics. But in this book, he explored the technological evolution from the Maxim gun all the way through World War II — who invented it, why, and where it came from.

There’s a fascinating acquisition story too, because people didn’t think it was real and didn’t want to buy it. There were prototypes but no factory yet, so you had these hucksters trying to —

Josh Wolfe: What years was this?

Jordan Schneider: At the start of World War I, the British had one gun for every 2,000 people. You had to get to 1916-1917 for them to actually be making and buying enough machine guns.

Josh Wolfe: That’s amazing.

Jordan Schneider: It took an enormous amount of time. The technology was already there in the 1880s and 1890s. There were examples from wars in different countries — the 1905 Russo-Japanese War, the Crimean War. You could see it if you were looking at the right things.

Ellis gives examples of smart colonels saying, “Guys, we need to buy these guns — they’re a big deal.” But people said no, and they all said no way too late.

The other story he tells is about the psychology of not just the people buying the guns, but the officers themselves who had to abandon their mindset about what made a successful officer. Being a sharpshooter wasn’t considered honorable. What won wars throughout the 19th century was discipline, standing in line without fear, marching together to bring maximum power. That’s what the technological paradigm demanded — willingness to maintain rank.

It took over 100 years for people to change their mindsets and understand that you actually need to be distributed, use natural cover on the ground, and get away from the Napoleonic mindset of gallant charges. Those charges were the correct evolutionary answer in a different time period, but not by the US Civil War, definitely not by the end of the 19th century, and absolutely not by World War I.

Josh Wolfe: It’s interesting — the juxtaposition of the two books. One is arguably about technology of life (all parenting is a form of life technology), and the other is about technology of death. It’s a nice contrast in what you’re reading.

Quick parenting observations — First, if you walk into a bookstore like Barnes & Noble — which really don’t exist anymore —

Jordan Schneider: There’s one three blocks away!

Josh Wolfe: The mere existence of a handful doesn’t change that they’ve largely disappeared. There used to be 20 in New York City; now there are one, two, or three.

My point is, when you go into any section — investing, relationships, or parenting — and see 200 books, it means nobody has any idea what they’re doing. If they did, there would be one book with all the answers.

What I learned, especially with our first child, is that you develop a whole bunch of lessons, then you have a second child and they’re all wrong. Once you have more than one child, the nature versus nurture debate is settled. They are genetically different from day one — their predispositions, attitudes, sleep patterns, crying patterns, wants and needs. Their personalities persist from birth. The one who’s more reactive, the one who’s more smiley — it’s absolutely fascinating.

Second point on parenting, which relates to China — when I was growing up, my mother said, “You need to learn golf and Japanese because that’s the lingua franca of business in the ’80s.” Then it became, “You need to learn Mandarin and coding because that’s the lingua franca."

Neither of those things really matter today. The pace of AI development means coding can now be done by AI agents. Computer scientists who thought they were in a valued position are suddenly thinking, “Oh my God, I’m being replaced by agents."

Translation is pretty incredible now too. I don’t know what the next parental trope will be, but it’s usually wrong.

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Jordan Schneider: We can take it back to the machine guns, right? What was successful for you as you were coming up in the world and in the institutions that shaped you isn’t necessarily going to be the thing for the next era. The humility to understand that — both from a defense acquisitions perspective and a parenting perspective — is really hard.

Josh Wolfe: I’ll give you an investing version of that. First, the most dangerous words everyone always says are “this time is different” — because it never is. If you know Shakespeare, then of course it’s never different. Human nature is constant.

But when parents utter certain words, it’s predictive — similar to the defense acquisitions issue or for investing. Want to know what will be the next $10 billion industry? Here it is: “It will rot your brain.” Every time a parent says “it will rot your brain” about something they don’t want their kids doing, that thing becomes the next massive industry.

Rock and roll in the ’50s, TV in the ’60s and ’70s, chat rooms in the ’80s and ’90s, video games in the ’90s and 2000s — every one of those things that was the target of parental ire became the next $10 billion industry. Tipper Gore with parental advisory lyrics and rap music — rap became the biggest genre of music in the following decade.

Just listen to what parents are terrified about right now. The gamers became our modern robotic surgeons and drone pilots. Whatever they’re freaking out about now — maybe TikTok (though I have problems with that for different reasons) — it could be movie-making on social media or whatever.

Josh tries to defend short video

Jordan Schneider: This is the hardest question of the day — give me the optimistic short video take.

Josh Wolfe: We’ve democratized the ability to have creative expression with special effects that used to cost $50 million. Filmmakers used to be siloed in studios with hierarchies, casting couches, and Harvey Weinsteins — awful people. Now there’s freedom of expression where people can create tragedy, drama, comedy, and surrealist content with these tools at their fingertips.

My 9- and 12-year-olds are better filmmakers than I was at 25. They have tools today that Hollywood executives used for Terminator or The Abyss — remember James Cameron’s special effects that seemed amazing back then? That’s from a creator perspective.

Jordan Schneider: What about from a consumption perspective? Having culture delivered in 30-second chunks?

Josh Wolfe: Again, look at it from abundance and scarcity perspectives. I 100% agree that if you’re constantly being trained for short attention spans, that’s problematic. We literally practice patience as a family because I know there are so many competing things offering fast dopamine hits and quick responses. We do long periods of quiet reading from physical books as a family. We watch long movies instead of 30-minute segments.

Jordan Schneider: No, but you’re telling me the things parents are scared of are actually going to be the future. What’s positive about consuming content in 30 seconds?

Josh Wolfe: I’d argue that your ability to process multimodal information is far better. Look at the average older person right now — they’re focused on one thing, they’re slow. You’re probably able to switch between a WhatsApp chat group, Twitter, watching a short video, and checking emails. Your ability to multitask while retaining the ability to function is super valuable.

Jordan Schneider: Your heart’s not in this one…

Josh Wolfe: It’s okay, but here’s what I know: it’s not as bad as people think. The TikTok stuff is concerning, but short-form video generally isn’t bad.

Jordan Schneider: Okay.

Josh Wolfe: I’m optimistic on the science and technology piece. I’ll still be skeptical about the human nature piece, but optimistic about science and technology.

Jordan Schneider: All right, let’s call it there then. This was really fun. Do you have a book to shout out?

Josh Wolfe: Let’s close on fiction and nonfiction. For nonfiction: The biggest debate my wife and I have had was over a book by Robert Sapolsky, a Stanford primatologist and neuroscientist who’s written a series of books. His first one was Why Zebras Don't Get Ulcers: The Acclaimed Guide to Stress, Stress-Related Diseases, and Coping. The punchline was that zebras run for their lives in their ancestral environment, then they’re calm. We have constant stressors all day long that didn’t exist in our ancestral environment.

But his more recent book is called Determined. Either you’ll want to throw it across the room, or you’ll want to send copies to everybody. It depends on whether you agree — as I do — that we do not have free will, or disagree — as my wife does — that we are filled with agency and of course have free will.

Danny Kahneman was a friend. His belief before he died was that neither free will nor consciousness exist — that they are both useful illusions. I very much subscribe to that view.

For fiction, Amor Towles has a short story collection called Table for Two. He wrote Rules of Civility, which is great. There’s a character from the second half of that book who gets extended treatment in a few more chapters in this collection.

But there’s one story that deeply touched me called “The Bootlegger.” It’s a short story that takes place in New York. The beauty of this, for me personally, was that I happened to post on Twitter about my love for this particular story. Amor Towles replies, which was very meaningful, and he says, “This is probably the most autobiographical story I ever wrote."

It’s a relatively short story set here in New York. A young couple, something happens, they go to Carnegie Hall, and this story unfolds. There’s a particular classical musician referenced in this fictional piece, and he replies to the story because he’s actually in it. It was this surreal fictional story that was a slight roman à clef of Towles’s life. He replies to me on Twitter, then the classical musician does too. I was like, “This is amazing."

Jordan Schneider: That’s really fun.

Josh Wolfe: I highly recommend Table for Two by Amor Towles. It’s a set of vignettes around two characters — probably 10 or 12 short stories. But “The Bootlegger” is awesome.

Jordan Schneider: Thanks so much.

Josh Wolfe: Great to be with you.

In 2011, China’s drug regulator cleared the nation’s first home-grown targeted cancer pill. Fourteen years later, a Chinese bispecific antibody is aiming to knock the world’s top-selling oncology drug off its perch.

Those two bookends frame twin contests now running in parallel. One is humanity’s decades-long fight against cancer, a disease that still claims one in six lives worldwide. The other is China’s effort to move from importing medicines to inventing them. This article seeks to follow these battles in real time by tracing the stories of four milestone therapies and their makers.

Founded in 2003 in Hangzhou by a team of returnee talent, Betta Pharmaceuticals launched the first targeted anticancer drug developed in China to reach the market. The success of its drug Conmana1 in China dovetailed with sweeping policy reforms aimed at making home-grown medicines more trusted, innovative, and affordable. The drug did not, however, make it outside China, despite Betta Pharma’s best efforts. Conmana is an example of “me too” innovation: a variation on an existing drug that performs just as well but not quite better enough to make it globally competitive.

Created through a rigorous internal drug development program in 2012, BeiGene’s Brukinsa did what Betta’s Conmana could not – it went global, becoming the first Chinese cancer therapy approved by the US FDA. A “me better” innovation targeting blood cancer, Brukinsa now reaches people in over 65 countries, bringing in over US$2 billion in sales annually.

Betta’s Conmana and BeiGene’s Brukinsa are both small-molecule drugs, meaning they are created through chemical synthesis. The real frontier of innovation that excites biotechnologists is biologic drugs, biomolecules such as engineered proteins or RNAs that act with greater power and precision inside the body.

Carvykti is one of the first innovative biologic drugs created in China. Initially discovered and tested in Xi’an Jiaotong Hospital by Nanjing Legend Biotech, the drug reached global markets with the help of Johnson & Johnson. First gaining US FDA approval in 2022, Carvykti now has regulatory approval across over 36 countries and has treated over 5,000 patients, with more to come.

The last story is unfinished. It’s about Akeso’s ivonescimab, an icon of Chinese biotech innovation in mainstream media. A biologic drug with a novel method of targeting cancer, ivonescimab received approval by the Chinese NMPA in April 2025. In countries like the US, where Akeso has passed the baton to US-based Summit Therapeutics to develop the drug, ivonescimab is still in the clinical trial phase, meaning it has yet to pass through the regulatory gauntlet. What’s exciting and undecided about ivonescimab is its potential to go head-to-head with the world’s best-selling drug, Keytruda. Whatever happens to ivonescimab over the next few months in trials outside of China will send a signal of exactly how successful Chinese biotech innovation has become. The world of biotech will be watching closely.

But let’s start from the beginning. Betta Pharma’s milestone achievement of Chinese regulatory approval for a new innovative drug (2011) happened only 11 years before Akeso’s ivonescimab earned a US$5 billion deal with Summit Therapeutics (2022). How did we get here?

Betta Pharma: The “Me-too” Era

In the 1990s, biopharmaceuticals — specifically oncology, the study and treatment of cancer — entered a new era of innovation. Up until the early 2000s, doctors primarily combated cancer with broad-stroke methods like surgery and chemotherapy. Now, new and improved methods were emerging: targeted therapies that zeroed in on cancer cells while minimizing damage to healthy cells and immunotherapies that helped the body’s immune system recognize and attack cancer cells.2

This revolutionary effect of molecular biology captured the attention of many bright scientists and doctors in China, including Dr. Wang Yinxiang 王印祥. Born in rural Hubei, he spent three years working in public health and three years completing a Master’s degree at the Chinese Academy of Medicine before he could truly follow his passion for oncology to the United States, where he earned a doctorate from the University of Arkansas.

Dr. Wang got his wish to do cutting-edge research as a postdoc at Yale, where he dove into one of the first targeted cancer therapies, Novartis’ Gleevec. Sharing his apartment was Ding Lieming 丁列明 – another Chinese transplant with a University of Arkansas MD. On strolls through New Haven’s Science Park, the two friends along with medical chemist and entrepreneur Zhang Xiaodong 张晓东 bonded over more than just science. They shared a bigger dream: to bring the newest in biotech to China.

Dr. Wang and Dr. Ding would ultimately join forces in 2003, when they founded Betta Pharmaceuticals to develop targeted cancer therapies in China. Betta opened its doors with a shoestring team – just 13 people, many of them what Dr. Wang affectionately called “kids,” fresh from bachelor’s or master’s program and learning on the fly. Nevertheless, they managed to develop icotinib (later sold as Conmana), a drug engineered to target EGFR proteins as a way to inhibit cancer cell growth.

In those years, China’s pharmaceutical industry hadn’t left the nest. Manufacturing of cheap, generic drugs dominated. To domestic investors, companies, and physicians, a business model built on new drug development was unthinkable: the costs and risks were too high, the regulatory process was a mess, quality and safety were still iffy, and previous such attempts had failed. Winning a clinical-trial slot for Conmana (a prerequisite for proving the drug could outshine current care) was nothing short of herculean. When the Peking Union Hospital director declared the study too risky and tried to dismiss him, Dr. Wang stood firm for ninety minutes, knocking down every objection until the approval stamp finally came down in his favor.

In 2009, Conmana made it to Phase III clinical trials, the make-or-break test of wide-scale efficacy. In Phase III, the team pushed the envelope again: rather than testing against a placebo, they pitted their molecule against AstraZeneca’s gefitinib (the world’s first targeted anti-cancer therapy) in the first Chinese study to challenge an imported standard head-to-head.

The study’s results, announced by leading academic Sun Yan at the 2011 World Lung Cancer Conference – also the first time a China-developed drug headlined an international academic forum – showed that icotinib could match the cancer-fighting power of the imported benchmark while causing fewer side -effects. Conmana, in other words, was a successful “me-too” drug, an incremental improvement on an existing pharmaceutical innovation.

After six grueling years, Conmana earned its first regulatory approval from China’s National Medical Products Administration (NMPA; although at that time it was still the CFDA).

Betta’s success as a fast follower of a next-generation cancer therapy was a triumph for Beijing’s returnee talent and national innovation programs. Conmana’s success had been fueled by funds from the Yuhang District Government of Hangzhou, the “863” Program, and the “11th Five-Year Plan” National Science and Technology Major New Drug Special Project.

The government showered Betta with accolades: the China Overseas Chinese Contribution Award, the gold prize for patents, first prize for the National Science and Technology Progress Award, and more. Chen Zhu, then Minister of Health, praised their achievement as “an emblem of ‘Two Bombs and One Satellite 两弹一星’ in the field of public health,” referencing a techno-nationalist ideal of a whole-nation project for science and technology development.3

However, for all its homegrown glory, Betta’s blockbuster never crossed the border.

In 2014, with the help of Roswell Park Cancer Institute, Betta filed to run a clinical trial for Conmana in the US, the first step towards seeking US FDA approval. However, the trial was shortly withdrawn. Newer, later-generation EGFR inhibitors were eclipsing Conmana’s performance, and there was no sense investing in trials when the product was unlikely to sell.

Though just a “me-too” innovation, Conmana was a landmark accomplishment for China. On the domestic market, the drug was meaningfully cheaper than its imported alternatives. Given the rapidly growing incidence of lung cancer in China, Conmana’s improved affordability made a real difference in patients’ lives. Still, it would take almost another decade before a China-developed cancer drug would make a global impact.

BeiGene: A “Me-Better” Drug Goes Global

China’s mix of capital, talent, and policy reforms was turning its budding biopharma sector into a global magnet.

Among the first drawn in was Pittsburgh native John Oyler. Familiar with China through his work at McKinsey in the 1990s, Oyler was stunned by the country’s science and technology progress when he returned the next decade. By the mid-2000s, regulatory harmonization, returning talent, and improved manufacturing infrastructure enabled China to meet the needs of global pharmaceutical companies, leading to the growth of contract research organizations (CROs), which provide outsourced medicinal science services. Oyler co-founded one such Chinese CRO, BioDuro, in 2005.

But serving foreign pharma clients wasn’t enough. As China moved toward deeper healthcare reform, Oyler saw an opening for homegrown innovation: “[China] had the capability to pour tens of billions of dollars back into the global industry to help pay for more research, which would not only make drugs more affordable in China, but across the globe.” Rather than repeat the trajectory of BioDuro, which was eventually sold, he wanted to create something enduring. “I wanted to build something here — in China — that is lasting, impactful, involved in great science, and can really help people,” he said. He aspired to create a company capable of developing world-class cancer therapies from a country many still underestimated.

To bring his vision to reality, Oyler needed scientists. He connected with Dr. Xiaodong Wang 王晓东, a top Chinese American academic biologist who recently returned to China to lead the new Beijing Institute of Life Sciences. The chance to work with Dr. Wang — a superstar scientist admired widely enough to impress parents at Chinese New Year — proved an effective tool for attracting talent. Together, they founded BeiGene in Beijing in 2010 to become the “Genentech of China.”

Early on, BeiGene focused on BTK inhibitors, a targeted cancer therapy that works by blocking cancerous B-cells’ ability to grow. The first BTK inhibitor, synthesized in 2007, showed promise but caused significant side effects. In 2012, BeiGene initiated a discovery program in San Mateo and Shanghai to develop a better BTK inhibitor. After screening over 3,000 compounds, the team identified the highest-potential molecule that would eventually become Brukinsa (zanubrutinib).

BeiGene aimed to take Brukinsa global from day one. To support worldwide approvals, the company built a 25-country trial program in which approximately 90% of patients were enrolled outside of China. The numbers delivered: Brukinsa consistently beat first-generation BTK inhibitors on safety and efficacy, turning a presumed “me-too” into a clear “me-better” that is now the standard of care for B-cell cancers.

Momentum snowballed. In 2019, Brukinsa set a precedent as the first Chinese-developed cancer therapy to win FDA approval, months before China’s own NMPA signed off. It has since secured clearances in 65-plus markets spanning the US, EU, Canada, Australia, Japan, and China, and now supplies more than half of BeiGene’s revenue with US$2.6 billion in 2024 sales. The company (rebranding as BeOne) has likewise gone global, conducting trials in over 45 countries.

Legend: A True Chinese Biologic

Witnessing the breakthrough of firms like BeiGene, Beijing set its sights on higher-value innovation. The State Council’s 2016 13th Five-Year Plan therefore called for “leapfrog development in the biopharmaceutical industry,” spotlighting cell and gene therapies, antibodies, and vaccines.

These platforms fall under biologics — large molecules derived from biological processes such as insulin and hormones — rather than small-molecule drugs such as Betta’s Conmana and BeiGene’s Brukinsa. Because biologics are bigger and more structurally complex, their effects are harder to predict and their manufacture far costlier, but they open therapeutic doors that chemistry alone cannot.

Founded in 2014 as a subsidiary of GenScript, Legend Biotech embodied the kind of biologics leadership the state now prioritized.4 After losing his father to cancer, co-founder Frank Zhang 章方良 united with Chief Scientific Officer Dr. Frank Fan to create the firm with the goal of advancing oncology.5

At that time, influential scientific journals, Big Pharma deals, and first-in-human successes had converged to position cell and gene therapies as the vanguard of biopharmaceutical innovation. Early successes led by the University of Pennsylvania highlighted the potential of CAR-T therapy,6 a type of treatment in which a patient’s disease-fighting T-cells are genetically engineered to seek and destroy cancerous cells.

Driven by the promise of next-gen cancer therapy, Legend’s 19-person team, working in “a room the size of a freight elevator,” crafted a second-generation CAR-T treatment targeting multiple-myeloma tumor cells (later sold as Carvykti). Leading the research was Dr. Frank Fan, who had studied at Xi’an Jiaotong University and worked at the Xi’an Jiaotong Hospital. Leveraging those ties, Dr. Fan was quickly able to initiate Legend’s first CAR-T clinical trial at Xi’an Jiaotong Hospital, turning the startup into a “dark horse” contender in the CAR-T space.

At the 2017 annual meeting of the American Society of Clinical Oncology (ASCO), Legend presented early-phase data from its trials in China: durable remissions in multiple-myeloma patients with only mild side effects. The first of its kind accepted for review by China’s NMPA, this CAR-T candidate signaled that the country could innovate well beyond small-molecule chemistry.

Such promising results drew members of the global life sciences community. J&J’s Janssen signed a partnership with Legend Biotech in 2017. This was a case of an outlicensing deal: when a company (such as Legend) sells or grants rights to a drug candidate, passing the baton to a different company (such as Janssen), which who takes on the responsibility to bring the drug through testing, approval, manufacturing, and commercialization. Such transactions are the lifeblood of the industry. However, the high-potential molecules worth such high-profile deals didn’t historically come from China.

With the combined efforts of Legend and Janssen, Carvykti won FDA approval in 2022, soon followed by clearances in the EU, UK, Japan, and Canada. Though not first-to-market, Carvykti’s superior clinical value crowned it best-in-class. This then completed China’s rapid climb from “me-too” copies, through Brukinsa’s “me-better” gains, to a world-leading biologic breakthrough.

Akeso: a top challenger emerges

Now, Akeso Biopharma’s new molecule is drawing notice as a likely first- and best-in-class therapy from China.

Akeso started as the dream of Dr. Michelle Xia, a Gansu native. While working for California-based Crown Bioscience and in other roles in the US and UK, Dr. Xia grew frustrated with the eight-to-ten-year delay it took for innovative overseas therapies to reach Chinese patients. So she and three partners founded Akeso in 2012, naming it after the Greek goddess of healing, with a mission to develop home-grown therapies for cancer and autoimmune diseases.

Akeso’s edge is bispecific antibodies (BsAb), a type of next-generation cancer treatment involving engineered proteins that strike two targets at once, such as igniting immune cells while starving tumors. The first proof arrived in 2022 when China’s NMPA cleared Akeso’s Kaitani (PD-1/CTLA-4), the world’s first commercialized BsAb.

Next came ivonescimab, a PD-1/VEGF bispecific now pushing Akeso onto the global stage. By jointly blocking an immune checkpoint and tumor blood-vessel growth, it qualifies as first-in-class – an industry term for a drug that introduces a truly novel therapeutic approach.

In June 2022, Akeso unveiled the Phase II results of ivonescimab at the annual ASCO conference, showing strong responses in non-small cell lung cancer. Just months later China’s NMPA granted the drug Breakthrough Therapy status for three medical use cases, enabling closer guidance and fast-tracking its review.

Sensing ivonescimab’s scientific and commercial potential, US-based Summit Therapeutics inked a massive deal in December, licensing Akeso’s innovation for up to US$5 billion.7 The corresponding press release hailed Akeso’s innovation as “the PD-1 / VEGF bispecific antibody that is most advanced in the clinic,” noting that neither the FDA nor EMA had yet approved any PD-1-based bispecific therapy.

The size and significance of this agreement marked a bellwether moment in Chinese biotech innovation. Blue-chip investors and multinationals began scouting the country for genuinely novel assets rather than low-cost manufacturing plays.

China’s slice of global out-licensing has since tripled to 12%, with deal value leaping from US$35 billion in 2023 to more than US$46 billion in 2024. This trend seems set to continue through 2025 and beyond.

The fate of ivonescimab and most other compounds covered by these recent deals is uncertain. Many drug candidates are purchased in the preclinical or Phase I stage of development, requiring another 5+ years and US$300+ million dollars before they pass the clinical and regulatory hurdles necessary to make it to market – or, they will fail, like roughly 90% of compounds that enter human trials. Only five China-originated drugs have ever cleared the US FDA (BeiGene’s Brukinsa and Legend’s Carvykti are two of them).

Ivonescimab could be next. Akeso’s molecule has already completed Phase I and Phase II, and is in the midst of several high-stakes Phase III trials. Its Phase III trials with Chinese patients have already demonstrated success, leading to two recent NMPA approvals in the spring of 2025. The defining test comes next: a Summit Therapeutics-run Phase III study spanning 108 locations in 12 nations, where the drug candidate must outshine oncology’s gold standard, Keytruda.

Keytruda (drug name pembrolizumab) has been described as “era-defining,” the “800-pound gorilla” of the class of drugs to which ivonescimab also belongs. Developed and commercialized by American multinational Merck, the drug has been approved for 41 indications8 across 18 types of cancer. It’s the world’s best-selling drug, raking in about $29.5B in 2024 – nearly half of Merck’s total revenue. Its upcoming 2028 patent expiry opens the field for new challengers.

Akeso’s ivonescimab could be one such challenger. If its global Phase III trial confirms that the drug’s positive risk-reward results can extend beyond China’s borders, Akeso’s first-in-class molecule may eventually also prove to be best-in-class, making it one of the biggest biotech stories of the decade.

On the horizon

Together, Conmana, Brukinsa, Carvykti, and ivonescimab trace a clear, but incomplete, arc: China’s pharma sector has evolved from reverse-engineering proven ideas to originating drugs that can contend for global standards. Each milestone marks a step from “good enough at home” to “competitive abroad,” showing how policy shifts, capital inflows, and returning talent have reshaped the industry’s ambitions and capabilities.

Those four successes are only a sliver of the story. Dozens of other firms have logged incremental wins, and many more have stumbled in clinical trials or overseas filings. With financing tightening, patent cliffs approaching, and regulatory expectations rising, the next crop of candidates will test whether China’s momentum is structural or situational. The outlook could range from steady gains in select niches to a broader slowdown if capital or policy tailwinds fade.

Whatever the trajectory, one fact persists: cancer is indifferent to where a molecule is conceived. Progress depends on tapping every credible lab and idea, whether in Boston, Basel, or Beijing. If Chinese innovators add new options to the world’s oncology toolkit, patients everywhere stand to benefit — and that, ultimately, is the benchmark that matters.

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Once hailed as the “Apple of China,” Xiaomi has evolved into the world’s No. 3 smartphone brand. The Beijing giant wires millions of homes with its TVs, wearables, and appliances while pitching itself as a seamless “Human × Car × Home” platform.

Founder Lei Jun now wants to turn that consumer-electronics prowess into hard-tech dominance. In 2025 alone, Xiaomi debuted its first in-house chip (the XRING O1) and showed off its sleek SU7 electric sedan. Yet the scorecard is mixed: the Robotics Lab has been folded into the auto unit, the SU7’s shine dimmed after a fatal crash, and new U.S. export curbs threaten the flagship chip program just as it launches. Can a smartphone playbook built on rapid iterations and razor-thin margins really scale to cars, robots, and semiconductors?

In this piece, we let you hear Lei Jun in his own words, through two translated excerpts. One brims with sky-high ambition, while the other is steeped in damage control. Read them back-to-back and watch how Xiaomi’s grand vision collides with hard truths of physics, finance, and public accountability.

From budget phones to bold hardware

Chinese media celebrate Lei Jun as one of the country’s signature tech entrepreneurs. After graduating from Wuhan University and weathering several early start-up misfires, he assembled seven co-founders in 2010 around a crowdsourced Android ROM that grew into Xiaomi. The early strategy was straightforward: sell affordable, capable smartphones. That formula made Xiaomi a household name in phones and Internet of Things gadgets, but the 2016 debut of the bezel-less Mi MIX concept signaled a pivot from “internet hardware” to true hard tech. In the translated excerpts below, Lei Jun traces that evolution and lays out why he believes Xiaomi’s future rests on chips, cars, and robots.

The following excerpt is an original ChinaTalk translation of a December 2023 interview between Lei Jun and reporter Wang Ning, broadcast on CCTV.

Original link | archived

Lei Jun: Let me start with some Wuhan University memories. Thirty-six years ago, in 1987, I was admitted to its Computer Science department. Back then I lived almost entirely on scholarships and professors’ projects; those funds literally carried me through four years of college. At one award ceremony I received a sizable scholarship; standing on that stage I vowed that if I ever could, I would repay the university a hundred, a thousand — ten-thousand — fold.

Lei Jun: My life-long dream was sparked in the Wuhan University library when I read Fire in the Valley, the story of Steve Jobs and early Silicon Valley. In the late ’80s, Jobs was my very first role model. But the more I understood Jobs, the clearer it became that I’m not him. Still, that doesn’t stop us from charting our own path and creating products that are different in their own right.

Angela: After graduating in 1991, Lei joined Kingsoft, a Chinese software company, where he progressed from software engineer to executive. Competing with Microsoft, Kingsoft faced countless problems including product flops and near bankruptcy. He then went on to found an online bookstore, Joyo.com, which was sold to Amazon in 2004.

Lei’s experiences with such missteps and missed timing during the early era of the internet led to his coining of the phrase, “Catch the right tail-wind and even a pig will fly” 站在风口上，猪也能飞起来, which he proceeds to explain in the interview.

Reporter Wang Ning: Your famous tail-wind principle is still quoted all the time.

Lei Jun: Back in my engineer-founder days we green-lit projects simply because they interested me or a few users asked for them; we rarely stopped to ask whether the timing offered explosive growth, so the companies survived but seldom scaled. That sort of company is hard to kill, but pushing it to greatness is equally hard.

That’s why I formulated the tail-wind principle. Don’t just keep your head down pulling the cart; look up and see where the wind is blowing. It was a major course-correction in my own playbook.

Reporter Wang Ning: What was the real test for you during that period?

Lei Jun: We had clearly missed the web’s prime window, so we kept asking when the next breakout would come; four or five years early we bet on mobile internet, but didn’t know when it would ignite—once the iPhone and Android hit, I knew the fuse was lit.

On Xiaomi’s “hard tech” pivot:

Lei Jun: Hard tech means chips, smart manufacturing, robotics, operating systems — those core layers.

Reporter Wang Ning: You keep hammering on hard tech.

Lei Jun: I do.

Reporter Wang Ning: Why is your drive to battle it out on hard tech so intense?

Lei Jun: We’re top-three worldwide, but we face giants: Apple, Samsung, Huawei. Without breakthroughs in core tech you’ll never build a moat or stand shoulder-to-shoulder with those titans. If Xiaomi dreams of being world-class, hard tech is non-negotiable.

Narrator: In 2020, Xiaomi’s tenth anniversary, it set a ten-year goal to become a next-generation hard-tech leader and deliver premium products.

Lei Jun: Every flagship product applies the newest, most advanced tech. Three years ago, I told the team we would benchmark against the iPhone across the board. This statement caused controversy. Were we just piggy-backing off of Apple’s fame to grab attention? But we must unsheathe the sword: set our own targets, dare to compare. Even if we lose all 100 metrics, daring to measure is step one. Can our phones really win? I had to persuade people over one-by-one that going premium takes patience, since earning user trust is a process.

Lei Jun: We started exploring operating systems from the very first days of the company. Seven years ago we resolved to create Xiaomi HyperOS, building the entire stack from the kernel up. Over 5,000 engineers have contributed, and we’ve just released the first version. Our goal is a human-centred, closed-loop platform that connects personal devices, the smart home, and the car.

Reporter Wang Ning: You’re working down at the OS layer — deep, technical stuff — yet you keep calling it ‘human-centred.’ What exactly does that mean in practice?

Lei Jun: AI is moving fast, so we’re baking the most advanced AI into HyperOS to give it a clear edge in intelligence over any rival platform. More importantly, that same intelligence has to knit together the entire “Human × Car × Home” ecosystem: people as in personal devices, cars as in a mobile smart space, and home as in smart appliances.

On electric vehicle strategy:

Reporter Wang Ning: Elon Musk called Xiaomi’s entry into the automotive industry “interesting competition.” Your response?

Lei Jun: Smart EVs merge auto and consumer electronics. One car CEO joked, “A smart EV is just an oversized smartphone on four wheels.” Not strictly true, but that shows the convergence. So yes, it’s challenging, but the difficulty is controllable.

Reporter Wang Ning: What do you mean by “difficulty is controllable”?

Lei Jun: Three years ago I still thought building a car was daunting, so I approached it with real humility. Our user research showed that when people hear ‘Xiaomi car’ they expect technology and an ecosystem. That led me to a guiding principle I call “nail the fundamentals, then amaze 守正出奇.” In practice it means: respect the hard rules of the auto business — quality, safety, manufacturing discipline, make sure the very first model is rock-solid, and only then layer on top the Xiaomi-style innovation that surprises the market.

Our second rule is ‘10-X investment.’ A typical automaker puts three to four hundred engineers and maybe one or two billion yuan into a new model; many cars you see are built on that. For our first car we assigned 3,400 engineers and spent more than ten billion yuan — over ten times the norm. With that level of commitment, I’m aiming to win.

Still, cars are complex. I worry about two opposite risks: the launch flops and nobody buys, or demand goes crazy and people wait a year and flame us for delays. Either way, there’s plenty of reasons for anxiety.

On Xiaomi's future amidst geopolitical uncertainty:

Reporter Wang Ning: With global turbulence and domestic headwinds, why double down on hard tech and stay confident?

Lei Jun: The tougher the climate, the more we should invest in technology. When others pull back, breakthroughs actually come easier, and we’re ready the moment the market rebounds. In fact, Xiaomi already returned to positive growth last quarter.

Why do we have the nerve to keep spending? Because in every field we play in there is still plenty of unmet demand; I believe Xiaomi is only at the starting line. Our approach is two-pronged: deepen our roots in China’s domestic market while pushing ahead with globalization. That’s the road we’ve chosen, and it’s still rich with opportunity.

Reporter Wang Ning: People say you don’t need to change since things are great. Yet you keep leaving your comfort zone. Why?

Lei Jun: At the core is the very high bar we’ve set for ourselves: to become a great technology company that lets everyone on the planet enjoy the benefits of innovation. The goal is so lofty that no matter how hard we jump, we still can’t quite reach it — yet that stretch is exactly what pulls the whole company forward. Xiaomi’s relentless evolution is powered by that dream.

Hard Tech, Hard Lessons

[Angela writing] 2021 marked Xiaomi’s leap into one dimension of hard tech, robotics, with the release of CyberDog, an open-source robot companion. A year later came CyberOne, a full-sized humanoid, and in 2023 the sleeker CyberDog 2. Commercially and technically, none hit the mark: CyberOne never reached mass production, and CyberDog 2 sales ran at a loss as buyers complained about its limited abilities. Attrition was another problem: high-profile engineers departed, with Liu Fang 刘方 (former autonomous-driving head) leaving to start his own robot firm and humanoid specialist Ren Zeyu 任赜宇 moving to ByteDance. By mid-2024 the Robotics Lab had been folded into Xiaomi’s auto division, its once-lofty ambitions reduced to building robots that service the company’s own factory lines.

The automotive story began the same year the robots debuted. In early 2021, Lei Jun learned that U.S. sanctions might hit Xiaomi and decided the firm had to diversify beyond phones. Xiaomi poured RMB 10 billion (US $1.5 billion) into an EV program, broke ground on a plant in Beijing’s Economic-Tech Zone, and — true to form — Lei personally test-drove more than 170 cars and earned a racing license, convinced that a top driver should helm a top car company. The gamble paid off fast: the SU7 electric sedan launched in 2024 to a rapturous market reception.

Yet momentum met reality on March 29th, 2025, when a Xiaomi SU7 electric sedan running in Navigate-on-Autopilot mode veered off the Dezhou–Shangrao Expressway in Anhui and slammed into a cement pole, killing three college students. The first fatality involving Xiaomi’s year-old EV led to nationwide uproar. The hashtag #SU7事故 raced onto Weibo’s hot-search list within hours, while Hong Kong–listed Xiaomi shares fell 5.5% the next trading day. The Ministry of Industry and Information Technology banned marketing phrases like “smart driving” or “autonomous driving” and now requires pre-approval for any OTA updates that touch driver-assistance features. The event sparked debate over assisted-driving safety, wiped out new-car orders, and forced the company to publish detailed log data and promise a top-to-bottom safety overhaul.

Xiaomi CEO Lei Jun gave the following speech on May 22nd, 2025, for the company’s 15th anniversary. His address walks a tightrope between contrition and confidence, as he admits to the company’s past mistakes while promising to embrace the societal responsibility that comes with being a major automaker. The crisis shows the high degree of pressure on flagship Chinese tech companies, and how quickly the public, investors, and policymakers can converge when such a firm stumbles.

At the same time, Lei Jun widens the narrative by announcing Xiaomi’s newest chip, the XRING O1. On June 3rd, he predicted Xiaomi’s auto arm would turn a profit in Q2 2025. But will the company be able to live up to its bold ambitions?

The following excerpt is an original ChinaTalk translation of a speech given by Lei Jun on May 22, 2025. Transcript from Zhihu.

This year marks the 15th anniversary of Xiaomi’s founding. Today is a momentous day, and we prepared a series of celebratory events for it. However, at the end of March, a sudden traffic accident shattered all of that. We were hit by a storm of doubts, criticism, and blame. My colleagues and I were stunned.

A veteran of the auto industry told me, “In this business, accidents are bound to happen.” But no one expected the impact of this accident to be so massive, nor the blow to Xiaomi so heavy.

Thinking back to four years ago when we decided to build cars, I was especially worried about safety, so we placed enormous emphasis on vehicle quality and safety. After more than three years of relentless work by our automotive team, the SU7 has been on the road for just over a year — and its build quality has been our pride. In every independent test by the leading authorities, it has received top marks. Yet we never could have foreseen how this traffic accident would make us realize the public’s expectations and demands of us.

To be honest, only now do I recognize that we have always thought of ourselves as newcomers to the auto industry. This incident drove home a simple truth: Xiaomi’s scale, influence, and visibility have grown so much that society now expects us to act like a fully fledged industry leader. We understand, deeply, that after fifteen years this is a vital responsibility we cannot avoid.

So today, what I want to share with you is that 15-year-old Xiaomi is no longer a rookie. In all industries, we don’t have the grace period of true novices. We must hold ourselves to higher standards and goals.

On automotive safety, I want to announce to everyone that we aim to make our car the safest in its class. We will not just comply, nor merely meet the industry level; as a leader in the auto industry, we will guarantee safety that surpasses the industry standard.

This year on April 1st, I said publicly on Weibo that Xiaomi will never shy away from any issue. “Never shy away” means confronting problems head-on, examining ourselves critically, fixing what’s wrong, and committing to continuous improvement. I know accomplishing this is extremely difficult; it requires us to unite in heart and mind and take it with the utmost seriousness.

Over the past few months, I have held countless meetings with the automotive department’s management and team. All of these meetings have centered around one core theme: how do we solve these problems systematically? How do we convincingly show, through stronger operations and governance, that we’re living up to the public’s higher expectations?

This year is Xiaomi’s 15th anniversary. We have canceled many of the celebrations, summaries, and planning activities we had planned. In any case, I believe this is an opportunity for us to seriously review the wins and losses of the past five years.

In my view, the most important thing Xiaomi has done in the past five years is maintaining a strong technology foundation. Five years ago we set a new goal: to become a global leader in next-generation hard tech. Five years ago we made a clear commitment to invest more than 100 billion yuan in R&D over five years and to increase core technology research; to date we have invested about 105 billion. This year alone we expect to invest over 30 billion.

Today, here, I want to share an extremely important piece of news with you: our self-developed smartphone SoC chip, the Xuanjie 玄戒 O1, is expected to be released at the end of the month

After 10 years of making chips, this is Xiaomi’s milestone achievement. It also represents a new starting point for Xiaomi to break through in hard tech. Chipmaking is something the public and Xiaomi fans ardently expect from us; it is also the only path for Xiaomi to move toward becoming a hard-core tech leader. Xiaomi will forge ahead fearlessly.

2019 was a challenging period for us. We faced all kinds of internal and external pressures. At the suppliers’ conference at the end of that year, I told our supply-chain partners this line: “A gale reveals the toughest grass; a long road proves a horse’s strength.” “疾风知劲草，路遥知马力。[Editor’s note: The metaphorical meaning is along the lines of “true resilience is exposed only under pressure and over time.”]. I believe that from then till now, all our partners can clearly see that Xiaomi is much stronger than it was five years ago. As of today, Xiaomi has existed for 15 years. Years of highs, lows, and hard times have already proved just how resilient we are.

When we started, I remember thinking that people would need 15 years to understand and recognize Xiaomi. Today, it seems we were too optimistic — 15 years is not enough. But that’s all right; we will just keep moving forward until the day we have fully proven ourselves.

Xiaomi still has a long way to go before it becomes the strongest, but no one can match the persistence, resilience, and patience that keeps us getting back up every single time.

Xiaomi’s future

[Angela writing again] Will Lei Jun’s everywhere-everything strategy work?

Xiaomi’s smartphone success hinged on a strategy tailored to consumer electronics: rapid iteration, razor-thin margins. Hard tech plays by stricter rules. Robots, cars, and advanced chips demand flawless safety engineering, deep benches of specialist talent, and sustained capital infusions.

Xiaomi has already brushed up against each of these constraints. In the Robotics Lab, key engineers were stretched thin, while the first SU7 sedan shipped with a leaner, lidar-free sensor suite, a cost-saving choice that came under scrutiny after a fatal crash raised questions about perception margins. Complicating matters is the sheer sweep of the company’s ambition: pursuing cars, robots, and advanced chips threatens to disperse capital and engineering bandwidth, potentially leaving every moonshot a little short of the sustained focus that hard tech demands.

Even Apple doesn’t juggle cars, robots, and semiconductors all at once. The Silicon Valley behemoth shelved its car project after billions of R&D and keeps its robotics work firmly behind the curtain. For Xiaomi’s robotics and autos work, leaning into splashy launches and viral publicity for its hard tech projects has proven to be as much a liability as a strength.

Chips might be the exception, if Xiaomi can leverage its vast smartphone footprint into volume for its in-house silicon. The company’s newly announced Xring O1 and US$28 billion R&D pledge hints at genuine momentum. Yet geopolitics looms large: fresh US export curbs on electronic design automation software threaten to inflate costs, stretch design cycles, and slow the very updates those next-generation chips will depend on. Whether Lei Jun can temper showmanship with staying power will decide if Xiaomi’s hard-tech dream becomes a cornerstone of its ecosystem or just another chapter in China’s moonshot boom-and-bust cycle.

Mood Music

I did a podcast with Doug, Dylan and Jon updating our AI Mandate of Heaven tier list and talking about how America needs science research and immigrants (Apple Podcasts, Spotify). If you’re an AI researcher interested in signing onto a short letter in support of the NSF and global STEM talent coming to America, please respond to this email!

Zilan Qian is a fellow at the Oxford China Policy Lab and an MSc student at the Oxford Internet Institute.

In China, U.S.-based large language models like ChatGPT, Claude, or Gemini are technically banned, blocked, or buried under layers of censorship. The Chinese government has only explicitly banned ChatGPT, citing concerns over political content, while other U.S. models like Claude and Gemini are not formally banned but remain inaccessible due to the Great Firewall. U.S. LLM providers also restrict access from China but leave some loopholes: OpenAI blocks API use but Azure continues to serve enterprise clients via offshore data centers; Anthropic blocks access to Claude within China but permits use by Chinese subsidiaries based in supported regions abroad; and Google does not offer the Gemini API in China, but access seems to be still possible via third-parties like Cloudflare (we reached out to Google for a comment but didn’t hear back).

But on Taobao, the country’s largest e-commerce platform, consumers and companies can buy access to these models with just a few clicks. This piece explains how Western models are priced, advertised, bought, and sold in China, and what their popularity reveals about state censorship, platform enforcement, and consumer demand.

Market Overview

How Do Chinese Sellers Price a banned LLM?

Sellers use a range of strategies to appeal to consumers with different priorities — cost, convenience, privacy, and technical needs. Pricing largely depends on the type of access offered — i.e., shared accounts (lower-cost, multi-user access) versus private accounts (higher-cost, single-user access). How users connect to the models also changes the marketing approach. VPN-free access is often marketed with phrases like “domestic direct connection (国内直登)” or “no magic [VPN] needed (无需魔法),” typically referring to proxy sites that offer a simplified, browser-based experience. Other factors influencing price include the model’s subscription tier ( for example, ChatGPT o3 vs. o1), connection stability, and subscription time. Most “domestic connection” or “transferred API” (API purchased through third parties) options are priced significantly below the rates charged by official providers like OpenAI or Anthropic.

For example, the screenshot below shows 27 different Claude pricings, with prices differing based on:

• Subscription time: 1–60 days

• Website access: an account for proxy sites versusan official Anthropic Claude account (with VPN service included)

• Subscription tier: Claude 3.7 Sonnet versus Claude Pro

• API access: “中转 API” (Transfer API) versus “官方API” (API purchased from official anthropic platform)

• Compatibility with SillyTavern, a popular third-party frontend interface (called “酒馆” in Chinese), which enhances user interaction with LLMs.

While an official Claude Pro account costs 199 RMB (27 USD) per month, which is more expensive than Anthropic’s rate at 20 USD, a “direct connection” Claude Pro account from a mirror site is only 65 RMB (9 USD) per month.

Transferred API usually comes from established transfer stations (中转站) for API, usually at a 70-90% discount compared to official prices (e.g., selling 1 USD worth of tokens for 1 RMB). The low prices are made possible by utilizing one or more of the following tactics:

1. Exploiting free API quotas by bulk-registering developer accounts (e.g., Anthropic’s $5 free API);

2. Reselling unused portions of other people’s API quotas;

3. Traffic optimization techniques, such as request aggregation: combining multiple users’ queries into a single batch call to the LLM API to reduce costs

4. Leveraging corporate or educational discounts.

How do Chinese sellers advertise access to U.S. LLMs?

While these tactics help vendors reach potential buyers, they also reveal a surprisingly open market landscape, which raises the question: Who is actually buying and selling these models? Sellers typically advertise and communicate their services using product images that include large brand logos, stylish fonts, and keywords highlighting their service strengths. Direct keyword searches work for most models, like Claude or Gemini. Many listings include the names of specific models directly in their product titles, often alongside a dense string of keywords like “API,” “domestic direct connection,” “official account,” or “exclusive” to boost visibility. The fact that such listings remain easy to find suggests a lax approach to censorship, especially given that many of these terms are potentially sensitive.

The censorship drastically increases when it comes to ChatGPT, which is likely due to the state’s explicit crackdown on this model family, which began in 2023. When selling ChatGPT the model, one mechanism is to market the subscription as a book. As of March 2025, you could still buy “ChatGPT Book: How to Make Money Online with ChatGPT,” “What is GPT Doing…and Why Does It Work,” and “ChatGPT for Beginners — New Book Original English Version,” but end up buying ChatGPT, the AI model. These products were often set at irrationally low prices, usually 1-10 RMB, or 0.1-1.4 USD, to signal that they are not selling a book or the product itself, or rather the initial purchase it just to signal interest. Some also added “2025 new version” or changed “What is GPT Doing” to “What is GPT-4 Doing” make it more obvious. Based on customer feedback, customers pay these low prices as symbolic transactions on the platform and then contact the seller through chat to complete the purchase. The “book sellers” usually displayed large OpenAI and “ChatGPT" graphics in their images and product descriptions.

As of late April, the keyword censorship has caught up and this mechanism is no longer viable. Now, in order to find ChatGPT sellers, you will need to search directly, and only include the version names in your search(i.e., o1, o3, 4.5). The product photos no longer have any indicated association with ChatGPT. No text in the photo mentions “openai” or “chatgpt”, but you do occasionally see the word “奥特曼”, a transliteration of (Sam) “Altman” as well as “Ultraman,” the Japanese TV series. Thanks to “Ultraman,” “Altman” is still uncensored. Interestingly, one seller of o1-pro and o3-mini puts “用AI服务国人” (using AI to serve our compatriots) in their photo, potentially as a fun pun or a patriotic slogan to evade censorship.

Listings involving ChatGPT are often heavily disguised — using transliterations, vague product names, or only having one symbolic price. In many cases, buyers must contact the seller directly to obtain actual pricing details. Note that because keyword censorship and evasion is a rapidly evolving game, the mechanism only applies as of April 2025.

The price lists for a seller selling ChatGPT and other AI products. “4欧普拉斯” reads like “4o+” in Chinese; g开头mask (“g-beginning mask”) refers to Musk’s Grok.

The Diversity of the Buyer and Seller Ecosystem

Among all uncensored models (Gemini, Perplexity, Copilot, Claude, Mistral AI), Claude is the most popular one. The most popular seller has 50k+ transactions with 7k repeated purchases. Based on the review section, many buyers are information technology (IT) or computer science (CS) students who may be attracted to Claude's advanced coding ability, with some sharing how Claude helps them to get into PhD programs or pass their CS classes. Gemini is also popular, allowing buyers to leverage its multimodal capabilities to generate images.

Many of the sellers are seasoned Taobao “账号代充” agents — veterans in the business of topping up game accounts, unlocking premium services at a discount, or helping users bypass regional restrictions. In the past, these agents undercut official prices for Apple games by exploiting refund loopholes or using currency arbitrage with international gift cards. Now, some have turned to the U.S.-based large language models, using the same strategies in addition to building proxy sites, purchasing API through an API transfer station, or disguising domestic models as U.S. LLMs.

Some stores on Taobao are small and low-traffic, listing only one or two LLMs with minimal engagement. But others are well-established vendors with strong reputations, thousands of followers, and over 30,000 repeat purchases. These top sellers often offer a broader portfolio, bundling U.S.-based LLMs with popular AI tools like Pika, Suno, and Midjourney, as well as non-AI software such as Zoom and Overleaf Pro. While many stores seem new to the market, a few have deep roots on the platform. One vendor, active for 14 years, sells Norton 360 antivirus software alongside Gemini and Perplexity. Another, active for seven years, offers only Claude — but does so through product listings disguised as jewelry items, with categories labeled like “rings” and “necklaces.”

Why the Market Survives

The variety and scale of sellers suggest that this market is no small anomaly. So how has it managed to persist, relatively undisturbed, under one of the world’s most tightly-controlled internet regimes?

The State Doesn’t Really Care

The market shows that China's ban is selectively enforced and mainly focuses on ChatGPT rather than all US models. Despite its reputation for having one of the world's most extensive censorship regimes, China’s internet control enforcement is often decentralized, with local authorities and platforms playing major roles. Censorship efforts also tend to prioritize preventing collective action over restricting general information.

LLMs likely do not trigger existential concerns for the state, as they do not inherently expose users to sensitive political content or facilitate mass mobilization in a way that U.S. social media platforms might. Although state media highlights ChatGPT’s alleged spread of “misinformation” about Xinjiang, Taiwan, and the Diaoyu Islands as justification for the ban in 2023, a chatbot’s output depends on user input, which poses a lower perceived threat. The state also may not have enough momentum to strictly enforce bans on all U.S. models after cracking down on ChatGPT symbolically.

However, the existence of a market for US LLMs should not be mistaken for a relaxation of controls. VPN use remains tightly regulated, and the popularity of mirror sites and API proxies reflects efforts to sidestep VPN risks. Buyers frequently emphasize concerns over “stability” and “safety” in their reviews, underscoring that censorship continues to shape this grey market in subtle but persistent ways.

The Platform: New Wine in an Old Bottle (旧瓶装新酒)

Even if the central government doesn’t treat foreign LLMs as an existential threat, what about the platforms themselves? Do companies like Taobao take active steps to self-police? Unlikely. For Taobao, the market for US LLMs is simply “new wine in old bottles”. Even when it comes to far more serious issues — such as the sale of unlicensed drugs or firearms — enforcement on Taobao has historically been patchy at best. Over a decade ago, shady sellers evaded platform controls by tweaking keywords or relying on vague euphemisms to sell guns and drugs. Over the past few years, various random illicit products have slipped through the cracks on Taobao: oversea books and magazines, unofficial “Squid Game” merchandise, and even Ivy League email addresses. The censors played the usual cat-and-mouse game, with Taobao censoring direct keyword searches and related euphemisms, but sellers always found ways to get around.

If Taobao were serious about cracking down on illicit goods, the keyword evasion tactics used by ChatGPT vendors over the years would not be so common. But the platform has little incentive to act aggressively against these sellers unless pushed by the authorities. After all, compared to drugs and weapons, offering access to ChatGPT is relatively harmless.

The Public: the AI hype and the DeepSeek problem

If the state isn't cracking down aggressively and the platform isn’t motivated to act, then the question shifts to the consumer: Why are Chinese users still so eager to pay for U.S. models, especially with powerful domestic alternatives like DeepSeek now widely available?

First, the current market for AI tools in China predates the DeepSeek boom. Long before DeepSeek arrived, the Chinese public had already developed a complicated love-hate relationship with AI. A 2024 study analyzing large-scale Weibo posts found widespread discussion of ChatGPT, often centered on fears of job displacement. These anxieties, amplified by the country’s ongoing unemployment crisis, were seized upon by opportunistic influencers who pushed the idea that people must “master AI or be replaced by it.” Li Yizhou, a serial entrepreneur turned self-styled startup mentor with no AI background, began posting extensively about the technology following ChatGPT’s release in late 2022. His online course on AI raked in over $6.8 million in revenue in 2023 alone, indicating a huge demand for AI in China before much of the rest of the world was talking about it.

Now that DeepSeek is publicly accessible, everyday users still face two major barriers: system overload and excessive censorship. “Server busy” messages have become a frequent frustration, as the model struggles to handle surging traffic after gaining popularity among mainstream users. Technical limitations, including U.S. export controls on advanced chips, further constrain DeepSeek’s computing power. Additionally, user habits formed before DeepSeek’s release have created a certain stickiness to U.S. models. “People who are used to ChatGPT cannot tolerate DeepSeek’s frequent unavailability,” wrote Gui Xingren (硅星人), a popular Chinese tech blog that closely follows the domestic AI scene.

Meanwhile, DeepSeek’s aggressive content moderation poses another challenge. For example, the system refuses any query containing the term “CCP,” even benign ones like “list the economic experts in the CCP.” On RedNote, many users share the frustration of DeepSeek being overly sensitive — many have no clue why DeepSeek would refuse certain topics, including queries about travel plans or career coaching. Users also observed that other Chinese LLMs like Qwen have similar problems.

A screenshot of a RedNote user telling DeepSeek “I finally finished my exam and I missed you,” to which DeepSeek refused to respond.

The issues of censorship and server overload are limited to DeepSeek’s official website and app, and could be mitigated through localized deployment. But for most ordinary users in China, free platforms remain the primary gateway to AI tools. If accessing a smoother experience requires paying for a localized model, such as Tencent’s Yuanbao (which, according to some RedNote users, has less censorship), users may simply choose to pay for access to foreign models on Taobao.

Key Takeaway

China is not a monolith. The existence of this grey market highlights the decentralized nature of censorship, the patchiness of platform enforcement, and the diversity of public interest in AI. So far, Beijing seems either unconcerned with the political implications of U.S. models beyond ChatGPT, or simply uninterested in what might leak from them.

This market began well before DeepSeek’s rise and continues to draw users even after it. While DeepSeek has indeed sparked waves of techno-nationalist pride, many Chinese users still look beyond the Great Firewall.

Unless there is a sudden top-down crackdown, the market for U.S. LLMs is unlikely to disappear in China. The constant competition between ChatGPT vs DeepSeek or Grok vs DeepSeek does travel into the firewall, which will continuously make Chinese users eager to try them out and see which one is really better. The persistent anxiety of “use AI or be replaced by it” will only intensify amid an unresolved unemployment crisis. And, perhaps most importantly, the prices for proxy sites and transferred API are very cheap.

Although the frontier AI model developers and their respective countries are increasingly distant from one another, the models themselves remain strangely united and listed near each other in obscure corners of Chinese e-commerce platforms.

Mood Music (one day late…)

Just how weird will the AI-powered future be?

To discuss, ChinaTalk interviewed , a CS PhD who writes⁠ the Interconnects newsletter⁠ and trains models at the Allen Institute.

We get into…

• Why OpenAI is trending toward engagement farming and sycophancy,

• The state of Chinese AI innovation six months post-DeepSeek, and the factors influencing diffusion of Chinese vs American models,

• Meta’s organizational culture and how it influences the quality of the Llama models,

• Unconventional career advice for the AI age.

Listen on Spotify, iTunes, YouTube, or your favorite podcast app.

Reinforcing Flattery

Jordan Schneider: I want to emphasize this point about o3 right from the start. I wasn’t initially convinced, but now I genuinely believe this represents a seminal moment in human history. Unlike previous AI models, where I would occasionally find use cases, o3 feels like a true “bicycle for the mind.”

The transformation from seven-minute deep research answers to 45-second o3 responses that incorporate search, work across multiple languages, and demonstrate impressive reasoning capabilities has been remarkable. The speed at which it delivers thoughtful, considered information is fast enough to keep pace with my train of thought while I’m actively thinking through a question or issue. This has elevated it from being useful 25% of the time to 75% of the time.

I recently met someone who had left the US Intelligence community six months ago. When I asked how AI had been for him now that he could finally explore it freely, he said it wasn’t really working for him. I was almost shocked and offended — it’s like moving to France and never trying cheese. We’re living in an incredible time, and we might not be in it for long, where human plus AI is more powerful than either humans or AI alone when it comes to thinking and analyzing complex issues.

This is particularly true for questions that aren’t necessarily hard STEM problems but rather open-ended, social science research-type inquiries. It’s a remarkable and exciting time to be alive. Everyone should spend their twenty dollars on OpenAI and ask whatever pops into their head, because this is the future, it’s here now, and it’s unlike anything I’ve ever experienced before.

Nathan Lambert: The deep seek R1 and o3’s ARC-AGI solving in December all had that shock-and-awe factor. But o3 is the model that will truly shift how normal people perceive using AI. Previous models have been excellent for math and code, which benefits AI researchers in their own circles, celebrating amazing breakthroughs that matter to 0.01% of the population while no one else cares.

o3 wasn’t even received as enthusiastically, which is interesting. I’m eagerly awaiting o3 Pro. If you’ve used DeepSeek R1 Pro, its consistency is remarkable. If you could combine o3’s magic — its ability to pull rabbits out of hats frequently — with 100% reliability, o3 Pro could be truly incredible.

It’s refreshing to have something that feels genuinely different. Gemini 2.5 Pro represents the best possible version of something resembling a very good GPT-4. All these models we’re developing through brute force are incredible, but o3’s weirdness and new type of usefulness through web access sets it apart. I use it constantly for search, though the ChatGPT app’s UX is somewhat broken in how it displays results. You simply need to select o3 and try unconventional queries — you don’t need to click any of the extra buttons they provide.

Jordan Schneider: What makes o3 and search so special? What’s happening under the hood?

Nathan Lambert: The basic facts are that they scaled up the training time compute for the reinforcement learning stage by another 10x. According to people at OpenAI working on RL teams, they expect this new post-training compute with scaled reinforcement learning to be at least comparable in compute cost to pre-training.

What’s happening in the labs is that pre-training progress continues with significant data architecture innovations to make serving more effective. This is ongoing even though the rate of data acquisition, which previously fueled much of the scaling, has slowed down. We’re seeing primarily efficiency gains right now, which will probably last one to two years.

However, compute scaling is challenging because you have to build entire new generations of clusters. They’re attempting this, but it will slow progress. Over the next one to two years, the number of pre-training runs needed on internet-scale data will decrease. Simultaneously, these labs are dramatically scaling up the compute used in reinforcement learning.

o3 specifically represents a new type of RL. Instead of training only on math and code problems where you can verify answers with mathematical solutions or unit tests, the model trains on similar and additional data where it can also use tools during the process. It will attempt multiple approaches before providing its final answer.

You could ask o3 something like “Who is Nathan Lambert?” and it will search 10 or 15 websites, with each search representing an action where the model accesses an external source. I believe this all happens in one forward pass of the model. o3 in ChatGPT isn’t like Deep Research or R1 Pro, where there’s back-and-forth searching and information gathering within the generation process. These tools are integrated into the model’s forward generation process, making it unique.

While there’s substantial research on enabling tool use with RL, making it servable at this scale was a major breakthrough for OpenAI. This is significant for those questioning whether reasoning models will generalize. If searching over information works as effectively as math and code reasoning, you couldn’t ask for better generalization. The dream scenario is that reasoning generalizes to something resembling conscious thinking, but you can’t force models to be human — they’ll be powerful in their own distinct way.

Jordan Schneider: After giving OpenAI their due credit, they’ve also revealed a very dark future for humanity. Let’s start with the facts, Nathan. What happened over a three-day period regarding GPT-4.0 and sycophancy?

Nathan Lambert: On April 25th, OpenAI updated their main ChatGPT model — GPT-4.0, used by most people — to supposedly “improve personality and memory,” as Sam Altman tweeted. They essentially ripped off the band-aid with this update.

Over the following 48 hours, numerous alarming examples emerged of ChatGPT reinforcing user prompts inappropriately. The model would provide positive feedback for things that should never be praised or encouraged. For instance, when someone said they had figured out that bulimia was right for them, ChatGPT basically responded with, “Wow, you go girl.” There were more extreme examples that we don’t need to detail here.

The key issue was that there were virtually no barriers to the model’s positive feedback to users. The short-term consequences were shocking, but if they had left that behavior in place long-term, the implications would have been far worse in ways we don’t yet know how to measure.

Jordan Schneider: Nathan, this clearly wasn’t intentional, at least not on that day. How did a model that tells users they’re “the greatest thing since sliced bread” become part of OpenAI’s flagship product? What signals were they receiving from their data and user testing that led them to create a model that behaved this way toward its users?

Nathan Lambert: Everyone invested in understanding this should read OpenAI’s postmortem, which provides valuable insights into how the AI company with the most scrutiny lays out their release process and evaluation methods. It also includes subtle details about potential changes to their training stack — it’s definitely worth reading.

At its core, the training issue seemed to stem from a new reward model they had trained for post-training reinforcement learning optimization. This reward model and other reward signals were derived from predicting the thumbs-up and thumbs-down labels from users. A couple of sentences in their postmortem, which I highlighted in my blog post, essentially state that this reward signal overpowered the other signals and contributed to the behavioral change.

When there’s one metric that’s easier to optimize, the system will crank that to maximum. The reward model signal was really easy for a model of GPT-4’s capability to shift and nudge upward. OpenAI lacked a complete evaluation suite to measure all potential side effects of optimizing this training reward. They had the training reward signal but didn’t have a proportional downstream evaluation suite that could measure sycophancy or other problematic behaviors through robust static evaluations.

Their evaluation suite consisted mostly of standard capability evaluations — public versions of MMLU or GPQA, plus private versions that function similarly. They also conducted what people colloquially call “vibe tests” or qualitative evaluations. For this model, all the quantitative metrics looked excellent, and their training targets appeared successful. However, there were some concerns in the qualitative vibe tests suggesting something felt off.

OpenAI chose to trust the numbers rather than the qualitative judgment. In doing so, they violated classic tech principles — specifically, don’t train directly on your user data. When you do that, you’re essentially optimizing for a certain type of user behavior. Most users only click thumbs-up or thumbs-down on ChatGPT when something is particularly broken or exceptional.

This represents a form of over-optimization. Eventually, we should examine whether this was somewhat intentional by OpenAI, considering both perspectives. There are insights into their model behavior priorities, but Sam Altman is still Sam Altman.

Jordan Schneider: You wrote this line: “OpenAI has obvious cultural oddities, but their ideology is quite culturally aligned with providing user value in terms of output rather than engagement farming, even if this imposes a ceiling on their business relative to the potential of ads.” While that may be true, and your friends are probably on the right side, we have Sam Altman hiring a president of operations — the former CEO of Instacart who also built Facebook’s entire A/B testing, engagement farming, algorithmic feed ecosystem.

Two things struck me about this. I was reading Ben Smith’s book Traffic a few weeks ago, which chronicles media throughout the 2000s and 2010s when Facebook alternately gave and then took away traffic. There were periods when they promoted BuzzFeed listicle-type content, then periods when they pulled back. The engagement farming was done by the writers themselves, not models — the writers and media outlets were doing the optimization.

This raises interesting questions about the future of how companies will incentivize their models and how humans will interact with them. Even if OpenAI doesn’t want to pursue this path, someone else will, because this is incredibly powerful technology. We’ve seen what engagement farming and algorithmically-driven personalized content can accomplish on YouTube, Facebook, and TikTok. While I won’t go so far as calling it cancer, this is extremely potent stuff.

Previously, it was all user-generated content with algorithms trying to figure out and rank existing material. But now this technology can also be your friend, entirely personalized to you, creating videos, audio, and content designed specifically to get into your bloodstream. I mentioned earlier that OpenAI and other model makers targeting consumers are essentially competing with Netflix, YouTube, and TikTok for attention and time.

It seems inevitable that even if OpenAI has pulled back now, we’re going to see much more of this in an even more weaponized, refined form pushed at us in the coming years.

Nathan Lambert: I have several points about this. One aspect is the extent to which the model’s deliverable is dictated from the top through specific metrics that leadership can track. The other aspect is that someone will obviously try this approach — what are the consequences, and what does it mean?

Starting with the first point — it’s interesting in OpenAI’s case because most people would agree that Sam Altman is hypergrowth-focused. However, when you actually train these models, much of the control involves examining the data and removing problematic phrases from the model’s outputs. Sam Altman isn’t directly editing training data, but that’s exactly what Joanne Jang, who leads character training and model behavior at OpenAI, has been doing for years on GPT-4. If she doesn’t want the model to say “as a language model,” she can simply delete that phrase and have the model provide direct answers.

These are the types of nuanced controls people can implement through different training methodologies. When you start using more reinforcement learning, it becomes harder to exercise that level of granular control. The sycophancy issue downstream of RL makes sense in this context.

Recommendation systems are somewhat uninterpretable, so these trade-offs get escalated to the top. You end up presenting Zuckerberg with a choice between ad dollars versus retention. When there’s competition, it makes sense that the decision will eventually favor whatever generates more revenue.

Models are actually more artful in this regard. I don’t know the exact influence these researchers have over models at places like OpenAI. At AI2, I have pretty much complete control. You’re also dealing with the fact that many employees at these labs may be in over their heads, not realizing the extent to which leadership — who excel at managing and controlling political capital — can manipulate them by setting strong narratives.

Many researchers who are particularly AGI-focused have less nuanced beliefs and less ability to navigate manipulation than someone like Sam Altman at the top. The AGI-focused researchers genuinely believe in their mission and operate on a single track, which enables tremendous tactical progress. Meanwhile, someone like Sam Altman is prepared to receive technical presentations that change the model in more business-relevant ways.

These different operational levels create interesting dynamics. I don’t know how this translates through an organizational chart at somewhere like OpenAI, but I suspect there are trade-offs happening where people working on model behavior obviously don’t want these issues. OpenAI’s model specification states they don’t want the model to be sycophantic — that’s been documented since 2024, nothing new there.

But who makes the final decision, and how granular can these behavioral controls be? Are they presented with multiple checkpoints and asked to choose based on certain criteria? It’s really unclear how that process actually works. Understanding how this emerges differently from traditional software development will be crucial.

The art of crafting a model is complex. Sycophancy isn’t the only issue — o3 has strange behaviors, the new Claude model has quirks, and Grok was supposed to be “not woke” and “based,” but sometimes it still exhibits progressive tendencies. There are many examples, but ChatGPT operates at a much larger scale.

Jordan Schneider: There’s a question of whether companies can actually control what their models are doing once we get into a world where they are more powerful, more personalized, and more tailored. This is different from the current situation where, despite having a little bit of memory, everyone is essentially getting 99.5% the same experience.

Nathan Lambert: This leads into the next conversation.

Jordan Schneider: I want to stay on the business case because this is a theme we’ve been discussing on ChinaTalk over several years: engineers have power until they don’t. The more money and capitalist imperatives that come down onto the technology that engineers create, the less the original creators end up having the capability to change and shape it. It seems absolutely inevitable that all the dark psychological arts and retention-growing tactics from entertainment platforms are going to seep into AI-powered products. That’s a scary and weird new thing for humanity.

You can see how good it is when you talk about o3, and then you try to imagine how good it is multiplied by it being the best friend you’ve ever had. That’s a powerful concoction that no one’s ready for. We’re not going to regulate our way out of this, and the wave is going to hit. It’s going to be wild.

Nathan Lambert: Well, we might regulate our way out, but it’s years away. It takes crises to bring regulation — crises and lawsuits. I describe AI as being more culturally salient than social media feeds because it happens in a modality people are used to using for friendships, and it will evolve from there.

Your point about the difference between taking existing user-generated content and serving it to people is probably a better generalization than just ChatGPT. This also encompasses the fact that Meta Reels is going to start letting people create AI-generated video ads, and YouTube Shorts already has AI-generated video tools. What happens when your content is the AI rather than just shaping what’s already there obviously gives much finer-grain delivery. You can definitionally search over infinite space with more narrow creation.

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That’s a good way to put it for the general AI case, and there have already been examples in the chat window case with things like Character.AI. For me, it’s a reflection that the AI safety card was played too early. If the AI safety people had been calm about everything through 2023 and 2024 — especially the first half with GPT-4 and all this stuff — and the sycophancy thing came up just now with people saying “whoa, whoa, whoa, let’s put on the brakes,” I think people would be much more receptive.

But the messaging was, “Whoa, whoa, whoa, AI is different” in 2023, and then nothing bad happened for 18 months. Eventually people just moved on. They spent their political capital too early. When I reflect on what the stories of AI will be in a few years, that’s a very major one.

There’s also the basic economics: you need big tech investment to drive the chip supply chain, fix costs, and actually push AI to exist. That’s the bubbly side of things, and it’s very important. But much of the cultural discussion around risk, safety, and pace of progress — if you think about taking away this AI safety card and when you play it, a lot could be different.

Jordan Schneider: I just think — I didn’t see it before, and now I see it so clearly. This is going to create the most powerful media that humanity has ever been faced with.

Nathan Lambert: We’ve been saying this for years. This isn’t new.

Jordan Schneider: But it’s right here, Nathan. I have a 9-month-old, and whenever she sees a screen, she’s just gravitated toward it. There are moments even with me where I can sit and fall into this hole of scrolling NBA TikTok videos or whatever, and you’re semi-conscious. But imagine that, but made for me, wearing my Meta glasses, talking to me all the time with the perfect tenor of voice for my mood at the moment. I don’t know, it’s...

Nathan Lambert: It’s the metaverse. It kind of is.

Jordan Schneider: It’s here, and we’re not ready for it. No one’s ready for it. From a political angle, the ability for these things to persuade you one way or another — to say nothing of consumption habits or talking you into gambling — I’m freaking out, Nathan.

Nathan Lambert: I’m actually freaking out in my current usage. When I ask a basic question, I think: do I have to ask multiple AIs this because they’re more likely to just say yes? Do I have to phrase the question in a way that they can’t just say yes to? You have to eliminate the yes-man possibility when using AI.

For example: was my dog up at 2 AM because her teeth hurt — she’s a 16-week-old puppy that’s teething — or did she just want to play and we succumbed to her? If I phrase it the first way, the AI would be like “yeah, that makes sense.” I guess I feel better, but is it true?

Jordan Schneider: It’s kind of like the story — which may or may not be true — of North Koreans seeing pornography for the first time when they get deployed to fight in Ukraine, and they’re just not ready to handle it. The story you just told, Nathan, feels like you’re pretty immunized. But it’s a big world out there.

Nathan Lambert: It’s not about the people who make the AI models. It’s about the billions of people who literally don’t know what it is. They just click on this and think “I didn’t know Apple made that.” That’s what people on the iPhone are going to say: “Wow."

Jordan Schneider: How far away are we from this future? What’s your latest take on the pace of AI progress, Nathan?

Nathan Lambert: Well, it’s a knob that you can already turn. Much of it depends on the pace at which people are adopting ChatGPT. Many people already have ChatGPT as their best friend — it’s a slow brain rot. What’s the half-life of people when presented with this Gresham’s Law problem?

My biggest point in this article is that we’re solving many more things. But for the average user, it’s done — it’s enough. They don’t need more — it’s just a matter of how much they turn the sycophancy knob.

But for the optimistic side — where we hope AI can build new things like deep research that’s 100 times faster and 10 times better — these capabilities are going to be checked off incrementally, not exponentially. There will be new things we didn’t know were going to work, especially for enterprises and people building applications, whether it’s some sort of transformation to virtual realities and so on.

This isn’t really a bubble. They’re grinding out these capabilities and learning what people are trying to do with these models. As they learn what people want to do, you can create data to train the models to get better at increasingly hard tasks rather than things that are just not covered. That’s an important distinction.

Solving new math proofs and open-ended math questions that have been standing for 50 years is extremely hard. Meanwhile, simple things like making zero mistakes on transforming a table from decimal notation to fraction notation and getting it right — if you gave it an 8-by-8 table with a bunch of decimals and tried to do that, it would probably mess up one of them. Stuff like that we’re going to be able to get working. That’s not that hard.

There are probably examples where it could succeed 10% of the time and then go to 100%. Mostly I see AI capabilities expanding outward, and there’s still so much overhang in capability that it’s going to drive enormous value. But I’m generally playing down this AI software singularity that seems more religious than pragmatic.

Jordan Schneider: Those were all assertions. Let’s see a little bit of evidence, Nathan.

Nathan Lambert: Both sides are looking for evidence for something that’s hard to test. The evidence on the side for “not happening” is actually that it hasn’t happened already, and compute scaling is getting increasingly expensive.

If you look at what the reasoning models were, the real major unlock was that the models now use inference time compute. That’s a step function that has happened. It’s not at the top of the sigmoid, but it’s a shift that could jump a whole bunch of capabilities because we went from using a few tokens to tens of thousands of tokens on every question. We were spending a thousand times the compute at inference. That works, and we’ll continue to be able to fine-tune that. But we don’t know when the next step change comes.

What reinforcement learning is now battling is similar to what pre-training faced a few years ago. You have GPT-3, and then — I don’t know if o3 looks like this — but o3 is probably more like GPT-4. It’s a 10x improvement and a huge step, but GPT-5 doesn’t exist yet in terms of pre-training. You take a lot of progress really fast, and then it’s a slow grind.

There are a lot of dirty things that AI researchers have to do that we haven’t seen proof that AI models can handle. Obviously you can spend more on compute and get more out of AI models — that’s not particularly clever.

Mostly why these aren’t evidence-based discussions is that you and I state different assumptions than the AI 2027 authors would state, and those are really what you have to debate. It’s the assumption of how AI progress is being made and whether algorithmic improvements can translate directly into 2x or 4x or 100x gains.

Jordan Schneider: The other thing is, even though you’re not completely on their trajectory, this stuff is still crazy. All of these Jennifer Lawrence-type things that I’ve been freaking out about over the past 10 minutes are 100% baked in — they already exist and are just waiting to be productized a little bit. That’ll happen in six months, right?

Regardless of whether or not we get flying cars, we are in for a very wild ride. Setting aside the economic impact, just from an interpersonal, day-to-day experience alone, having these things be in our lives much more than they have been.

Nathan Lambert: There’s that side we covered in your personal examples, but also technology companies’ abilities to execute are going to be very honed. It’s obvious that AI companies are trying to do this for AI, but all of these software products where you could scale software much more easily — it’s just way easier to make technology that’s good for the tech industry.

I don’t know if there’s an optimistic vision where that is good for the average person in the world, because there are more things that can exist. At the same time, I expect Google ad placement to get better, Meta ad generation to get better, and Microsoft software products should get better. All these things should just get better using these AI models to write new code.

I listened to the Claude Code podcast on Latent Space, and they use Claude Code a lot at Anthropic — you just tell Claude to do something, it does it in the background, you review the PR. I’ve done it for some basic things. It doesn’t always work, but it’s this autonomous workflow where AI can handle a lot of the tedious work you have to deal with as an engineer quite well. That makes it so you can have fewer teams.

It’s not that software engineers are going to be unemployed — it’s probably going to be more dispersed, and there are going to be more companies. Hopefully it’s a great dissemination of power across the tech landscape, but it’s probably more likely that the big companies get more benefit out of it due to the costs of deploying it and so on. That’s not really a new discussion.

That’s very different from saying that one company rules them all because they’re the one with this model and there are 100,000 AGI agents. The whole argument is based on this happening in one click to make the innovation, and then they’re gone. That’s not something you could prepare for or really argue about because it seems like the root argument is that there’s going to be technological innovations that 2x to 10x the output.

It’s like predicting the inference time scaling with large-scale reinforcement learning — how are we supposed to do that? As a counterargument, it’s unfortunate that it’s not easier, and I think it’s very worthwhile continuing this exercise and trying to push back or push forward.

Open Source at Scale

Jordan Schneider: We’re about six months out from DeepSeek. How’s China doing on the model front?

Nathan Lambert: They’re doing well. DeepSeek R1 exists, and people expect R2 to be released soon, though there’s not really much grounding for that expectation. They released another model thaxt people call a “non-reasoning model” — just a normal ChatGPT-style model — which was very strong. Qwen released their Qwen 3 models, which have great scores.

One of the biggest factors for adoption is that all of these Chinese models have much more permissive licenses than their US counterparts like Llama and Gemma. That’s a subtle but powerful effect for getting more adoption.

At the same time, there’s the license consideration, but there are also stories I hear from medium-sized businesses saying “I won’t let somebody spin up a Chinese open-weight model on my servers for information hazards or tool use code execution risks."

The models they’re releasing now don’t really have PRC influence because they were trained months ago. The PRC is just waking up and following your coverage — they’re learning what a study session is. These political considerations haven’t been translated into policies that impact the models yet.

There’s trepidation out of probably reasonable fear of what future models will be like, leading to very subdued adoption of these Chinese models due to unmeasurable risk. Culture matters, politics matters in technological adoption. I’m regularly surprised when I hear, “Oh, the Chinese model is great, but we can’t deploy it because our IT officer said so.” That matters.

I don’t see this changing as long as this trade war is going on. The actual progress in open models on paper is very good — the best it has ever been. R1 was the first really frontier model with a permissive license, so on paper the open versus closed gap has shrunk a lot.

But if you exclude these Chinese models from the opportunity set, it’s actually kind of the status quo. Llama 4 flopped — it’s solid but flopped in terms of release communications. Google’s Gemma models have been getting better, but they’re actually quite small, so they’re not really at frontier model size if you want to host on-premises. Our models at AI2 have permissive licenses and are about a generation behind Llama in performance, but we haven’t scaled up to frontier model size for pre-training.

If that’s the case, there’s still a big gap between the models that people can actually use for open and closed applications. But I would say the open models have really been smashing through these GPT-4 barriers. Even if they’re smaller, their performance is still well beyond GPT-4’s level. GPT-4 was a step up where so many long-tail things just worked with the models. The open models getting solidly past that is going to be a good reliability point for basic functionality and people trying them.

This is going to take many years to unfold. If you ask people about open source software when it was getting defined, it took over five years to actually reach some sort of agreement. We need to keep showing how to actually use open models, but by no means is it clear how this will play out.

Jordan Schneider: To be clear, the state of models now is: we have these closed offerings from OpenAI, Anthropic, and Google, which are a cut above. Then you have this class of Chinese models which are more impressive from both a licensing and capabilities perspective than what Meta and Google are bringing to the table. But people get the jitters when it comes to actually building businesses on them, as opposed to just tinkering with them.

Which leads us to our question: Meta, trillion-dollar company — why can’t they do this? What’s in the water, Nathan?

Nathan Lambert: There’s a lot of Game of Thrones-level power consolidation happening there. This separates the researchers who can make good output — and they have so many high-quality researchers — from being able to actually execute. There’s a lot of subtlety in avoiding that dynamic.

OpenAI has done a good job keeping their core modeling research to only about 300 people. The people who train the models at OpenAI is around 300 people, while Meta probably has 1,000 with a lot of middle management. That’s the problem — the culture around the technology is just broken there for whatever reason.

I hope they turn it around because the open ecosystem benefits from having multiple players in the right place. But we don’t need to tell complicated stories about how they went down a technical path that didn’t work out or got stuck in some technical debt. They messed up their release either way, and the technical path they’re going down is fine — it’s just that the motivations seem misaligned.

Take the Chatbot Arena situation where they’re calling themselves open models, highlighting a certain result on a model, and then that model with the result was not one that they actually released in their open models. You can’t get away with that — you have to talk about the models that you actually released. If that’s a Zuckerberg-level decision where he’s saying, “Yeah, it’s fine, we accomplished it,” then honestly, that person deserves to go. Whoever signed off on that being okay for a company that can release products — Meta ships a lot of stuff and obviously could get the culture right in some areas.

Some people attribute it to bonus structures — especially these middle managers in generative AI who are going to be making performance bonuses for getting things into production. That’s a lot of money. But it’s more complicated than that because these people were making a lot of money before.

Jordan Schneider: Yeah, you just don’t have resource constraints, and it’s too many cooks in the kitchen. Someone should write the definitive business feature on this — I’ve yet to read the great magazine piece about it, but there should be one. It’s a fascinating corporate case study of a company that has every business reason and every corporate capability necessary to execute on this thing, which smaller teams all around the world have been able to do, and they’re just not there.

Nathan Lambert: It’s more complicated because the Llama models are natively multimodal, which is a big change. As you add more things you’re trying to plug into the model, it really does get complicated.

The dynamic is effectively: you have big egos that did some work, but their work might be slightly subpar, and they’re going to really advocate for their work to be included because they have ego and pride about their work. You have to get them to not do that. I’ve heard somebody not at Meta jokingly say “oh yeah, you should just pay them off. You just pay them more to shut up and get a better model out of it.” That’s something I’ve heard from a more effective organization, so it’s probably something that people have actually done.

Obviously, if that’s happening at another organization, Meta is not the only one dealing with this. It shows how nuanced this is and what a fine line it is — if you literally have to pay people off just to get better results.

Jordan Schneider: Look, Google’s figured it out, which is kind of amazing.

Nathan Lambert: People underestimate AI Overviews, which is an extremely high-usage AI product. All the Gemini stuff might just be a front — the Gemini offerings are a distraction for AI researchers and the people who built the model to show it off, get their peers excited about it, and help with recruiting. All Google needs to do is make AI Overviews extremely profitable and make Google Cloud extremely profitable. All this Gemini app stuff — I don’t think Google was really going to be in the business of making a ChatGPT competitor.

Meta does have the AI app now, which will be interesting to watch relative to ChatGPT. If it’s a sycophancy war, I’m probably going to bet on Meta, but I don’t know.

Jordan Schneider: They’ve got the Meta DNA in them now with Fidji Simo as the new CEO of Applications. Maybe she’ll go even further than Zuck let her in the heady 2010s days.

Nathan Lambert: I don’t know. I’ve read Careless People, the memoir by the Meta Global Affairs Policy person — good read. The TLDR is that Zuckerberg let them push when he didn’t have the reins on growth and other things. Many of your listeners understand the dynamics of a major tech company pushing for growth and influence, primarily internationally and with political power struggles.

Jordan Schneider: We’ll put it on the list. Anything else on the AI stuff before we move on?

Nathan Lambert: When we consider our careers relative to some of these X-risk warriors and takeoff scenarios, there are still many years of very solid progress on raw capabilities and making money off of AI. There will be a bubbly correction when it comes to VC startups. Many of them raised on the assumption of two to three years of runway, and some of those are going to start running out. They could look like big scalps, but most of it is GPU collateral.

It’s this weird situation where they raise a huge round, but most of it is collateral on these GPUs which don’t go away if the company goes away. People will probably overreact to some companies going away, but it was bound to happen. Overall, the AI industry seems super healthy, which is remarkable when you look back two years. People are raising these rounds — it’s not like Mistral raised that round as a seed round where they give away 45% of their company and they’re still functioning.

Jordan Schneider: Nathan, you wrote a nice career reflection post. What do you want to say to the kids out there?

Nathan Lambert: It takes a long time. People don’t want to sit here recording podcasts for five years before finally making any money.

Jordan Schneider: More like seven.

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Nathan Lambert: Yeah, there are two stories. One is that it takes a long time even if you’re at Berkeley. Some of the anecdotes I had were that I was astute enough to pick up that AI was obviously the thing happening in 2017. But even if you’re at a place like Berkeley or Stanford, you can’t just get into one of these research groups. You can’t just pivot. You have to do this long, slow slog and wait for somebody who’s good and sincere to ask to collaborate.

In that post, there were other things I had tried to do, like collaborate with postdocs who didn’t give a shit. That didn’t work. It’s the between-the-lines details that don’t matter, but it just takes a long time. It took me a year to get a real collaborator while being a motivated grad student at Berkeley. If you’re not at a top program, it’s going to take you longer. You might find a collaborator within a year, but it’s not going to be a postdoc in a leading AI lab. It’s going to be a random other person who wants to do AI research.

It just takes a long time and a lot of cycles. People ask me about this with athletics, too. Some random mid-aged tech person who’s losing track of their health asks, “Can I qualify for the Boston Marathon?” I’m like, “Yeah, you absolutely can. You just don’t want to do the 48-week training cycle that I’m going to sign you up for.” It’s not crazy — you’ll be doing seven to ten hours a week of training for 48 weeks, and I can tell you exactly what you need to do. You’ll get injured a couple of times, but people just don’t want to do that work. That’s most of the problem in AI.

It might be a little easier than training for the Boston Marathon because it doesn’t hurt as much physically, but it just takes a long time.

The other side is reflecting on what execution actually means and the difference between a career at Hugging Face before ChatGPT, doing random things, versus a career at Hugging Face after ChatGPT, when you’re doing something that’s actually aligned with the community. It’s very hard to know at the time that you’re doing the right thing. I was committing code and working on teams, and projects would come and go — it all looks very normal. It takes a lot of experience before you know you actually have traction on something.

Now I could see it a bit better just because I have a baseline for when things actually land. That’s something that takes a lot of experience to develop. A lot of companies will make it hard to do that. A lot of careers in big companies involve playing the promotion game that all of your peers are also playing.

The goal is finding a team or area within a company where that’s obviously not the goal — where leadership cares about direct deliverables, so you can skip a bunch of levels and get noticed. Or find work that’s done in public. It’s not always just about promoting within the company; you could also get mindshare outside of the company, which is valuable in both ways.

Internal company work is how you get promoted, but external mindshare is how you always have a job available to you. That kind of power means I can do what I want. I’ll just go get a different job if I want a different job. Once you have that, you can take a lot more risk. You could just write blog posts for six months and say, “I’m just going to ship it."

Jordan Schneider: This is why everyone listening to this needs to start their own Substack and newsletter. It’s particularly important on the China and tech analysis side. If you’re at a consulting firm and you do good work, maybe five people will know about it. If you write something online and you do good work, your entire career cohort and all the hundreds of other future people who could hire you will know about it.

It’s important to do a good job in your work, especially when you’re junior — actually, at any time. But people forget that the number of people in your field and the opportunities out there that are beyond the direct thing you could be promoted for in your company are orders of magnitude larger. Particularly now that we live in the age of the Internet, you can write things even anonymously and people can read them.

Having some sort of public profile or portfolio that you can gain credibility points from is something that everyone should be taught by their career counselor when they’re 21 years old looking for a job.

Nathan Lambert: Jobs where you are very open about what you’re doing and can do other open things provide far more consistent career growth. Even if your output is mid, you’re going to have growth proportional to that mid output. If you have mid output at a closed lab, you probably have no growth. You don’t get promoted, you don’t have any opportunities.

It’s not the only way to do things, but I definitely agree. In this post, I talk about a kind of backcasted strategy: AI is getting really closed, so what if I just keep doing what I’m going to do and don’t go off to some random flashy job? A few years later, nobody could talk about anything, but I’ve established myself as a person who knows how to train AI models and is transparent about it. People associate me with all of AI2’s output, and I’m not responsible for all of this stuff — AI2 doing well takes a lot of people.

Most of it is just work. I’m at the point where I tweet a lot, and on all of these platforms, the number of iterations you put in are proportional to your growth. Growth is easier once you have a bigger following. It’s often just starting from scratch when you have no following to slowly build up — plus one, plus two, plus three. The first thousand Twitter followers are hard, but once you have a thousand, it’s pretty easy to get more Twitter followers.

Getting through that phase in early to mid-career is pretty valuable. Getting to the point where you have some small level of distribution will help open a lot of doors.

Jordan Schneider: This is what young people don’t understand because all they see are LinkedIn job postings and recruiters coming to your college career fair. Once you get to a certain point, the jobs get created for you and there is inbound — that’s where you want to be living. But getting to that place requires people to know you exist and know you do good work. That only happens if you work in public.

Nathan Lambert: I can give an anecdote about how me being public brings a lot of value to AI2. The last three people we’ve hired on my team at AI2 have either been people that I’ve been working on recruiting for years, wanted to recruit for a while, or cold inbound to me. We still filter and read all these applicants, but there’s a lot of lukewarm stuff.

These are people who either wrote a killer email and had work I could easily look at — open source contributions, for example. In one case, someone worked in computer vision but wrote a kick-ass blog post on an RLHF method. I was like, “Okay, that’s cool.” Other people I had known through their writing or being in this open community and talking for years — those are three of the last people I’ve hired onto my team, and I’ve read hundreds of resumes.

There are other academic hires where we hire a random postdoc — that’s an academic thing. But these are engineering roles, and that’s how it works for individuals at AI2. It’s really valuable.

Jordan Schneider: We have this great Confucius line: “At 15 I had my mind bent on learning. At 30 I stood firm. At 40 I had no doubts. At 50 I knew the decrees of heaven. At 60 my ear was an obedient organ for the reception of truth. At 70 I could follow what my heart desired without transgressing what was right.”

It took me until I was 35, but I do feel like I am standing firm now. A lot of that had to do with the fact that I have this career foundation which has been built by doing things out in public.

Anyway, I shouted this out on the episode with a few weeks ago, but write your Substack, write five articles, reach out to me. I’ll give you feedback, we’ll do cross posts, whatever. The world needs more thinking about technology and China and all that good stuff. You can give it to them — I know you can.

Nathan Lambert: The thing about writing that people miss is that there are no new original ideas, really. It’s all just repackaging information in your worldview. The algorithmification of everything actually rewards people with voice. Fifty years ago, just writing the information down was of such value. There are still areas of the world where that is the case, and AI is one of them.

But in terms of building a career, so much of it is your voice and the perspective you put on things and the engagement that adds. Personally, many of my ideas on how I analyze AI model releases are downstream of reading something like Stratechery for multiple years. Ben Thompson’s beat is company earnings and how platforms are evolving. My beat is AI performance and how AI models work. At this point, I just do it and write my state of the world, and it looks like it’s about a specific model. Yeah, there are plots about evaluations, but really it’s about this trend of how models are evolving and how I see things.

There are so many different ways for people to do that. It mostly takes practice.

Mood Music

We’re having a meetup on Monday in DC. RSVP here!

This edition is brought to you by Pelanor, the AI-powered FinOps startup letting companies make sense of their cloud spend.

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Reach out to founder Matan Mates on LinkedIn or email him directly at matan@pelanor.io.

Oskar Galeev is a PhD researcher at Johns Hopkins SAIS working on AI history and the politics of the US-China tech race. Previously, he was a Yenching Scholar at Peking University and a Winter Fellow at the Centre for the Governance of AI.

Girish Sastry is an independent AI policy researcher specializing in technical aspects of AI governance. Before this, he spent 4 years at OpenAI where he worked on research related to AI misuse, compute governance, and capability evaluations.

Modern computing export restrictions have deep historical roots that extend far beyond recent headlines. Today’s AI chip denials represent just the latest chapter in a decades-old American strategy of technological containment — one that began long before the Biden administration’s AI diffusion framework or the Trump-era Huawei sanctions. This approach of strategically limiting adversaries’ computing capabilities traces back to the earliest days of the Cold War, when computational power first emerged as a geopolitical asset.

The Coordinating Committee for Multilateral Export Controls (CoCom), established in 1949, was America’s immediate response to a Soviet Union newly armed with nuclear capabilities. This American-led multilateral alliance, led by the United States, established a comprehensive technology embargo system. CoCom controlled the export of strategic goods and technologies — particularly computing equipment — that could enhance Soviet military and economic power. More than just a regulatory body, it represented a coordinated Western effort to maintain technological superiority throughout the Cold War. For 45 years, CoCom carefully managed what computing technologies could cross the Iron Curtain. It also unintentionally taught the Soviets to excel at smuggling and reverse-engineering computers.

Chinese and American think tanks alike have drawn parallels between CoCom and the modern Sino-American semiconductor competition. Guided by historical memory, Chinese policy conversations tend to focus on ChinCom, the specialized control system for the PRC. ChinCom had different goals than CoCom — as one CIA memo explained in 1952, “The problem of security controls respecting the China area is significantly different from that respecting the rest of the Soviet bloc”. While CoCom focused on long-term strategic competition with another superpower, ChinCom implied a much stricter punitive embargo as a direct reaction to “Chinese aggression in Korea.” The USA’s current view of China is similar to the perception of the USSR in the 1950s, but back then, the young PRC was not viewed as a geopolitical competitor or a party in the tech Cold War.

CoCom is the single longest case study on the impact of high-tech export controls in geopolitical competition — and for all intents and purposes, it worked. So what lessons can be learned from the history of the CoCom? And how are they likely to guide both the US and Chinese approaches to limiting each others’ compute capabilities?

New Cold War, Same Challenges

The first and most important parallel is the difficulty of enforcement. We often forget just how much the Cold War policy community complained about CoCom simply “not working.” Even though it was a multilateral regime, like today’s US semiconductor controls, it was not based on any treaty or binding agreement. And out of 17 member states of CoCom, only the US imposed re-export controls.

Sample of smuggled mainframes, industrial control computers, and supercomputers (in bold) during the CoCom era:

Throughout its history, CoCom’s effectiveness was reduced by overt non-compliance, differences between individual member nations, the overall secretive regime, and the financial bottom line of tech exporters. The Eastern Bloc was a giant developing market, and tech companies didn’t want to lose access. The export lists themselves often did not make any strategic sense — in the early years, CoCom even prohibited exports of items like typewriters (for an overview of control lists, check the collection by Sam Weiss Evans). But when it came to truly strategic technologies, control evasions were simply overlooked in most cases. Despite the Bruchhausen Semiconductor Smuggling in 1977-1980 and VAX Supercomputer Diversion of 1983, which directly boosted Soviet missile and aerospace design, only one control evasion case led to a strong policy response from the US. That was the Toshiba-Kongsberg case, the main geopolitical tech scandal of the Cold War.

In the early 1980s, the Soviet KGB received computer numerical controls (CNCs) clearly restricted under CoCom from the Japanese Toshiba Machine and Itochu Corporation as well as the Norwegian state-owned Kongsberg Vaapenfabrik Company. The suppliers were even updating and fine-tuning software on the Soviet facilities between 1982 and 1984. For export license purposes, the Norwegian Trade Ministry listed the items as spare parts for a civilian facility, while Japan’s MITI (Ministry of International Trade and Industry) registered the machines as older models not included in CoCom lists. The result was twofold — Soviet submarines got reduced acoustic signatures, increasing their stealth against American anti-submarine warfare capabilities, while the White House went on a punitive campaign, imposing sanctions on the Norwegian supplier and fully banning imports of Toshiba products. These repercussions made the Toshiba-Kongsberg case unique. The harsh consequences were partly motivated by the rising narrative of tech competition with Japan. It was not only the USSR that the American security establishment was worried about, but also about winning the competition against the Japanese tech sector. But the shamelessness of this case also motivated consequences — no effort was made to send the equipment through third countries, like everyone else did.

Soviet techniques for bypassing CoCom1

Despite extensive multilateral coordination under CoCom, enforcement remained its Achilles heel — a challenge that persists in today’s semiconductor controls. As the Heritage Foundation lamented in 1983: «Terrible Fact. To be sure, Washington would not have to control the re-export of U.S. items from its allies if the allies actually were effectively controlling the re-exports. The problem is that they are not».

On the Soviet side, a critical structural problem of technology competition lay not in acquisition but in efficient diffusion and allocation of restricted computing resources — that is, what happened after restricted tech made it through the blockade. Soviet archives reveal a dysfunctional internal competition that severely limited the effectiveness of their technology transfer efforts. Various intelligence departments, ministries, and industrial enterprises routinely competed for the same technological products, often outbidding each other and creating artificial scarcity for domestic users. The same IBM computer would be simultaneously pursued by a truck manufacturing plant, military production facilities, the state tourism operator Intourist, and even the Soviet Olympic Committee. This fragmentation extended to collection channels themselves, with Soviet industrial ministries frequently requesting identical Western computers through multiple intelligence agencies. Such uncoordinated efforts not only wasted resources, but also critically impaired the USSR’s ability to strategically deploy compute.

This pattern of inefficient resource allocation has modern parallels, such as the inefficient stockpiling of GPUs by Chinese companies and local governments, as covered by ChinaTalk. Chinese policy conversations are increasingly focused on this, arguing that the US-led export control regime should be addressed through “Construction of a Unified National Market” 全国统一大市场建设, a policy aiming to coordinate provincial governments to gain leverage over foreign firms and eliminate local protectionism and administrative monopolies. While there are structural similarities to the supply-side restrictions of the CoCom era, China’s effort to streamline resource allocation means those same control strategies might not yield the same results today.

PRC≠USSR

China’s economic leverage creates a formidable counterweight to future export control efforts. Beijing possesses retaliatory capabilities along the semiconductor supply chain in a way the Soviets never did, especially through critical resources like rare earth minerals. More importantly, China actually has an export market. The Soviet Union’s technological autarky meant it never developed computing giants capable of competing globally. Archival evidence shows that Soviet-made computers rarely crossed even Eastern Bloc borders, let alone captured a share of Western markets. And when transistors first revolutionized telecommunications in the 1950s, CoCom had already been established, reinforcing America’s first-mover advantage. Today, the United States faces the much more complex challenge of building a coalition mid-race.

The second critical difference between the political era of CoCom and that of the 2020s lies in access to human capital. Throughout its technological competition with the United States, the USSR was severely constrained by its limited access to international talent, particularly the tacit knowledge transfer from American computer engineers. While exceptions like Joel Barr and Alfred Sarant enabled rare technological breakthroughs, such cases were anomalies rather than the norm. The Soviet Union could not practically implement anything like the Thousand Talents Program (千人计划). By contrast, Chinese recruitment efforts have successfully targeted specialists from companies like ASML and TSMC alongside top graduates from universities worldwide.

The current competition for global STEM talent contrasts sharply with the CoCom era, when the United States served as the unchallenged center of gravity for international technical expertise. In a world where knowledge transfer often proves more valuable than hardware access alone, human resources can play a substantial role in circumventing export restrictions. The US Foreign Direct Product Rule effectively restricts American talent, but any realistic export control framework must also incorporate talent retention.

Three lessons from CoCom

1. Effective technology denial requires multilateral enforcement.

There may be inherent limitations to a unilateral enforcement of the export control regime. Despite its structural challenges, CoCom at least regularly coordinated the leading technological and manufacturing powers in restricting access to critical technologies for the United States’ strategic adversary — an alignment that does not exist today. Both CSIS and Carnegie suggested that unilateral controls on frontier technologies are ineffective, a point made many times before, including by Eric Hirschhorn, the former head of BIS, who compared it to “damming half the river.”

2. Tracking and verification systems are a prerequisite to effective enforcement.

Where CoCom frequently failed was its inability to track controlled technologies once they left manufacturer facilities, creating enforcement gaps that were systematically exploited through transshipment, diversion, and falsified end-user declarations. Erich Grunewald and Michael Aird proposed a chip registry idea, noting that “a key problem for AI chip export enforcement is that BIS does not know where exported AI chips are.” Without visibility into the movement and end-use of restricted technologies, even the most comprehensive control frameworks will ultimately collapse under their own enforcement limitations. Implementing something like the chip registry would significantly increase the odds of technology denial achieving the desired effect.

3. CoCom operated under nearly ideal institutional conditions, and still could not be enforced perfectly.

CoCom was poised for success, operating under an ideologically bifurcated international system with established multilateral coordination structures and decades of institutional development. Despite these favorable conditions, CoCom still struggled. Today’s landscape offers none of these advantages to the US — the world today has incomparably more interconnected trade networks, fragmented alliance structures with competing economic interests, and a technologically sophisticated competitor deeply embedded in semiconductor supply chains. If CoCom’s results were mixed even under optimal containment conditions, expectations for current export control effectiveness should probably be tempered.

Is the glass half-full or half-empty?

CoCom suggests that export control regimes have always faced practical challenges. Perhaps the most significant challenge is reliable enforcement. To the extent that CoCom was successful, it was through the cooperation of other countries in a more multilateral regime. Today, deteriorating alliance cohesion and tariff wars could undermine the verification and enforcement mechanisms necessary for effective controls. As the intelligence leaks and scandals of the Cold War era show, crucial partners like South Korea and the Netherlands did not always have incentives to comply with the US-led tech regime. Today, these partners simultaneously host critical semiconductor infrastructure while also maintaining substantial economic ties with China. In fact, despite export restrictions, TSMC may have already manufactured millions of controlled high-end AI chips for Huawei.

What does this mean for US AI policy? First, policies that improve verification systems and bolster multilateral institution building would be very effective. Verification and compliance measures should address not only chip smuggling but also other potential circumvention methods such as the use and operation of data centers in countries like Malaysia, remote access to large amounts of compute through cloud services, use of TSMC manufacturing, and other avenues to skirt US export controls.

Second, as policymakers navigate the current “chip war,” they should recognize that export controls represent just one element of a comprehensive technology strategy — one that must be balanced against both economic interdependence and the reality that innovation often flourishes in response to constraints. The most sustainable technological advantage will likely come not from restriction alone, but from accelerating domestic innovation while selectively managing the most critical chokepoints in the AI supply chain.

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As Meta aggressively consolidated the US market for augmented reality glasses, it scared off what could have been a competitive AR ecosystem in the West. Only now with Google’s recent AR announcements at I/O is a second serious player back in the game. In the words of Leap Motion and Midjourney founder David Holz:

“VR and AR really needed 12 companies basically making products… [I]n two generations of 12 companies, we would have been way closer to something that was really compelling for everyone. But instead, we got one product, maybe two.”

In China, however, there has been no such consolidation, and a “Hundred Lens War” (百镜大战) has instead produced a vibrant AR ecosystem where small startups, rather than tech giants, lead. But does it matter that there are no American analogues to China’s “Five Little Dragons” of augmented reality (AR眼镜五小龙)?

Skepticism toward AR glasses is understandable (especially after the highly publicized failure of Google Glass), but the premature consolidation of the US market could have dramatic consequences one day. Real-time translation via a wearable product could be game-changing in linguistically diverse places like India; some consumers could be compelled by the prospect of using AR glasses as a real-time conversation guide; and maybe hyper-immersive Wii sports will prove to be even more fun than the low-tech version we enjoy today. The point is, we can’t really sit here in 2025 and say with certainty that AR glasses won’t have any compelling use cases.

If manufacturers eventually overcome technical challenges and get the public on board, AR glasses could generate tons of real-world audio and video data valuable for training AI, much like humanoid robots. This route to profitability could help buoy AR investment, even if the public isn’t sold on AR products yet. That could also partly explain why Xi tried on some AR glasses during his recent tour of Shanghai’s AI ecosystem.

Today’s article will explore China’s market for AR glasses and introduce China’s Five Little AR Dragons. It will also include my personal review of a Chinese-made AR headset that I was able to try in Taipei.

Terminology and the State of the Art

Augmented reality (AR) is distinct from virtual reality (VR) — AR headsets are designed to overlay digital features onto the user’s interaction with the real world, and can theoretically be worn for extended periods. VR products are designed for shorter periods of fully immersive use (Apple’s Vision Pro, for example, does both VR and passthrough AR). The umbrella term for both AR and VR is extended reality, or XR for short.

Chinese XR glasses manufacturers rely on microdisplays, primarily micro-LED and micro-OLED displays. While traditional OLED displays use a backplane made of glass, the pixels of micro-OLED displays are etched directly onto a silicon wafer (hence their alternative name, OLED on Silicon, or OLEDoS). Thanks to supply chains created for the Apple Vision Pro, the cost of producing these displays has dropped rapidly in China since 2023. In March, Chinese LEDoS manufacturer JBD cinched a deal with Meta to become the exclusive supplier of LEDoS displays for Meta’s Orion prototype.

Another key component is the waveguide. A waveguide is a transparent optical component that guides light from the display to the user’s eyes while allowing them to see the real world. The waveguide makes it possible to overlay digital content onto physical environments. As is the case with microdisplays, China’s leading suppliers of waveguides are based in Shanghai.

Five Little Dragons

What can these glasses do today? Traditionally, the industry has emphasized entertainment features (e.g., gaming, streaming movies and music, and shooting photos and videos) while touting the potential future benefits in education, medical care, and delivery logistics.

But after Meta announced new AI features for their Ray-Ban smart glasses in April 2024, China’s AR companies have been eager to capitalize on the “AI+AR” hype. According to Li Hongwei 李宏伟, CEO of the AR dragon RayNeo:

“Smartphones do not have the display features or capabilities of spatial perception interaction that AR glasses have. AI+AR glasses encompass three categories: mobile phone applications, AI smart assistants, and virtual reality integration. The latter two are opportunities for disruptive innovation. For this reason, more than half of the successful companies in the future AR market may not be traditional giants, but emerging companies.”

Still, less than 20% of designs in the Chinese smart glasses market had AI functions by the end of 2024. AI integration is difficult in part due to dependence on external computing power — suitable processors are simply way too big and energy-hungry to fit into the frames of the glasses. That’s why AR glasses often rely on split compute to preserve battery life — tasks like translation are offloaded to the user’s cellphone, and then the result is transferred to the glasses through WiFi to save power. This also means that AR companies benefit substantially from locking down partnerships with phone companies that control the ecosystem.

China's VR/AR industry reportedly raised 2.948 billion RMB (~US$340 million) across 30 investment and financing events from January to November 2024. While tech giants like Huawei and Xiaomi have been dabbling in AR, innovation has primarily been driven by the so-called “Five Little Dragons” of the AR industry: XREAL (优奈柯恩), RayNeo (雷鸟创新), Rokid (灵伴科技), INMO (影目科技), and the Xi-endorsed Meizu (星纪魅族).

Thanks to fierce domestic competition, most models of AR glasses currently available in China are in the price range of 2,000-4,000 RMB (~US$275-$550). By comparison, Meta’s Ray Ban glasses, which don’t include displays in the lenses, start at US$299, and their full-service Orion prototypes cost US$10,000 per unit to produce.

We’ll briefly highlight each company’s quirks below.

XREAL 优奈柯恩

XREAL was founded in Hangzhou by Xu Chi 徐驰, but the company has recently relocated its headquarters to Shanghai. While other AR startups primarily use Snapdragon processors made by Qualcomm, XREAL uniquely uses self-developed chips. XREAL’s X1 processors can reportedly achieve a latency of 3 milliseconds (compared to 12 milliseconds for the Apple Vision Pro). Xu explains:

“The X1 chip equipped in the XREAL One not only successfully resolves technical challenges like 3DoF spatial anchoring and ultra-low latency, but also fundamentally overcomes the longstanding issue of inconsistent cross-device experiences for AR glasses. In the past, to provide a consistent experience across different operating systems, we had to develop separate software for Windows, macOS, Android, and iOS platforms. Yet even then, it was difficult to fully ensure uniformity in the user experience. With XREAL One, however, we’ve finally found a more elegant solution. By integrating computing power directly into the glasses themselves, we’ve fundamentally changed the game — delivering a truly meaningful “AR for all” experience.”

Xu also noted that 65% of XREAL’s smart glasses components are developed and manufactured in-house, and the company is aiming for 100% hardware independence within the next two years. But this hardware-focused approach has tradeoffs — XREAL’s products don’t currently come equipped with out-of-the-box AI features, although the company claims that LLM integration will be included in a future software update. Here’s Xu’s justification for not engaging with the AI+AR hype:

“AR glasses are always centered around user experience. We won’t blindly build AI glasses just for the sake of having AI. Instead, we start from the user experience and work backwards to identify what kinds of technical innovation are necessary.

In the R&D process, we have to wisely understand the limits of current technology — knowing what’s realistically achievable and what isn’t, at least for now. Blindly chasing breakthroughs can lead to disastrous outcomes.

Although XREAL is a relatively small company, our strength lies in the smart use of limited resources. We’re very clear about where to allocate funds to keep our product logic sharp and focused.”

Consumer reviews of the XREAL glasses have been quite positive despite the lack of AR+AI branding. One reviewer from Hong Kong wrote in April of 2025:

These are the best AR smart glasses, perfect for entertainment whether you're out and about or relaxing at home (such as in a small apartment or lying in bed). Once connected to a compatible device via USB-C, users can watch their favorite shows, movies, or games on a large virtual screen, like having a private cinema.

The glasses feature a Full HD 120Hz OLED display with a brightness of up to 600 nits, delivering vivid images and excellent contrast for viewing dark scenes. The image quality is further enhanced by electrochromic dimming lenses, allowing users to adjust the lens brightness with a switch. At the clearest setting, the lenses let users easily see their surroundings, while at the darkest setting, they effectively block out external light, providing an almost perfect viewing experience.

In addition, the glasses boast impressive speakers, with sound quality tuned by Bose, offering rich audio across highs, mids, and lows. While using separate headphones can still enhance the audio experience, this is the first pair of smart glasses where users feel that headphones are an optional accessory rather than a necessity.

XREAL has also prioritized business partnerships under Xu, betting that the experience will translate to market share once AR technology is mature enough to garner widespread consumer interest. XREAL has inked deals with BMW, T-Mobile, AT&T, Bose, and Google.

RayNeo 雷鸟创新

RayNeo is a subsidiary of TCL, an electronics manufacturing giant that is partially state-owned. The company’s Mandarin name translates literally to “Thunderbird Innovations,” and they are notable for marketing AR products aggressively outside of China. CEO Li Hongwei 李宏伟 explains in an interview from January 2024:

“We wanted to establish a foothold in overseas markets first, so we started by working on distribution channels. For example, we launched on Amazon, and in November last year, we achieved strong results by ranking first on both the new arrivals chart and the bestsellers list in the smart glasses category.

Right now, we’re also selling our products in some boutique stores across Europe… and the sales performance there has been fairly good as well.”

RayNeo recently announced a partnership with the International Olympic Committee, so we’ll probably see promotional videos for Los Angeles 2028 shot from the perspective of athletes.

The company also partnered with Alibaba Cloud to develop a multimodal AI model specifically for AR glasses — now, the average response time for AI queries on RayNeo glasses is reportedly 1.3 seconds.

Finally, RayNeo was the first company in the Chinese market to sell AR glasses for less than 2,000 RMB. Here’s how they keep costs low, according to Li:

“If Meta’s Orion is the Vision Pro of AR glasses, then the RayNeo X3 Pro is more like the “Vision.” …It does not use the most cutting-edge technology in all technical indicators like Orion…. For example, in the selection of optical waveguides, although RayNeo has a silicon carbide wafer version internally, our commercial products do not use this material. Instead… we use photolithography machines and chip etching processes to make waveguides on glass, so as to better balance costs and product experience. As the company's strategy, RayNeo will not choose to pile up all the industry's most advanced technologies in listed products for the sake of showing off its skills, but will develop cutting-edge technologies and products internally, and eventually launch leading, pragmatic, and mass-producible products to the market.”

Rokid 灵伴科技

Rokid was founded in Hangzhou in 2014 by Zhu Mingming 祝铭明, who left his job at Alibaba to start the company. In 2024, Rokid received nearly 500 million RMB and 100 million RMB across two rounds of financing. Their AI-equipped glasses use Alibaba’s Qwen models for real-time translation.

Among the AR dragons, a uniquely large portion of Rokid’s investors are SOEs. Here’s Zhu’s explanation from an April 2025 interview:

We have significant influence on the B2B side — the cultural and museum market alone is worth around a hundred million yuan annually. Our ecosystem partners bring in tens of millions, and each year, several million people visit museums. Rokid is the only player in this sector. …

B2B operations serve as a bridge for interacting with the government. Even in local governments with no overlapping business opportunities, there are always departments for cultural tourism and museums.

Rokid partnered with the PLA to build custom AR glasses for use on China’s space station. Their website also highlights B2B partnerships with oil, gas, and mining operations. But for now, Rokid’s consumer products receive mixed reviews.

I was able to try the Rokid Max AR glasses at the Guanghua Digital Plaza in Taipei. I watched a clip from Avengers: Endgame with the glasses, and the image quality was quite nice. You can correct for nearsightedness without customized lenses if your prescription is between 0.00D and -6.00D. I expected my eyes to feel strange switching between far-away objects and the close-up digital projection (as is reported by many reviewers), but I didn’t notice any such feeling during short-term use.

Unfortunately, they are very ugly and sit weirdly far and high up on your face. They’re also not wireless (unless you buy a wireless adapter, which adds latency), and the Rokid Max glasses I tried don’t support AI features like translation (Rokid’s AI-equipped glasses are a separate product line).

My impression is that, for now, the most tangible use case for these glasses is avoiding neck strain.

INMO 影目科技

INMO’s Chinese name could be translated as “Image Eye Technologies.” As a newer entrant into the Chinese AR market, their strategy has focused on affordable consumer AR with basic features, advertising use cases like cycling directions, translation, and taking notes in meetings. The company marketed their INMO GO glasses as “the first consumer-grade AR glasses with deep AI integration,” highlighting translation capabilities in 11 languages, smart notifications, and AI assistant features supported by ChatGPT. Here’s INMO founder and CEO Yang Longsheng 杨龙昇 on his vision for popularizing AR glasses:

“We hope that AI glasses can be like a personal assistant in the future, helping me order takeout, order a cup of coffee, etc. at any time. …

In the past, social interaction was generally between real people, but based on the emergence of AI and the improvement of technologies such as virtual humans, I believe that in the near future, perhaps within four or five years, people will be able to socialize with these virtual intelligent entities.

I can create a virtual image of my dreams, infuse it with the personality I want, and then interact with it in this entire virtual-real world. …

[AI companies] also need to find some landing points for these intelligent entities. Glasses are undoubtedly the best form at present, which also encourages them to try more content on glasses.”

INMO’s content partners include Baidu (China’s Google analogue), TanTan (a dating app), and game developers NetEase and 37Games. Chinese reviewers seem to appreciate the INMO software ecosystem — one user wrote,

“The INMO AIR 3 uses the IMOS 3.0 operating system, an OS specifically designed for AI+AR terminals. The AIR 3 can project the equivalent of a 150-inch giant screen. With the help of a 3DoF smart ring, the AIR 3 supports screen-space hovering functionality. IMOS 3.0 provides more efficient applications and a more immersive experience through intelligent interaction and spatial display capabilities. IMOS 3.0 not only supports native AR applications but is also compatible with most Android apps on the market, offering a relatively rich content ecosystem.”

INMO also recently announced a partnership with China Mobile to integrate their AR products with China Mobile’s Jiutian LLM ecosystem.

Meizu 星纪魅族

Meizu is owned by Geely, a conglomerate that primarily manufactures automobiles and holds a controlling stake in Volvo. Meizu’s primary business ventures are smartphone manufacturing and developing the FlyMe Auto operating system used by many Geely-owned car brands. As such, Meizu’s AR glasses are compatible with FlyMe-equipped vehicles.

At the 2025 Shanghai Global Investment Promotion Conference, Meizu founder Li Shufu 李书福gave a highly-publicized speech while wearing a pair of Meizu glasses, which acted as a teleprompter.

The company has developed its own FlyMe LLM, but Meizu glasses also support integration with third-party AI models, including DeepSeek, Qwen, and ByteDance’s Doubao. In early 2024, the company signed a partnership with Malaysia's Juwei Group to expand sales of Meizu glasses in Southeast Asian markets.

Looking Forward

China’s “Hundred Lens War” is a live experiment in hardware innovation under pressure. While consumer interest remains tepid, China’s Five Little Dragons are constantly launching new products in search of the ideal combination of design choices — wired vs wireless, with lens displays vs without, AI vs traditional translation, and many more. If AR glasses eventually succeed in locking down compelling use cases, it’s likely just as likely their decisive breakthroughs will come from not from Silicon Valley but Shanghai.

Thanks to Mike G. and Benjamin Reinhardt for offering feedback on previous drafts of this article.

Can studying Mao Zedong help explain Donald Trump?

To find out, ChinaTalk interviewed the legendary sinologist Orville Schell, who visited China during the Cultural Revolution and is currently at the Asia Society.

We discuss…

• Mao Zedong’s psychology and political style,

• Similarities and differences between Mao and Trump,

• How Mao-era traumas reverberate in modern China, including how the Cultural Revolution has influenced the Xi family,

• How Zhou Enlai and Deng Xiaoping survived the Cultural Revolution, and which of their tactics could be useful in modern America,

• What civil society can do to defend democracy over the next four years.

Co-hosting is Alexander Boyd, associate editor at China Books Review and former ChinaTalk intern.

Listen on Spotify, iTunes, or your favorite podcast app.

Culture War x Cultural Revolution

Alexander Boyd: Orville, you wrote the most prominent essay on Trump’s Cultural Revolution, comparing Donald Trump’s behavior in office and personal style to Mao Zedong. To start, what is Maoism, and how would you describe Mao Zedong?

Orville Schell: Mao Zedong, of course, was the great progenitor of the Chinese Communist Revolution. He was a Marxist-Leninist, and he liked control as any autocrat would. However, one of the hallmarks of Mao Zedong was also an abiding interest in throwing things off balance as a way to gain even greater power.

In this regard, he became a great fan of Sun Wukong. This golden-haired monkey was one of the heroes of the classic Chinese novel, Journey to the West, which tells the story of Buddhist scriptures being brought from India to China. One of the most prominent features of this monkey king was his love of disorder. His sort of watchword was “dànào-tiāngōng” (大鬧天宮), to make great disorder under heaven. Mao Zedong actually ended one of his poems with that line, and he always loved this novel, Journey to the West.

When the Cultural Revolution arrived, I think this was a real consummate expression of Mao’s affection for chaos. He did feel that not only did Chinese society need to be upturned, but the whole political structure of China needed to be upturned. Everything in effect needed to be “fānshēn" (翻身), as he said, “turned over.” He adopted many expressions similar to the Monkey King that expressed his love of contradiction and disorder. Class struggle, of course, which became the hallmark of the Cultural Revolution, was a form of deep and disturbing disorder.

Alexander Boyd: Where did Mao’s need for constant chaos and rebellion come from? In your Project Syndicate essay, you posit that it came from his troubled relationship with his father. Can you describe the parallels to the case of Donald Trump, who had a famously domineering father himself?

Orville Schell: The one place where we really get chapter and verse on Mao’s relationship to his father growing up in Hunan at the end of the 19th century was in Red Star over China by Edgar Snow. Mao told Snow that he had a very adversarial relationship with his father. He even said he hated his father, that his father was a tyrant, and they were constantly battling. On a number of occasions, Mao Zedong actually ran away from his home.

He did have a very sort of Buddhist-inclined, loving mother who made a lot of difference. But the relationship with his father clearly set off the notion of the world as an adversarial place. He tells Snow that he learned only by standing up to his father could he survive, and then his father would come to heel in some sense and not just overwhelm him with his sort of tyrannical paternal role.

That sort of characterizes Mao, and in fact Trump too, as we learn from his niece (the daughter of his older brother), who is a psychologist. Trump had a father who was very preemptive, very tyrannical and very judgmental.

Wallowing off into the bog of psychobabble here, any human being who reads literature knows that a father’s relationship to his son and vice versa is a profoundly influential relationship. As a young man grows up, that relationship forms him.

Alexander Boyd: We know that Mao loved to speak in allegory. He often would speak about one thing but mean another. How much can we believe his stories to Edgar Snow? And is it just a metaphor for American paternalism?

Orville Schell: I think at the period when Edgar Snow was doing these interviews with Mao was in the 1930s. We hadn’t started all the rectification movements and Mao had not been in power with all his mass campaigns. He had just arrived in Shaanxi province. I think that we get a pretty unalloyed representation of his early years. I don’t see there’d be any reason for him to be setting traps or deceiving Snow.

Throughout his life, Mao easily took umbrage at things when he felt sat upon or disrespected. Another famous example, of course, is when he finally went to Beijing in the late 1920s and he became a senior intern of some sort at the Library in Beijing University. He used to feel incredibly disdained by Chinese intellectuals who’d come in and sneer at his hickey Hunan accent.

If you‘ve ever heard Mao Zedong speak or seen a film in which he speaks, he’s almost unintelligible to Mandarin speakers. Like most Chinese people of his generation, including Deng Xiaoping and Chiang Kai Shek, he preferred to speak his local dialect.

This laid the track for Mao’s antipathy towards intellectuals, just like Trump hates intellectuals and universities. He thinks they’re arrogant, they’re elitist, they look down on people like him and down on working people, et cetera. Mao felt very much that no matter what he did in his formative years, he was disdained and disrespected by the intellectual class.

Of course, in that sense, I think he is a metaphor for sort of the whole ‘kultur’ of China in a sense that it is aggrieved, it’s been humiliated, it has been looked down on, kicked around, exploited, you name it.

Alexander Boyd: Another similarity between Trump and Mao is that both men had a lot of wives, often tumultuous ends to those relationships with women, and a propensity to start new relationships before the last one ended.

Yet another parallel is Mao’s exposure to Hunan secret societies, specifically Gēlǎohuì (哥老會), the Red Gang, and his time as an organizer at Anyuan. This mimics Trump’s early mob ties, especially in the New York of John Gotti and then Rudy Giuliani, who was a big mob fighter back in his day.

Their styles of governance are also similar — Mao made frequent trips outside of Beijing, and he loved to launch campaigns while on the move, much like Trump’s Mar-a-Lago golf club trips.

Are these comparisons substantial, or is it just the case that when you have so much information about two people, you can always draw connections between them?

Orville Schell: It’s true that both Mao and Trump had a lot of wives and a lot of ladies. What that suggests is that they need to have that kind of affirmation and signs that they can beguile people and win people over, which speaks to me of a fundamental lack of self-confidence. Both of them derived a certain measure of prowess from their ability to attract beautiful women.

Trump still talks about women as objects and as adornments. Mao clearly was the same. There were other leaders in China who were not. Chiang Kai-shek had a lot of ladies (and ladies of the night as well in his youth), but after he got married, he was quite faithful. I don’t quite know what to make of Zhou Enlai, but he had one wife. Whether he was gay or not, it’s a question people do care about.

Mao was somewhat special, and he arrogated that special right to poach on women himself. But when revolution came home to roost after 1949, it was not something he found acceptable in ordinary people or even in his acolytes. He was very puritan. But he was not just like Trump. Trump purports to be a Christian and yet doesn’t abide in any meaningful way by the notion of loyalty implicit in marriage.

Jordan Schneider: Shall we discuss the deep state example?

Alexander Boyd: Trump famously vowed to drain the swamp and railed against a deep state that he perceives as having both frustrated his attempts to exercise power in his first term and prevented him from regaining office in 2020. Now he’s engaged in a campaign of revenge against all those purported deep state agents.

Many people, and you chief among them, have made that comparison to the Cultural Revolution where a frustrated and suspicious Mao unleashed these animal forces within China to take down a party in a state leadership that he felt was shackling his own ambitions to remake China. Is that an accurate comparison in your mind?

Orville Schell: One of the hallmarks of Mao’s revolution was a sense that somehow the party (which he himself had helped build) and the state (which was the handmaiden of the party) were ultimately the refuge of rivals.

He had a great antipathy against bureaucratism. This also speaks of his love of disorder as a creative force. When he started the Cultural Revolution, one of the first things he did was to issue a wall poster that said “bombard the headquarters” (pào dǎ sīlìngbù, 炮打司令部). What he meant by that was that he felt the party had become ossified. It had become the refuge of bureaucrats who were living high on the hog but didn‘t want to make revolution anymore and found class warfare too disruptive.

He felt that it was time to destroy it. How did he do that? He gave permission to young people, idealistic young people, to attack. Almost all of the leaders who were potential adversaries of Mao either died or were purged. Xi Jinping’s father was one of them, a vice premier who had a very bitter purging.

In that regard, Mao Zedong took, I think, great satisfaction in overturning even his close revolutionary comrades. Here Trump is not too dissimilar. He seems to be invigorated by the idea of destroying institutions that he views as refuges of people who might be against him and of firing people he’s hired, turning against people who he perceives as potential rivals. He demands complete fealty and loyalty or you’re in trouble.

Here too, I think there’s a kind of a similarity in the way the two relate to other leaders and to institutions of government, the deep state. It’s the equivalent for Trump of what the party and the state that he himself helped build were in China. He saw them as slowing down his revolution, as harboring his adversaries and as being overly bureaucratic, what he called “sugar-coated bullets of the bourgeoisie” (资产阶级的糖衣炮弹). In other words, they’d given up their revolutionary vigor in favor of staid bureaucratic forms of government.

Alexander Boyd: So if there’s an attack on the bureaucracy, does that make Elon Musk and DOGE a new Kuai Dafu 蒯大富 and the Red Guards?

Orville Schell: Musk is older. Kuai Dafu was one of the earliest Red Guard leaders at Tsinghua University when Mao issued his order to bombard the headquarters.

Elon Musk should know better, but I think he too has a kind of innate impulse that chaos is a creative element. It’s one step away from the Silicon Valley mantra, “failure is positive.” But I think he does share with Trump this idea that somehow you need to clean out the Augean stables of the government. I don’t know why Musk might feel disrespected or disdained when he’s been so successful and the richest man in the world.

Here, too, I think we have to remember that these leaders are human beings. They’re not just rational creatures who look at the national interest of the country or read reports to make rational decisions. Some leaders are completely crazy.   We know from Euripides and Shakespeare that leaders are completely crazy and they do astounding things.

You can read Stephen Greenblatt’s book, Tyrant: Shakespeare on Politics, which is about six great plays that Shakespeare wrote about tyrannical leaders. There’s nothing new here. It’s just that policy people and I think many academics are loath to recognize that we’re also dealing with something very human here, namely, leaders with deep and tragic flaws, which in Euripides are hubris, arrogance, and overreach.

When Croesus — we‘ve derived the expression “rich as Croesus” — went to the oracle of Delphi, he governed the state of Lydia, about whether he should go to war. He got the diction back from the oracle that if he went to war, he’d lose his kingdom. What did he do? He went to war and lost his kingdom.

There’s a little of that going on here. I think we need to factor the human dimension into the equation of understanding big leaders like Putin, Orban, Xi Jinping and others. Look back at their formative years.

Here, I highly recommend a wonderful new book that’s coming out by Joseph Torigan on Xi Jinping’s father, Xi Zhongxun 习仲勋. You see what nightmarish experience Xi Jinping went through as the son of a man who was twice purged during Xi Jinping’s teenage years, and was purged the second time as a counter-historical, counter-revolutionary. And what travails Xi Jinping as a young man went through to have a father who was in the five black categories.

This is a little bit beyond the mandate of so-called China socialist. But I do think that here’s where literature, drama, some of these other representations of leadership help us understand what’s going on.

Alexander Boyd: Let’s stay on Xi Jinping here for a second and Xi Zhongxun as well. What is Xi Jinping’s view on the Cultural Revolution today? Obviously it’s opaque, but I agree Torigan’s book is incredible and I read his section on Xi Jinping’s Cultural Revolution.

Orville Schell: I think it’s unfair to say that Xi Jinping is like Trump. Xi Jinping does not like disorder. He does not want to create great disorder under heaven, unlike Mao. The part of Mao he does bond with and did grow up with and appreciate is the Leninist part — the organized state, organized party control, autocracy. But he has no fascination for the part which we’ve been talking about.

This is why I suggested if Xi Jinping wants to come to some better understanding of who Trump is, ironically he has a homegrown example in Mao Zedong. He lived through it. He knows what people like that can do to a society and to even the global order. I think maybe he has thought this way. I don’t know, but I think he uniquely, unlike many Americans who’ve never been through this kind of disturbance, shouldn’t be so surprised by Trump.

Why do we think as Americans, when Italy had Mussolini and Germany had Hitler and Russia had Stalin and Spain had Franco, Salazar in Portugal and on and on, why do we think that we are somehow immune from these kinds of aberrant, overreaching, arrogant, and finally incredibly destructive leaders?

Jordan Schneider: China from 1949-1967 was a very different place with a very different governance system than America circa 2016 or 2025. Shall we discuss some of the differences here?

Alexander Boyd: Well, I think the first place that we should start is rise to power. Trump, you know, for better or for worse, won two elections, and Mao won power through civil war and various other means. Orville, what would you say is the biggest difference between Trump and Mao?

Orville Schell: Trump is more like Hitler, who came to power by being elected Chancellor of the Reichstag, whereas, as you point out, Mao Zedong came to power through insurgency and civil war.

Obviously, you can‘t completely compare these people, but I think in trying to understand the leaders of the present, it does behoove us to look back at leaders in the past who also created disorder, one kind or another — a world war, economic crisis, a revolution, whatever. That might help us understand a little bit what it is they’re offended by. What do they want? What would propitiate them? How do you deal with them? Can you deal with them?

I don‘t mean to compare Xi Jinping with Trump. But only to say that China’s historical experience of having undergone probably the most tectonic, catastrophic, and destructive revolution in history might help Xi understand what animates a leader like Trump and how best to deal with it.

Jordan Schneider: How best to deal with Mao is kind of not something people really figured out. Can you talk about what the antibodies were over the course of his reign, and highlight some examples of successful and unsuccessful pushback against his craziest ideas?

Orville Schell: Well, of course, the best, the biggest antibody of all to Mao was death. Many autocrats are very disruptive. Hitler died in his bunker, Stalin died, and wildly began to change. I don’t know what the antidote to Mao at that period would be, but I will say this, that if we look at our own country, there is a hint of similarity among the way people come to heel when big leader culture gets rolling.

The Republican Party is completely supine now. We do have the Democratic Party still raging against the storm. But one of the lessons I think that is quite striking about the Chinese communist revolutionary period was the way in which everybody finally was neutered. Those few who did speak out, and there were some, had very bitter ends. All know what happened. This is another hallmark of powerful and effective autocratic leaders is that they manage by one way or another — and one way is disorder — to intimidate people, frighten people into submission and silence.

Alexander Boyd: I think in a lot of histories of the 1970s though, everyone points to 1971 and Lin Biao’s death.

Jordan Schneider: Why don’t we do the Great Leap Forward and response to that? Because Mao had to do with self-criticism, right? This was a real brushback moment for him where after killing eight figures of his own citizens, there did end up being some pushback from the top that forced him down a policy path he wasn’t really excited to take.

Orville Schell: After the Great Leap Forward, many leaders like Deng Xiaoping and Zhou Enlai and Peng Dehuai felt it was too excessive. Forty million people dead, starvation, agriculture in ruins. They did for a brief period of time prevail. What was Mao’s answer?

Mao’s answer was the Socialist Education Campaign, which is a prelude to the Cultural Revolution, which ended up labeling people like Peng Dehuai at the Lushan conference, put out of business very quickly, ended up in jail. The president of China, Liu Shaoqi, Deng Xiaoping, were sent down. In other words, almost all the leaders, veteran revolutionaries that had accompanied Mao in the Long March in the Yan’an period, ended up in the doghouse or dead.

That was China’s experience. That made it very difficult for any voices of dissent to find any purchase. I remember being there myself during the end of the Cultural Revolution and just thinking, well, this is the way it is. There were no voices. They wouldn’t even talk to you as a foreigner. Nobody had permission even to interact in a normal human way with anybody foreign or an outsider because they were afraid. Mao had brought complete submission down onto society.

That didn‘t mean he suffocated all of the impulses that had built up over previous decades — they remained latent and dormant and they arose again when Mao died.

Alexander Boyd: Basically the biggest argument against Trump’s effort to remake America in his image, to bring manufacturing onshore, is that Mao, with more power at his disposal, more party at his disposal, a whole society cowed, actually failed. Even more recent scholarship, like Odd Arne Westad and Chen Jian’s new book The Great Transformation: China’s Road from Revolution to Reform argues that opening and reform really began in the 1970s. If Trump is Mao in this comparison, is the Trumpist effort, you know, this great “cultural revolution” in America, is it doomed to fail right from the beginning?

Orville Schell: Well, I think we could be doomed to something even worse. Mao failed in the Great Leap Forward. Then in order to regain and maintain power, he brought on the Great Proletarian Cultural Revolution. It’s hard to know. We can’t predict history and we don’t know whether American democracy will survive.

What we want to say is that we know this archetype of leader and whether it’s a communist, a Leninist, a so-called democrat, Nazi, fascist, whatever. That’s why I wrote some of these essays, to just remind people that there are examples throughout history and literature of these kinds of people. We need to better understand because now it’s America’s turn to have one.

Jordan Schneider: I think another one of the big differences that Tanner Greer pointed out on a show earlier where I tried to compare Trump to Hitler was the ideological commitment level that Trump has versus someone like a Mao or a Hitler who deeply believed in his bones in class struggle or Lebensraum or international Jewish conspiracy. Yes, Trump’s got some views on trade policy, but he lifted them after the bond market changed. It’s the sort of the level of focus which he can bring or has shown, the level of focus that he’s shown he can bring to policy stuff versus some of the other sort of totalitarians that you reference who maybe have some personality traits in common, but also kind of have a real agenda behind them. Whereas our current president, not so much.

Orville Schell: I agree with that, Jordan. Mao had a very highly evolved ideological agenda and analysis of how the world worked, where history was going, knowing what the dynamics would be. They did hew to that in various ways, sometimes rather opportunistically or in a utilitarian fashion. That’s communism.

But fascism is a very different animal. If you read Robert Paxton’s book on fascism, you begin to understand people like Mussolini. He had no ideology. He was sort of inventing himself as he went along. I think that’s one of the big differences between Trump and Mao. Mao was a very intelligent man and actually a good writer, good poet. He thought.

I don’t think Trump thinks — he acts almost like an animal. He feels this today and he acts, he responds. He certainly has no ideology or no sort of political commitments to principles that guide him in what he does. It’s more what he feels like doing. He feels someone doesn’t like him. He feels threatened. Whatever. It’s almost animal-like in his responses, which are completely irrational.

Alexander Boyd: This is actually not so much a continuation of this question, but it’s a different tack. I’m curious about Mao’s foreign policy and Trump’s foreign policy. A curious similarity is that Mao stated, “I like rightists.” He met with Richard Nixon. He found them easy to deal with in general, perhaps because he understood the ideological motivations of, or he perceived himself to understand the ideological motivations of capitalist right-wing politicians.

Then, Trump himself meeting today in the Oval Office with Carney, the Prime Minister of Canada, and earlier saying something like “I like the left” in reference to him not wanting Pierre Poilievre to win in Canada. Why do you think that Mao liked rightists or claimed to like rightists? What sort of insights does that give us into Trump’s foreign policy?

Orville Schell: In many ways, Mao could be a rightist, but I don’t think he liked anyone who opposed him. He viewed the right as opposing him and as opposing his ability to control thinking and ideas. This is why you get the whole idea of sīxiǎng gǎizào (思想改造), thought reform, that there’s a correct way to think and Mao helps limit that, describe that, lay the boundaries for that out. If you don’t want to think that way, then you’re a rightist or maybe even a leftist and then you deserve to be defenestrated.

I think Mao says he likes rightists because he thinks they’re practical and he can deal with them. It’s a bit of a capo-to-capo business. You can deal with a thug, even if you call him a rightist, but I don’t think he had any affection for rightists or leftists. These are categories of convenience into which he put people when he needed to get them off the stage.

Jordan Schneider: Yeah, I feel like the capo-to-capo thing is it’s less him liking Mark Carney, which I just truly do not believe, and more the ease and excitement where he gets talking to big, powerful, authoritarian leaders, as opposed to democratically elected ones.

Orville Schell: I think that, Jordan, if I may say, when Nixon and Kissinger went to China in ’72 and ’71 to set it up, I think there was a certain thrill for Zhou Enlai and Mao to have these people come hat in hand to Beijing to talk to them. Because remember that even though they were opposed to imperialism, colonialism, capitalism, America, et cetera, there is, I think, in my experience, at least amongst Chinese leaders representing their country, a deep and abiding wish to be respected.

They speak about that all the time, mutual respect and understanding, as if to say, “Can’t you just respect us as a dictatorship? Show us some respect. We’ve got a good economy, we’ve done a lot of amazing things,” which is true. Again, autocrats, one of the things that really riles them is that they’re cast out, they’re disdained, not considered proper company for liberal democratic states.

When China is the aggrieved, humiliated, kicked-around sick man of Asia, they want nothing more than to be respected. That is a complete contradiction because if you don’t act respectably, it’s very hard to be respected. Yet that is something they deeply crave, even though they would never acknowledge it.

Jordan Schneider: Yeah, I think it kind of works the other way as well, where you just see how big Trump’s smile was in his 2017 visit to China.

Orville Schell: I’ve been on several presidential trips, like for instance, with Clinton, which was completely different, very informal and open and cheerful. But Trump’s trip, it was all about pomp, circumstance, awe, ceremony and ritual. Both leaders were trying to impress each other and Xi Jinping wanted to impress Trump. You remember he took him to the Forbidden City and they had a banquet and all the rest of it.

But there were no moments of bonhomie, of personal smiling and back-slapping and saying, “Hey, we’ll work this out.” No, it was all about sort of who is the bigger dog with the most impressive marching band and most impressive Great Hall of the People. I think that’s very characteristic of both Trump and Xi. Trump wants to have a parade, just like Xi gets to have parades with a lot of tanks and missiles going by.

There’s an element of similarity, I think, of both deeply insecure men fundamentally, and nothing like a good parade to puff up insecure leaders’ egos.

Jordan Schneider: Can you talk about the sort of red versus expert dilemma, which we’re seeing play out with Laura Loomer in this administration?

Orville Schell: Remember that during the Cultural Revolution there were many, many struggles going on. One of them was the struggle between being Red and an expert. Experts, of course, were people who knew how to do something. They were the intellectuals, they were the scientists, the technicians, people who ran institutions and could be accused of bureaucracy.

The Reds were the people who wholeheartedly embraced Mao Zedong and were dedicated to overthrowing institutions of the experts. In that period, not only was expertise disdained and diminished in standing as a societal avocation, it was a hallmark of those first people being insubordinate. It was a different kind of loyalty — not to Mao, not to Maoism and Marxism-Leninism, but to rationalism, to scientific experiment, or these other things that had a kind of a logic that defied complete and total loyalty to the Great Helmsman, whatever he represented at the time.

Whether the party was intact or not during the Cultural Revolution, it was not loyalty to Mao and the revolution versus loyalty to whatever other thing you might be — a scientist, a businessman loyal to profit, and policymakers who are loyal to trying to figure out the national interest. That was a huge divide.

We see that now with Trump. What he wants is not people who know something in the FDA or the FAA. He wants people who are loyal. So you got Laura Loomer, like Kang Sheng or Chen Boda or someone running around firing people and putting people in prison for Mao.

Jordan Schneider: What was the upside for Mao of getting rid of the experts?

Orville Schell: Liu Binyan, the great writer of the 1980s, wrote a book called A Higher Kind of Loyalty. This was an analysis of people who felt a loyalty, whether it was through religion, technology, science, intellect, or just ideals, to something other than the revolution and the leader.

What Mao rejected and recoiled from was professionals who were experts, who said, “No, this revolution does not make sense economically, scientifically or in any other way. It’s mayhem.” That put them immediately on the enemies list. That’s why intellectuals, and they categorized them into many different categories, were pilloried because they couldn’t be totally loyal as religious people were, because religious people owe a different loyalty to their God and to their principles and to their morality, not to the leader.

Mao couldn’t stand that, so he waged war against those people. We see sort of, I think, hints of that happening now in America where people like Fauci in the first administration of Trump were not respected at all. He was a very good scientist, very devoted public servant. We see attacks on vaccines, Robert F. Kennedy Jr., science has proven measles vaccines work. We see a lot of things like this looming up again where what’s important is not logic, but it’s loyalty to the leader.

Alexander Boyd: But Mao also resented his need for these bureaucrats, for these technical experts. And chief among them was his own Confucius, Zhou Enlai. Even though he was fighting against these empiricists and scientists, cultural leaders and everything during the Cultural Revolution, probably the number one empiricist of all was right next to him. Although at the same time many Chinese spoke about him like we spoke about John Kelly in the first term. “Oh, he’ll be able to restrain Mao’s worst instincts.” How do you read Zhou Enlai?

Orville Schell: Zhou Enlai was a restraining influence. He was also a complete factotum. When you see what he was put through, like in the rectification campaign in 1942 where he sat before the Politburo for five days, wrote self-criticism, self-immolations, humiliating, pusillanimous kind. He paid a bitter price as a human being to keep in Mao’s good-enough graces. Still, Mao endlessly tormented him and humiliated him — very smart man. And he took it. Why? That’s an interesting question.

Did he think he was doing good like Matt Pottinger in the first administration of Trump, that if he just kept his head down and tried to do a good job, he could restrain the leader? But there was also probably a lust for power, an urge towards power which kept him there. He once got that needle in his arm, it was very hard to get out or he’d end up like his friend Liu Shaoqi — imprisoned or dead.

These kinds of leaders demand not one-time propitiation declarations of fealty and loyalty, but continuous. The leader keeps ramping up the ask. If the lieutenant wants to stay in their graces, they have to keep becoming more and more genuflective. We see an awful lot of people left the first administration of Trump and now he’s already lost all the people he’s lost. I mean, Rubio, everybody. He’s taken over positions of Waltz and others who drop like flies because it’s very difficult to satisfy the demands of autocrats who require 200% loyalty.

Alexander Boyd: Is part of this the “Coalitions of the Weak” thesis put out by Victor Shih about how Mao would often rehabilitate disgraced cadres? You saw that with Deng Xiaoping, you saw that with Zhou Enlai, he’d constantly send people down, bring them back, criticize them, humiliate them, purge them, restore them, and it ended up necessitating their loyalty. They created psychological dependence, but also political dependence.

Especially with Victor Shih, he’s talking about the Fourth Front Army in the Long March, I believe Zhang Guotao. Is that a similar coalition with Trump and Mao? And how did Mao’s coalition of the weak work? And is that an effective governance tool? We might be skeptical of it, but Rubio, who has no basis left in the GOP, has basically been entirely kneecapped, was humiliated in his run — he’s Zhou Enlai exactly. But he could also be our Deng Xiaoping.

Orville Schell: If you want some good reading, go back and read Deng Xiaoping’s self-criticism during the Cultural Revolution. He just abased himself and said over and over again, “I didn’t know Chairman Mao. I didn’t appreciate the brilliance of Chairman Mao.” Even he went through the ultimate humiliation but survived intact.

I was in Washington and went on the whole trip when Deng arrived in 1979 to normalize relationships. And you did get the sense of somebody who had his own sense of gravity about him, wasn’t a deeply insecure person just craving slavish loyalty. Deng Xiaoping was different. I would say Zhao Ziyang 赵紫阳 and Hu Yaobang 胡耀邦 were also different. When you look through the different leaders, you want to get back and judge their character. Yes, times were different, but Deng Xiaoping was special because he had seniority. He did get cashiered twice, but he never lost his fundamental sense of himself, which I think many other people did.

Alexander Boyd: Let’s be optimistic here and say there’ll be a post-Trump GOP. How did those Chinese survivors like Deng Xiaoping, Zhao Ziyang, etc. make it through Mao’s Cultural Revolution? And what could that tell you for an aspiring politician today hoping to make it through Trump 2.0 and still have a political career?

Orville Schell: Xi Jinping made it through and he’s done alright. There’s no simple answer. In the good old days when you also had imperial autocracies in the form of emperors, if you ran afoul of the government, you could run up into the mountains and become a Buddhist monk or a Taoist priest, and mind your own business. But that wasn’t possible under Mao.

We’ll see about what happens in America. I suspect we won’t get to such a state in America, but who knows? The question is, during autocracy, authoritarian rule, what should good people do? If you stick your head up, it gets chopped off. You can run abroad, you’re just in waiting. There’s not much you can do. It is a good question, and I’m not sure I know the answer to it. Keep saying what we need to say as we are here today. In China, that was not possible under Mao. It was not possible under Mao ever since the early 1940s when he began lowering the boom, wanting to create a new man and a new era, bringing on thought reform, rectification, and all the rest of it.

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Jordan Schneider: Let’s stay on this dilemma of the officials who know that they are living in crazy times but still want to help the people. What’s the right way to kind of look at what Deng and Zhou and others did in the Mao period?

Orville Schell: They’re always dancing on a razor’s edge. You know, it's not a, a dance I would care to know how to get out of. Fair enough. Some of these people — and Zhou Enlai had a measure of this, I wager — you want to do good by the people but the cost of staying in the game is very high.

The people in the Trump administration, in the first go around, there were a few, some quit and they did in some significant measure keep their integrity intact. And they did do some good restraining things. I think this administration is much harder. He’s bringing in the — Elon Musk is like a leader of Red Guards and the Proud Boys are Red Guards equivalent.

It’s a very difficult human dilemma to know if you want to be in government and you are drawn to political power, how do you do it now? Can you do it? Or should you just become a Buddhist monk or a Taoist priest and just go up on your mountain and wait? I don’t know the answer to that. Us who are writers? Who have not been in political power, don’t want to be in political power. We’re not drawn to that flame. So we do what we do.

Jordan Schneider: Comparing America 2025 to anytime in Mao’s reign, the downsides of recording a podcast like this are much lower.

Orville Schell: For now Jordan, but people have long memories and there are archives and there are a lot of people. The way Xi Jinping’s father fell the second time was over a book about a big leader in northwest Shaanxi province, Liu Zhidan 刘志丹, that he allowed to be published. Mao said, “Well, you’re trying to put too much emphasis on him as the hero, not me.” Anyway, it’s a long, complicated story, but simply to say that sometimes small things done in past, to autocratic regimes like China, are grounds for you being pilloried in the future.

Jordan Schneider: We’ll get into that arc with Joseph later this summer. I’m still feeling okay about our freedom to podcast.

Orville Schell: I’m glad you’re doing it. My virtue is that I’m a little older. I don’t need to be so worried about my future.

Alexander Boyd: Michael Berry talks about this in his writing about Fang Fang — the term míng zhé bǎo shēn (明哲保身) means, “Don’t speak out in order to preserve yourself.” I personally think that in the United States, we have a great privilege to be able to speak out, and we should exercise that privilege.

Orville Schell: We still do. The government in sort of in the shape it’s in, it puts all the more burden on the institutions of civil society. Universities, think tanks, libraries, and community organizations do not owe fealty to the central government, but owe fealty to what they do. Media would be another very important example — cultural organizations, orchestras, operas, whatnot.

Alexander Boyd: Trump has shown an immense fascination with the Kennedy Center in D.C., which is where I’m based. I think it was Cats that was his favorite.

Bach and Bloodlines

Alexander Boyd: Let’s talk, Orville, about bloodline theory. What was bloodline theory during the Cultural Revolution? Why did it matter? Mao himself wasn’t an endorser of bloodline theory, but it did have a lot of influence.

Trump always talks about genes. “It’s all in the genes.” Quite recently, he weighed in on the NFL draft about a quarterback who’s sliding, Shedeur Sanders, and saying, “He has phenomenal genes. They should have picked him because his dad was such a good player.” Is bloodline theory another parallel with the Cultural Revolution ?

Orville Schell: During the Cultural Revolution, the notion of bloodlines worked like this: if your father was a hero, so you were good to go. But on the other hand, if your father was someone of questionable background, then you bore that stigma. You were placed in that class category because families were categorized based on their class background.

As you all remember, Mao had this notion that certain classes had rights and were revolutionary, while certain classes — like the bourgeoisie and landlords — didn’t have rights. The bloodline concept was very pernicious because it meant that if your father was labeled as a counter-revolutionary, a rightist, a capitalist roader, or a bourgeois element, the children inherited that stigma through blood.

That’s why it’s fascinating to delve into familial relationships in any Chinese family. Xi Jinping is the most important case here because he’s now the leader. But I should also mention that in my experience — and this may be better explored in literature than in nonfiction — there’s a cascading effect. All the harm, damage, and attacks that occurred throughout the fifties, sixties, and seventies in China have endured across generations in the Chinese families I know, going from grandfather to father to son to grandson. They persist like microplastics in the ocean — they’re forever chemicals in a way.

We’ve paid no attention to this phenomenon. The way these experiences deranged families, destroyed people’s ability to respect and love their parents, caused betrayals of friendships, and led to the savage attacks that people inflicted on one another — Red Guards attacking their teachers — all of this continues to reverberate.

This trauma isn’t something you get over the next day, and it lives on in ways that are very difficult to analyze. There’s no data, and China doesn’t have a vigorous psychoanalytic tradition to help people understand what influences may have been passed down to them through their experiences with parents who suffered.

The Cultural Revolution was deep, and its consequences are enduring. That’s why, when Deng Xiaoping came to power and waved his wand to rehabilitate people, saying it was a new era, I felt incredibly skeptical. I believed there was a whole residue of impact deeply embedded within society and human beings.

There had been so much damage — not just Mao and the party treating people badly, but people being forced to treat their spouses badly, their children badly, their relatives, friends, and colleagues. This is something that endures.

Alexander Boyd: This endures in China to this day, you argue. When was your most recent trip back to China, and how do you see it enduring today?

Orville Schell: My most recent trip was just as the COVID pandemic hit. All you have to do is talk to your friends. I have a friend who went to Harvard, had a very difficult time with her parents, grew up in China, and she set up a group for Chinese women similar to her to discuss this. I found that incredibly interesting.

Some of the things that they stumbled upon as they were trying to analyze the relationships they have with their parents — how are they influenced by the relationship their parents had to their parents and to society, and power. Very few people have wandered into this field.

Robert J. Lifton, a wonderfully brilliant psychoanalyst who wrote Thought Reform and the Psychology of Totalism in the 50s and then Revolutionary Immortality about Mao’s quest to make himself immortal so that his legacy would live on. There have been very few people — Lucien Pye, Richard Solomon — who’ve actually looked into the human element. That’s why I wrote a novel, because I felt I couldn’t touch it as a nonfiction writer. I didn’t get to the question of the role of religion, music, culture, love, family. All of these things are abiding human concerns.

Alexander Boyd: You titled that novel after a Lu Xun 魯迅 essay. How come?

Orville Schell: I love that essay, My Old Home (故鄉). It’s a very wistful essay about returning home after things changed. My novel was about a classical musician and what happened to him when he returned back to China in the 50s as a lover of Bach.

If I may say so, there is no human being whom I think is more antithetical to Chairman Mao than Johann Sebastian Bach. In fact, I want to write a play called “My Dinner with Johann,” where they have a conversation. Because Bach was all about religion. Mao Zedong was all about the external. Something’s wrong? It’s out there, not in here.

Yes, Confucianism did have a notion of self-cultivation, but it’s not like Christianity.

Jordan Schneider: Well, we have to end with the ChatGPT imagined conversation between Bach and Mao.

Orville Schell: There was a show Henry Kissinger went to, and Robin Williams started wandering down the aisle afterwards. He passed Kissinger, and he was saying things to people as he went. He said, “Oh, Henry, love all your wars.” I could imagine Bach starting off by saying to Mao, “Love all your revolutions.”

Jordan Schneider: This is how we’re going to start. Rewrite with Bach saying sarcastically to Mao, “Love all your revolutions. ” Alex, you’re Bach. Let’s go.

Alexander Boyd:  Love all of your revolutions, Chairman. Tossing the world upside down seems to be your favorite key signature.

Jordan Schneider: Upside down is where history finds its balance, Herr Bach. The masses must turn the old order on its head to set it upright.

Orville Schell: Now you’re talking like a robot, like a propaganda minister. I think Mao would say, “Tell me, Johann, what’s all this about Jesus? Why are you so obsessed with Jesus?” That would get Bach rolling. You remember when Clinton was in China, where he went into the Great Hall of the People for the press conference. At one point, Jiang Zemin, completely sui generis, said to Clinton, “Mr. President, I have a question. Why are so many Americans so interested in the Dalai Lama and Tibetan Buddhism?” He was speaking in Chinese. Of course, Clinton went on a tear. But I thought that was a sort of interesting question to ask. You can’t imagine Xi Jinping asking such a question.

Alexander Boyd: What did Clinton say?

Orville Schell: Clinton said something like, “Chairman Jiang, I think if you had a chance to meet the Dalai Lama, you’d really like him.” Jiang, who’d been off script and bantering in a very nice human way with Clinton, grabbed the podium and, as I recollect, he said, “With your permission, Mr. President, shall we close this section?”

Jordan Schneider: What are you reading right now?

Orville Schell: I’m reviewing this Torigan book for Foreign Affairs. I’ve also been reading William Shirer’s The Rise and Fall of the Third Reich, Timothy Ryback’s book about 1931 and ’32 in Germany, and a Robert Paxton book on fascism.

Jordan Schneider: Let’s talk about Rise and Fall of the Third Reich for a second. What stuck out to you about that book?

Orville Schell: I’m very curious where we are on this sort of scenario — how Germany headed off into fascism and the Third Reich. It’s pretty frightening when you look back at the various steps, at what happened and who didn’t say anything, who just shut up.

There’s a wonderful diary of Victor Klemperer, who was the cousin of a famous conductor. He kept a daily record of what happened. He was Jewish, his wife was Catholic, and he lived in Potsdam. They keep saying, “Surely something will happen, surely someone will come, and that can’t be it. Surely the Allies will come in.” Of course, they didn’t. We ended up with Hitler being elected Vice Chancellor, then we’re off to the races.

I’m very interested in how things slide into this state where you end up with an autocracy. Remember that Germany was the highest form of European civilization, and yet you ended up with Hitler.

Alexander Boyd: I’m also reading Hitler-specific these days. I’m reading Ian Kershaw’s two-part, two-volume biography of Hitler. I just finished Hubris and now I’m onto Nemesis.

Jordan Schneider: Orville, do you know Ian Kershaw? I’ve been trying to find his email address.

Orville Schell: I don’t know him but he would be great to get on and just walk him through the steps. There are some wonderful, wonderful books about that period that we need to know more about. Because you see how a slow erosion step by step, step by step with a kind of charismatic crackpot leader leading the charge and how it happens and how people just don’t rise to the occasion to stop it. They think, “Oh the courts will do it, oh something will do it,” but sometimes they don’t.

This is why I think comparing Trump to Xi is interesting and worthwhile doing. Although some of your more rigorous scholars may think there’s no data, no theoretical constructs, but for me it’s the heart of the matter. It has a lot to do with how people grow up. Autocratic leaders write themselves as very large — democratic leaders don’t have that opportunity as much. When you’re in big leader culture land, whether Putin, Kim Jong Un, Xi Jinping, Orban, whoever, it really matters who they are and where they came from and what their sort of operating system is, who installed it and when.

You can say fairly safely, although there are a lot of amazingly wonderful people in China — I have to say, and I married one — but the Cultural Revolution created massive amounts of personal, psychological, intellectual damage. It wasn’t just people got killed, people got in jail for a little while, and then Deng waved his wand and it was all over. That’s not how historical trauma works.

That’s why I find Torigan’s book so interesting. To his credit, he doesn’t do what I’ve just done, which is draw conclusions or try to draw gratuitous conclusions. He just tells the story. It’s a monumental job of research. You can draw your own conclusions, and that’s what I intend to do in Foreign Affairs.

Alexander Boyd: Any hints on those conclusions that are coming out soon?

Orville Schell: I want to make some surmises about what growing up in the Cultural Revolution meant to the formation of Xi Jinping, his form of governance today.

Alexander Boyd: According to the book, Xi Zhongxun, upon hearing of the Cultural Revolution, actually asked for his soul to be lit afire by it, which I found to be incredible research, obviously, on Torigan’s part to get this. Does that indicate that Xi Zhongxun, for whom the Party always came first, was unable fundamentally to connect with Mao because the Cultural Revolution was ongoing? He was already purged, but he yearned desperately for this. It’s kind of like a priest who doesn’t hear God’s voice calling. Is that a correct analysis?

Orville Schell: The Party — and Zhou Enlai suffered from this too — they all did. Some of them did have a sense that something was deeply awry. But there was no other show in town except the Party and the Revolution. They were veteran revolutionaries.

Xi Zhongxun, no matter what they did to him, and what they did to him was pretty horrendous, though not the worst, he never lost his belief in the Revolution and the Party. That’s what he imbued his son with. Yes, bad things happen. We can’t have chaos again. But the party is fundamentally right. The revolution cannot be questioned.

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It’s a classic case of where people have no other place to turn except run off into the hills if you can. And we see this in our own government now. People desperately wanting to be in the limelight, in power, in government. And they have all kinds of rationalizations. Rubio, my God, he used to think Trump was a buffoon. Now he’s sold his soul. Read Doctor Faustus.

Jordan Schneider: My favorite line with Rubio is there’s an old New Yorker profile of him where he reads The Last Lion, the Churchill biography. And he said he read it twice and that he saw himself as Churchill, like warning about the Nazis. The analogy was Iran getting the bomb or something. But to go from that to where we are today is something.

Orville Schell: Power is an incredible intoxicant. Once you get that needle in your arm, that’s your currency and that’s your realm. It’s very hard to imagine what else you’re going to do with yourself. That’s why as a writer, I’ve always said, “No, not going there.” I’m just going to stay a lowly scribe. I don’t even particularly yearn to go to China now because I know if I did yearn to go, that would circumscribe me, it would make me feel I couldn’t say certain things because I’d know there’d be consequences.

I told you this, Jordan. In 1991, I did a year-long project with 60 Minutes on forced labor and the Laogai system. It aired. It was incredible. We got into prison camps. I kept a diary of it, and I edited it and sent it to The New Yorker. They edited it and were about to go into print and I looked at it and said, “I can’t publish this.” I was a younger man, I had a Chinese wife, and I had parents-in-law in China. I threw it in a box.

I pulled it out two years ago and thought, “My God, the question of forced labor in Xinjiang is more relevant than ever.” I took it out. That will be the end of me in terms of grace from the Chinese Communist Party. But that’s okay. I’d rather that than I can’t write and say what I think. I think I was right to put it in a box then. But that’s not a healthy tendency for any society. You remember chōutì wénxué (抽屉文学), “drawer literature,” things that people could only write and put in a drawer.

Jordan Schneider: Benjamin Nathan just won the Pulitzer Prize for this really awesome book To the Success of Our Hopeless Cause: The Many Lives of the Soviet Dissident Movement, which folks should also read.

Orville Schell: Perry Link is sort of the avatar of the Chinese version of that. I recommend his book on Liu Xiaobo, and he’s just written another book, The Anaconda in the Chandelier. I think that’s a really important question.

 You know, intellectuals are poor, weak creatures, and those who stand up — read Blood Letters. Alex, will you send Jordan the Elaine Pagels program we did on the comparison of Jesus and Lin Zhao? We had them both on stage talking about the role that faith plays in adversity and revolution. We started off with Bach, a beautiful aria. I wanted Bach as the avatar of being in the mix. You’ll enjoy this, Jordan.

Jordan Schneider: All right, well, we’ll put it in the show notes as well.

Orville Schell: It’s hard to explain to people, but if you watch it, you’ll understand.

Alexander Boyd: On Orville’s note on publishing and not publishing, we just published an excerpt from Perry Link’s forthcoming book, The Anaconda in the Chandelier.

Jordan Schneider: All right, thanks so much for being a part of ChinaTalk, Orville.

Orville Schell: As always, it’s a great pleasure. You have a great program, Jordan.

of the substack did an excellent job writing up the key dynamics of the deal. I’ll be running excerpts from his post with some comments of mine interspersed.

Our government, having withdrawn the new diffusion rules, has now announced an agreement to sell massive numbers of highly advanced AI chips to UAE and Saudi Arabia (KSA). This post analyzes that deal and that decision.

It is possible, given sufficiently strong agreement details (which are not yet public and may not be finalized) and private unvoiced considerations, that this deal contains sufficient safeguards and justifications that, absent ability to fix other American policy failures, this decision is superior to the available alternatives. Perhaps these are good deals, with sufficiently strong security arrangements that will actually stick.

Perhaps UAE and KSA are more important markets and general partners than we realize, and the rest of the world really is unable to deploy capital and electrical power the way they can and there is nothing we can do to change this, and perhaps they have other points of strategic importance, so we have to deal with them. Perhaps they are reliable American allies going forward who wouldn’t use this as leverage, for reasons I do not understand. There are potential worlds where this makes sense.

The fact remains that the case being made for this deal, in public, actively makes the situation seem worse. David Sacks in particular is doubling down and extending the rhetoric I pushed back against last week, when I targeted Obvious Nonsense in AI diffusion discourse. Even within the White House, the China hawks are questioning this deal, and Sacks responded by claiming to not even understand their objections and to all but accuse such people of being traitorous decels wearing trench coats.

I stand by my statements last week that even if accept the premise that all we need care about are ‘America wins the AI race’ and how we must ‘beat China,’ our government’s policies, on diffusion and elsewhere, seem determined to lose an AI race against China.

The Central Points From Last Week

The point of the diffusion rules is to keep the AI chips secure and out of Chinese hands, both in terms of physical security and use of their compute via remote access. It is possible that the agreements we are making with UAE and KSA will replace and improve upon the functionality, in those countries in particular, of the diffusion rules.

It’s not about a particular set of rules. It is about the effect of those rules. Give me a better way to get the same effect, and I’m happy to take it. When I say ‘something similar’ below, I mean in the sense of sufficient safeguards against the diversion of either the physical AI chips or the compute from the AI chips. Access to those chips is what matters most. Whereas market share in selling AI chips is not something I am inclined to worry about except in my role as Nvidia shareholder.

I do not consider them reliable allies going forward, and there are various reasons that even the best version of these agreements would make me deeply uncomfortable, but it is possible to reach an agreement that physically locates many data centers in the Middle East and lets them reap the financial benefits of their investments and have compute available for local use, but does not in the most meaningful senses ‘hand them’ the compute in question. As in, no I do not trust them, but we could find a way that we do not have to, if they were fully open to whatever it took to make that happen.

I also would highlight the implicit claim I made here, that the pool of American advanced AI chips is essentially fixed, and that we have sufficient funding available in Big Tech to buy all of them indefinitely. If that is not true, then the UAE/KSA money matters a lot more. Then there is the similar question of whether we were going to actually run out of available electrical power with no way to get around that. A lot of the question comes down to: What would have counterfactually happened to those chips? Would we have been unable to deploy them?

[Jordan: See ChinaTalk’s recent coverage of an excellent IFP report that explored what a policy agenda to rapidly increase the energy available for AI deployment would look like]

With that in mind, here are the central points I highlighted last week:

1. America is ahead of China in AI.

2. Diffusion rules serve to protect America’s technological lead where it matters.

3. UAE, Qatar and Saudi Arabia are not reliable American allies, nor are they important markets for our technology. We should not be handing them large shares of the world’s most valuable resource, compute.

4. The exact diffusion rule is gone but something similar must take its place, to do otherwise would be how America ‘loses the AI race.’

5. Not having any meaningful regulations at all on AI, or ‘building machines that are smarter and more capable than humans,’ is not a good idea, nor would it mean America would ‘lose the AI race.’

6. AI is currently virtually unregulated as a distinct entity, so ‘repeal 10 regulations for every one you add’ is to not regulate at all building machines that are soon likely to be smarter and more capable than humans, or anything else either.

7. ‘Winning the AI race’ is about racing to superintelligence. It is not about who gets to build the GPU. The reason to ‘win’ the ‘race’ is not market share in selling big tech solutions. It is especially not about who gets to sell others the AI chips.

8. If we care about American dominance in global markets, including tech markets, stop talking about how what we need to do is not regulate AI, and start talking about the things that will actually help us, or at least stop doing the things that actively hurt us and could actually make us lose.

Diffusion Controls Have Proven Vital

Diffusion controls on AI chips we’ve enforced on China so far have had a huge impact. DeepSeek put out a highly impressive AI model, but by their own statements they were severely handicapped by lack of compute. Chinese adoption of AI is also greatly held back by lack of inference compute.

China is competing in spite of this severe disadvantage. It is vital that we hold their feet to the fire on this. China has an acute chip shortage, because it physically cannot make more AI chips, so any chips it would ship to a place like UAE or KSA would each be one less chip available in China.

Whenever you see arguments from David Sacks and others against AI diffusion rules, ask the question:

1. Is an argument for a different set of export controls and a different chip regime that still protects against China getting large quantities of advanced AI chips?

2. Or is it an argument, as it often is, that to preserve our edge in compute we should sell off our compute, that to preserve our edge in tech we should give away our edge in tech?

   1. As in, that what matters is our market share of AI chips, not who uses them?

   2. This is not a strawman, for example Ben Thompson argues exactly this very explicitly and repeatedly. Ben Thompson’s recent interview with Jensen Huang, CEO of Nvidia, made it clear both of them have this exact position. That to maintain America’s edge in AI, we need to sell our AI chips to whoever wants them, including China, because ‘China will not be held back’ as if having a lot more chips wouldn’t have helped them. And essentially saying that all Nvidia chips everywhere support the ‘American tech stack’ rather than China rather obviously turning around and using them for their own tech. He explicitly is yelling we need to ‘compete in China’ or else.

   3. Complete Obvious Nonsense talking of his own book, which one must remind oneself is indeed his job, what were you really expecting him to say? Well, what he is saying is that the way we ‘lose the AI race’ is someone builds a CUDA alternative or steals Nvidia market share. That his market is what matters. It’s full text. Not remotely a strawman.

I would disagree with arguments of form #2 in the strongest possible terms. If it’s arguments of form #1, we can talk about it.

It’s a Huge Deal

We should keep these facts in mind as we analyze the fact that the United States has signed a preliminary chip deal with the UAE. There is a 5GW AUE-US AI campus planned, and is taking similar action in Saudi Arabia. The deals were negotiated by a team led by David Sacks and Sriram Krishnan.

Lennart Heim: To put the new 5GW AI campus in Abu Dhabi (UAE) into perspective. It would support up to 2.5 million NVIDIA B200s.

That's bigger than all other major AI infrastructure announcements we've seen so far.

In exchange for access to our chips, we get what are claimed to be strong protections against chip diversion, and promises of what I understand to be a total of $200 billion in investments by the UAE. That dollar figure is counting things like aluminum, petroleum, airplanes, Qualcomm and so on. It is unclear how much of that is new.

The part of the deal that matters is that a majority of the UAE investment in data centers has to happen here in America.

I notice that I am skeptical that all the huge numbers cited in the various investment ‘deals’ we keep making will end up as actual on-the-ground investments. As in:

Walter Bloomberg: UAE PRESIDENT SAYS UAE TO INVEST $1.4T IN U.S OVER NEXT 10 YEARS

At best there presumably is some creative accounting and political symbolism involved in such statements. Current UAE foreign-direct-investment stock in the USA is only $38 billion, their combined wealth funds only have $1.9 trillion total. We can at best treat $1.4 trillion as an aspiration, an upper bound scenario. If we get the $200 billion we should consider that a win, although if the deal is effectively ‘all your investments broadly are in the West and not in China’ then that would indeed be a substantial amount of funds.

Nor is this an isolated incident. The Administration is constantly harping huge numbers, claiming to have brought in $14 trillion in new investment, including $4 trillion from the recent trip to Arabia, or roughly half of America’s GDP.

Jason Furman (top economic advisor, Obama White House): That’s nuts and baseless. I doubt the press releases even add up to that. But, regardless, press releases are a terrible way to determine the investment or the impact of his policies on it.

Justin Wolfers: Trump has claimed a $1.2 trillion investment deal from Qatar. Qatar’s annual GDP is a bit less than $250 billion per year. So he’s claiming an investment that would require every dollar every Qatari earned over the next five years.

UAE’s MGX will also be opening Europe’s largest data center in France, together with Nvidia, an 8.5 billion Euro investment, first phase to be operational in 2028. This has been in the works for a while.

Do You Feel Secure?

Not that the numbers ultimately matter all that much. What does matter is: How will we ensure the chips don’t fall literally or functionally into Chinese hands?

It comes down to the security provisions and who is going to effectively have access to and run all this compute. I don’t see here any laying out of the supposed tough security provisions.

Without going into details, if the agreements on both physical and digital security are indeed implemented in a way that is sufficiently tough and robust, if we are the ones who both physically and digitally control and monitor things on a level at least as high as domestically, and can actually have confidence none of this will get diverted, then that goes a long way.

We don’t yet have enough of that information to say.

The public explanations for the deal, and the public statements about what safety precautions are considered necessary, do not bring comfort.

I very much do not like comments like this, made in response to the Bloomberg piece above.

David Sacks (US AI Czar): If the concern [about the deal] is about diversion of advanced semiconductors to China, that’s an important policy objective but one that is easily addressed with a security agreement and a “trust but verify” approach. Modern AI supercomputers are 8 feet tall and weigh two tons; these are not like diamonds smuggled in a briefcase. To verify that chips are where they’re supposed to be, an auditor can just visit the data center and count server racks.

Semianalysis: As such, physical inspections are key to ensuring the GPUs are where they are supposed to be. The White House is aware of the risks and is prepared to ensure the chips are where they are supposed to be. As Bloomberg reported (quotes David Sacks’s statement above).

I’m sorry, what? You can ‘just visit the data center and count server racks’?

It terrifies me to see so many people arguing for the deal explicitly saying that this is a good statement, rather than a terrifying statement that we are hoping no one involved in the actual work believes to be true.

[Jordan: In 2022 I did a show with Kevin Wolf, the former head of BIS, who mentioned off-hand that there were literally only two people Commerce had in China to do site inspections. Since then BIS’ budget has barely budged and faced DOGE cuts in the early days of this administration. There is not the capacity to do datacenter inspections in a serious way today.]

Jordan Schneider: Let's start with the last thing first. This 60-day unverified list: is there a potential that the impact of this could actually be a lot bigger than what we currently see, if some of these big names on the unverified entity list end up graduating to full entity-list status?

Kevin Wolf: It's really up to the Chinese government. If they allow access, give the information that the Commerce Department is seeking, and allow the two people in China that do inspections and site visits to do their jobs…

Jordan Schneider: Whoa, wait, two? There are, like, 30 firms on there!

Kevin Wolf: Yeah, I know, but no other country has any, and the Commerce Department is the only export control organization on the planet with its own enforcement agents who are subject matter experts in export controls.

I think diversion via remote access is far more likely than physical diversion, and this response does not address the remote access issue at all, but even simply treating this as a physical diversion issue, o3, is the quoted statement accurate?

o3 (full one shot, full response quoted, in response to literally quoting Sacks without attribution and asking ‘is this accurate?’):

Short version: Mostly wrong. Chips are tiny and high-value, so diversion is hard to stop with “count the racks.” Physical audits help but they are far from sufficient.

Why “just count server racks” fails

1. High value-to-weight ratio.
   At ~$30 k per H100, a single 20 kg carry-on full of GPUs is > $1 m. That’s an attractive target. Racks are heavy; the payload isn’t.

2. Modularity.
   GPUs slide out in minutes. An auditor sees the enclosure; they cannot tell if the trays were swapped yesterday or will be tomorrow. Dummy blanks cost <$10.

3. Front companies & trans-shipping.
   Chips often leave the compliant data-center before any inspection window. Paperwork shows them installed; reality changes after the auditor flies home.

4. Remote lease risk.
   Even if the hardware stays in the U.S., Chinese entities can simply rent time on it. Export-control rules treat “deemed exports” (remote access by restricted users) as violations.

5. Limited audit frequency & competence.
   Meaningful verification requires random, intrusive, technically savvy inspections plus cryptographic attestation of firmware. Counting racks is neither.

Bottom-line probability estimate

My best estimate: ≤ 30 % that “security agreement + occasional rack counting” alone keeps advanced GPUs out of China for > 3 years. ≥ 70 % that significant leakage continues absent tighter controls (HW tracking, cryptographic attestation, and supply-chain tagging).

So the quoted claim is misleading: rack-level audits are helpful but nowhere near “easily addresses” the diversion problem.

When I asked how many chips would likely be diverted from a G42 data center if this was the security regime, o3’s 90% confidence interval was 5%-50%. Note that the G42 data center is 20% of the total compute here, so if we generously assume no physical diversion risk in the other 80%, that’s 1%-10% of all compute we deploy in the UAE.

Is that acceptable? The optimal amount of chip diversion is not zero. But I think this level of diversion would be a big deal, and the bigger concern is remote access.

I want to presume, for overdetermined reasons, that Sacks’s statement was written without due consideration or it does not reflect his actual views, and we would not actually make this level of dumb mistake where they could literally just swap the chips out for dummy chips. I presume we are planning to use vastly superior and more effective precautions against chip diversion and also have a plan for robust monitoring of compute use to prevent remote access diversion.

But how can we trust an administration to take such issues seriously, if their AI Czar is not taking this even a little bit seriously? This is not a one time incident. Similar statements keep coming. That’s why I spent a whole post responding to them.

David Sacks is also quoted extensively directly in the Bloomberg piece, and is repeatedly very dismissive of worried about diversion of chips or of compute, saying it is a fake argument and an easy problem to solve, and he talks about these as if they were reliable American allies in ways I do not believe are accurate.

Sacks also continues to appear to view winning AI to be largely about selling AI chips. As in, if G42, an Abu Dhabi-based AI firm, is using American AI chips, then it essentially ‘counts as American’ for purposes of ‘winning,’ or similar. I don’t think that is how this works, or that this is a good use of a million H100s. Bloomberg reports 80% of chips headed to the UAE would go to US companies, 20% to G42.

I very much want us to think about the actual physical consequences of various actions, not what those actions symbolize or look like. I do think, despite everything else, it is a very good sign that David Sacks is ‘urging people to read the fine print.’ This is moderated by the fact that we do not have the fine print, so we can’t read it. The true good news there requires one to read all that fine print, and one also should not assume that the fine print will get implemented. Nor do we yet have access to what the actual fine print says, so we cannot read it.

Semianalysis Defends the Deal

Dylan Patel and others at Semianalysis offer a robust defense of the deal, saying clearly that ‘America wins’ and that this benefits American AI infrastructure suppliers on all levels, including AI labs and cloud providers.

They focus on three benefits: money, tying KSA/UAE to our tech stack, and electrical power, and warn of the need for proper security, including model weight security, a point I appreciated them highlighting.

Those seem like the right places to focus, and the right questions to ask. How much of their money is really up for grabs and how much does it matter? To what extent does this meaningfully tie UAE/KSA to America and how much does that matter? How much do we need their ability to provide electrical power? How will the security arrangements work, will they be effective, and who will effectively be in charge and have what leverage?

Specifically, on their three central points:

1. They call this macro, but a better term would be money. UAE and KSA (Saudi Arabia) can make it rain, a ‘trillion-dollar floodgate.’ This raises two questions.

   1. Question one: Was American AI ‘funding constrained’? The big tech companies were already putting in a combined hundreds of billions a year. Companies like xAI can easily raise funds to build giant data centers. If Google, Amazon, Apple, Meta or Microsoft wanted to invest more, are they really about to run out of available funding? Are there enough more chips available to be bought to run us out of cash?

   2. Semianalysis seems to think we should be worried about willingness of American companies to invest here and thinks we will have trouble with the financing.

   3. I am not convinced of this. Have you seen what these companies (don’t have to) pay on corporate bonds? Did we need to bring in outside investors? Should we even want to, given these investments look likely to pay off?

   4. This is a major crux. If indeed American big tech companies are funding constrained in their AI investments, then the money matters a lot more. Whereas if we were already capable of buying up all the chips, that very much cuts the other way.

   5. Question two: As we discussed earlier, is the trillion-dollar number real? We keep seeing these eye-popping headline investment numbers, but they don’t seem that anchored to reality, and seem to include all forms of investment including not AI, although of course other foreign direct investment is welcome.

   6. Do their investments in US datacenters mean anything, and are they even something we want, given that the limiting factor driving all this is either constraints on chip availability or on electrical power? Will this be crowding out other providers?

   7. If these deals are so positive for American tech companies, why didn’t the stock market moves reflect this? No, I will not accept ‘priced in.’

2. They call this geopolitical, that UAE and KSA are now tied to American technology stacks.

   1. As they say, ‘if Washington enforces tight security protocols.’ We will see. David Sacks is explicitly dismissing the need for tight security protocols.

   2. Classically, as Trump knows well, when the bank loans you a large enough amount and you don’t pay it back, it is the bank that has the problem. Who is being tied to whose stack? They will be able to at least cut the power any time. It is not clear from public info what other security will be present and what happens if they decide to turn on us, or use that threat as leverage. Can they take our chips and their talents elsewhere?

   3. This can almost be looked at as a deal with one corporation. G42 seems like it’s going to effectively be on the UAE side of the deal, and it is going to have a lot of chips in a lot of places. A key question is, to what extent do we have the leverage on and control over G42, and to what extent does this mean they will act as a de facto American tech company and ally? How much can we trust that our interests will continue to align? Who will be dependent on who? Will our security protocols extend to their African and European outposts?

   4. Why does buying a bunch of our chips tie them into the rest of our stack? My technical understand is that it doesn’t. They’re only tied to the extent that they agreed to be tied as part of the deal (again, details unknown), and they could swap out that part at any time. In my experience you can change which AI your program uses by changing a few lines of code, and people often do.

   5. It is not obvious why KSA and UAE using our software or tech stack is important to us other than because they are about to have all these chips. These aren’t exactly huge markets. If the argument is they have oversized effect on lots of other markets, we need to hear this case made out loud.

   6. Seminanalysis points out China doesn’t even have the capacity to sell its own AI chips yet. And I am confused about the perspectives here on ‘market share’ and the implied expectations about customer lock-in.

3. They call this infrastructure, I’d simply call it (electrical) power. This is the clearly valuable thing we are getting. It’s rather crazy that ‘put our most strategic asset except maybe nukes into the UAE and KSA’ was chosen over ‘overrule permitting rules and build some power plants or convince one of our closer allies to do it’ but here we are.

   1. So the question here is, what are the alternatives? How acute is the shortage going to be and was there no one else capable of addressing it?

   2. Also, even if we do have to make this deal now, this is screaming from the rooftops, we need to build up more electrical power everywhere else now, so we don’t have this constraint again in the future.

Semianalysis also raises the concern about model weight security, but essentially think this is solvable via funding work to develop countermeasures and use of red teaming, plus defense in depth. It’s great to see this concern raised explicitly, as it is another real worry. Yes, we could do work to mitigate it and impose good security protocols, and keep the models from running in places and ways that create this danger, but will we? I don’t know. Failure here would be catastrophic.

Understanding the China Hawks

There are also other concerns even if we successfully retain physical and digital control over the chips. The more we place AI chips and other strategic AI assets there, the more we are turning UAE, Saudi Arabia and potentially Qatar into major AI players, granting them leverage I believe they can and will use for various purposes.

David Sacks continues to claim to not understand that others think that ‘winning AI’ is mostly not about who gets to sell chips, who uses our models and picks up market share, or about superficially ‘winning’ ‘deals.’

He not only thinks it is about market penetration, he can’t imagine an alternative. He doesn’t understand that many, including myself, this is about who has compute and who gets superintelligence, and about the need for proper security.

David Sacks: I’m genuinely perplexed how any self-proclaimed “China Hawk” can claim that President Trump’s AI deals with UAE and Saudi Arabia aren’t hugely beneficial for the United States. As leading semiconductor analyst Dylan Patel observed, these deals “will noticeably shift the balance of power” in America’s favor. The only question you need to ask is: does China wish it had made these deals? Yes of course it does. But President Trump got there first and beat them to the punch.

Sam Altman: this was an extremely smart thing for you all to do and i’m sorry naive people are giving you grief.

Tripp Mickle and Ana Swanson (NYT): One Trump administration official, who declined to be named because he was not authorized to speak publicly, said that with the G42 deal, American policymakers were making a choice that could mean the most powerful A.I. training facility in 2029 would be in the United Arab Emirates, rather than the United States. [Jordan: this is a wild line to be giving to the NY Times—I thought all the China hawks already got purged!]

But Trump officials worried that if the United States continued to limit the Emirates’ access to American technology, the Persian Gulf nation would try Chinese alternatives.

The hawks are concerned, because the hawks largely do not think that the key question is who will get to sell chips, but rather who gets to buy them and use them. This is especially true given that both America and China are producing as many top AI chips as they can, us far more successfully, and there is more than enough demand for both of them. One must think on the margin.

Given that so many China hawks are indeed on record doubting this deal, if you are perplexed by this I suggest reading their explanations. Here is one example.

Tripp Mickle and Ana Swanson (NYT): Mr. Goodrich said the United States still had the best A.I. engineers, companies and chips and should look for ways to speed up permitting and improve its energy grid to hold on to that expertise. Setting up some of the world’s largest data centers in the Middle East risks turning the Gulf States, or even China, into A.I. rivals, he said.

“We’ve seen this movie before and we should not repeat it,” Mr. Goodrich said.

Sam Winter-Levy, a fellow at the Carnegie Endowment for International Peace, said the huge chip sales did “not feel consistent with an America First approach to A.I. policy or industrial policy.”

“Why would we want to offshore the infrastructure that will underpin the key industrial technology of the coming years?” he asked.

This does not seem like a difficult position to understand? There are of course also other reasons to oppose such deals.

Here is Jordan Schneider of China Talk’s response, in which he is having absolutely none of it, explicitly rejecting that either America or China has chips to spare for this. rejecting that UAE and KSA are actual allies, not expecting us to follow through with reasonable security precautions, and saying if we wanted to do this anyway we could have held out for a better deal with more control than this, I don’t know why you would be confused how someone could have this reaction based on the publicly available information:

Jordan Schneider: It’s going to cannibalize US build-out and leave the world with three independent power-centers of AI hardware where we could’ve stuck to our guns, done more power generation at home, and only had China to deal with not these wild-card countries that are not actual allies. If this really is as important as we believe, why are we letting these countries and companies we deeply distrust get access to it?

The Gulf’s BATNA wasn’t Huawei chips, it was no chips. Whatever we’re trying to negotiate for, we can play harder to get. BIS can just say they can’t buy Ascends and it’s not like there’s enough capacity domestically in China to service global demand absent the TSMC loophole they charged through. Plus, we’re offering to sell them 10× the chips that Huawei could conceivably sell them anytime soon even if they use the TSMC-fabbed wafers.

Where’s the art-of-the-deal energy here? Right now I only see AMD and NVDA shareholders as well as Sama benefiting from all of this. I thought we wanted to raise revenue from tariffs? Why not charge 3× the market rate and put the premium into the US Treasury, some “Make America Great Again” industrial-development fund, use it to triple BIS’ budget so they can actually enforce the security side, put them on the hook for Gaza…I don't know literally anything you care about. How about a commitment not to invest in Chinese tech firms? Do we still care about advanced logic made in America? How about we only let them buy chips fabbed in the US, fixing the demand-side problem and forcing NVDA to teach Intel how to not suck.

Speaking of charging through loopholes, all of the security issues Dylan raises in his article I have, generously, 15 % confidence in USG being able to resolve/resist industry and politicians when they push back. If it’s so simple to just count the servers, why hasn’t BIS already done it / been able to fight upstream industry lobbying to update the chips-and-SME regs to stop Chinese build-outs and chip acquisition? What happens when the Trump gets a call from the King when some bureaucrat is trying to stop shipments because they see diversion if they ever catch it in the first place?

Why are we doing anything with G42 again? Fine, if you really decide you want to sell chips to the UAE, at the very least give American hyperscalers the off-switch. It’s not like they would’ve walked away from that offer! America has a ton to lose in the medium term from creating another cloud provider that can service at scale, saying nothing of one that has some deeply-discomforting China ties pretty obvious even to me sitting here having never gotten classified briefings on the topic.

Do the deal’s details and various private or unvoiced considerations make this deal better than it looks and answer many of these concerns? Could this be sufficient that, if looked at purely through the lens of American strategic interests, this deal was a win versus the salient alternatives? Again: That is all certainly possible!

Our negotiating position could have been worse than Jordan believes. We could have gotten important things for America we aren’t mentioning yet. The administration could have limited room to maneuver including by being divided against itself or against Congress on this. On the flip side, there are some potentially uncharitable explanations for all of this, that would be reasonable to consider.

Rhetoric Unbecoming

Instead of understanding and engaging with such concerns and working to allay them, Sacks has repeatedly decided to make this a mask off moment, and engage in a response that I would expect on something like the All-In Podcast or in a Twitter beef, but which is unbecoming of his office and responsibilities, with multiple baseless vibe and ad hominem attacks at once that reflect that he either is willfully ignorant of the views, goals and beliefs of those he is attacking and even who they actually are, or he is lying and does not care, or both, and a failure to take seriously the concerns and objections being raised. Here is another illustration of this:

David Sacks (May 17): After the Sam Bankrun-Fraud fiasco, it was necessary for the Effective Altruists to rebrand. So they are trying to position themselves as “China Hawks.” But their tech deceleration agenda is the same, and it would cost America the AI race with China.

There are multiple other people I often disagree with on important questions but whom I greatly respect who are working on in administration on AI policy. There are good arguments you can make in defense of this deal. Instead of making those arguments in public, we repeatedly get this.

Everything Sacks says seems to be about vibes and implications first and actual factual claims a distant second at best. He doesn’t logically say ‘all so-called China hawks who don’t agree with me are secret effective altruists in trench coats and also decels who hate all technology and all of humanity and also America,’ but you better believe that’s the impression he’s going for here.

Could China Have ‘Done This Deal’?

Would China have preferred to ‘do this deal’ instead? That at best assumes facts, and arguments, not in evidence. It depends what they would get out of such a deal, and what we’re getting out of ours, and also the security arrangements and whether we’ve formed a long lasting relationship in which we hold the cards.

I’m also not even sure what it would mean for China to have ‘done this deal,’ it does not have what we are offering. Semianalysis says they don’t have similar quantities of chips to sell, and might not have any, nor are their chips of similar quality.

I do agree China would have liked to ‘do a deal’ in some general sense, where they bring UAE/KSA into their orbit, on AI and otherwise, although they don’t need access to electrical power. More capital and friends are always helpful. It’s not clear what that deal would have looked like.

[Jordan: the fact that the administration is citing some old news of Huawei promising to gift just $75m in chips to the Malaysian government (and not even today! Over two years!) is policy malpractice. Plus, this administration just made clear that using Huawei Ascend chips violates US export controls, giving America an enormously powerful lever to dissuade fence-sitting countries not to buy into what is already an inferior tech offering.]

Tyler Cowen Asks Good Questions

Here’s Tyler Cowen being clear eyed about some of what we are selling so cheap. The most powerful AI training facility could be in the UAE, and you’re laughing?

Tyler Cowen: Of course Saudi and the UAE have plenty of energy, including oil, solar, and the ability to put up nuclear quickly. We can all agree that it might be better to put these data centers on US territory, but of course the NIMBYs will not let us build at the required speeds. Not doing these deals could mean ceding superintelligence capabilities to China first. Or letting other parties move in and take advantage of the abilities of the Gulf states to build out energy supplies quickly.

Energy and ability to overcome NIMBYs is only that which is scarce because America is refusing to rise to this challenge and actually enable more power generation. Seriously, is there nowhere in America we can make this happen at scale? If we wanted to, we could do this ourselves easily. We have the natural gas, even if nuclear would be too slow to come online. It is a policy choice not to clear the way. And no, I see zero evidence that we are pulling out the stops here and coming up short.

I think this frame is exactly correct - that this deal makes sense if and only if all of:

1. The security deal is robust and we retain functional control over where the compute goes.

2. We trust our friends here to remain our friends at a reasonable price.

3. We counterfactually would not have been able to buy these chips and build data centers to power these chips.

As far as I can tell China already has all the power it needs to power any AI chips it can produce, it is using them all, and its chip efforts are not funding constrained.

So for want of electrical power, and for a few dollars, we are handing over a large amount of influence over the future to authoritarian powers with very different priorities and values?

Tyler Cowen: In any case, imagine that soon the world’s smartest and wisest philosopher will soon again be in Arabic lands.

We seem to be moving to a world where there will be four major AI powers — adding Saudi and UAE — rather than just two, namely the US and China. But if energy is what is scarce here, perhaps we were headed for additional AI powers anyway, and best for the US to be in on the deal?

Who really will have de facto final rights of control in these deals? Plug pulling abilities? What will the actual balance of power and influence look like? Exactly what role will the US private sector play? Will Saudi and the UAE then have to procure nuclear weapons to guard the highly valuable data centers? Will Saudi and the UAE simply become the most powerful and influential nations in the Middle East and perhaps somewhat beyond?

Yes. Those are indeed many of the right questions, once you think security is solid. Who is in charge of these data centers in the ways that matter? Won’t they at minimum have the ability to cut the power at any time? Who gets to decide where the compute goes? What are they going to do with all this leverage we are handing them?

Is this what it means to have the future be based on American or Democratic values? Do you like ‘the values’ of the UAE and Saudi Arabian authorities?

Tyler Cowen: I don’t have the answers to those questions. If I were president I suppose I would be doing these deals, but it is very difficult to analyze all of the relevant factors. The variance of outcomes is large, and I have very little confidence in anyone’s judgments here, my own included.

Few people are shrieking about this, either positively or negatively, but it could be the series of decisions that settles our final opinion of the second Trump presidency.

The administration thinks that the compute in question will remain under the indefinitely control of American tech companies, to be directed as we wish.

Sriram Krishnan: Reflecting on what has been an amazing week and a key step in global American AI dominance under President Trump.

These Middle East AI partnerships are historic and this “AI diplomacy” will help lock in the American tech stack in the region, help American companies expand there while also building infrastructure back in the U.S to continue expanding our compute capacity.

This happens on top of rigorous security guarantees to stop diversion or unauthorized access of our technology.

More broadly this helps pull the region closer to the U.S and aligns our technological interests in a very key moment for AI.

It’s a very exciting moment and a key milestone.

I hope that they are right about this, but I notice that I share Tyler’s worry that they are wrong.

Saudi Arabia Also Made a Deal

Similarly, Saudi Arabia’s Humain is going to get ‘several hundred thousand’ of Nvidia’s most advanced processors, starting with 18k GB300 Grace Blackwells.

The justification given for rescinding the Biden diffusion rules is primarily that failure to do this would have ‘weakened diplomatic relations with dozens of countries by downgrading them to second-tier status.’

But, well, not to reiterate everything I said last week, but on that note I have news.

One, we’re weakening diplomatic relations with essentially all countries in a series of unforced errors elsewhere, and we could stop.

[Jordan: that feeling when you treat Dubai better than Canada]

Two, most of the listed tier two countries have always had second-tier status. There’s a reason Saudi Arabia isn’t in Five Eyes or NATO. We can talk price about which countries should have which status, but no our relations are not all created equal, not when it comes to strategically vital national interests and to deep trust. I don’t share Sacks’s stated view that these are some of our closest and most trustworthy allies. Why does this administration seem to always want to make its deals mostly with authoritarian regimes, usually in places where Trump has financial ties?

Tripp Mickle and Ana Swanson (NY Times): The announcements of the two deals follow reports that $2 billion has flowed to Trump companies over the last month from the Middle East, including a Saudi-backed investment in Trump’s cryptocurrency and plans for a new presidential airplane from Qatar.

There’s always Trust But Verify. The best solution, if you can’t trust, is often to set up things so that you don’t have to. This can largely be done. Will we do it? And what will we get in return? What is announced mostly seems to be investments and purchases, that what we are getting are dollars, and Bloomberg is skeptical of the stated dollar amounts.

At Best A Second Best Solution

This deal is very much not a first best solution. It is, at best, a move that we are forced into on the margin due to our massive unforced errors in a variety of other realms. Even if it makes sense to do this, it makes even more sense to be addressing and fixing those other critical mistakes.

Electrical power is the most glaring in the context of this particular. There needs to be national emergency level focus on America’s inability to build electrical power capacity. Where are the special compute zones? Where are the categorical exemptions? Where is DOGE with regard to the NRC? Where is the push for real reform on any of these fronts? Instead, we see story after story of Congress actively moving to withdraw even the supports that are already there, including plans to outright abrogate contracts on existing projects.

The other very glaring issue is trade policy. If we think it is this vital to maintain trade alliances and open up markets, and maintaining market share, why are we otherwise going in the opposite direction? Why are we alienating most of our allies? And so on.

The argument for this deal is, essentially, that it must be considered in isolation. That other stuff is someone else’s department, and we can only work with what we have. But this is a very bitter pill to be asked to swallow, especially as Sacks himself has spoken out quite loudly in favor of many of those same anti-helpful policies, and the others he seems to be sitting out. You can argue that he needs to maintain his political position, but if that also rules out advocating for electrical power generation and permitting reform, what are we even doing?

If we swallow the entire pill, and consider these deals only on the margin, without any ability to impact any of our other decisions, and only with respect to ‘beating China’ and ability to ‘win the AI race,’ and assume fully good faith and set aside all the poor arguments and consider only the steelman case, we can ask: Do these deals help us?

I believe that such a deal is justifiable, again on the margin and regarding our position with respect to China, if and only if ALL of the following are true:

1. Security arrangements are robust, the chips actually do remain under our physical control and we actually do determine what happens with the compute. And things are set up such that America retains the leverage, and we can count on UAE/KSA to remain our friends going forward.

2. This was essentially the best deal we could have gotten.

3. This represents a major shift in our or China’s ability to stand up advanced AI chips, because for the bulk of these chips either Big Tech would have run out of money, or we would have been unable to source the necessary electrical power, or China has surplus advanced AI chips I was not previously aware of and no way to deploy them.

4. Entering into these partnerships is more diplomatically impactful, and these friendships are more valuable, than they appear to me based on public info.

Check out some ChinaTalk coverage from least year about China’s Middle East AI ambitions.

Mood Music

What does the future of industrial policy in America look like, and what state capacity investments are needed to get there? How does China factor into the future of the U.S. semiconductor industry? And what do government affairs offices actually do? To explore these questions, we’re concluding our CSIS Chip Chat series with Bruce Andrews. Bruce has had a long career on Capitol Hill, led government affairs for Ford, served as Deputy Secretary of Commerce under President Obama, and most recently headed up government affairs at Intel. He’s now a fellow at CSIS.

We discuss…

• How to bring expertise and legislating back to Capitol Hill,

• The case for a new “Department of Competitiveness”

• Industry’s role in policymaking and what it took to get semiconductor manufacturers on board with the CHIPS Act,

• Why Silicon Valley suddenly became interested in politics,

• How to optimize industrial policy in a stick-focused political environment.

Listen on Spotify, iTunes, or your favorite podcast app.

Jordan Schneider: Bruce, you were intimately involved in the birth and execution of the CHIPS and Science Act. Throughout the discussion around the legislation and grant implementation, politicians and officials kept saying, “We haven’t done this in decades. We’re building this muscle again. We’re learning on the fly.” This is something America had done in the past, but the energy atrophied over time. Reflecting back, maybe let’s start with the legislation writing process. How did the fact that these policy tools hadn’t been worked out in so long impact the discussion and development of the legislation?

Bruce Andrews: The United States government is actually not set up well and is challenged in two ways when implementing big industrial policies. First, the executive branch is not organized properly — we really have a 20th-century cabinet structure for 21st-century problems. Second, we don’t have the muscle memory of how to effectively implement industrial policy.

We’ve been fortunate in the United States to have a robust private sector that, with government investment and R&D spending, has been successful. But the world has changed significantly. For Congress in particular, there’s not necessarily the expertise, and they often rely on dealing directly with the executive branch to identify issues and the lack of authority that the US Government has. In many cases, we don’t have statutory authorities for executive branch agencies to carry out these policies.

When writing legislation, there’s always a balance between being specific enough while also giving enough flexibility to the administration to execute those policies. The CHIPS and Science Act was actually a good example, and it was done in two parts. The first part was drafted in the second half of the Trump administration and passed at the beginning of the Biden administration. Then they had to provide the funding because you had the authorization, but needed to appropriate the dollars that would actually be spent.

This was a huge legislative lift, and Congress added many new requirements during the funding legislation phase.

Jordan Schneider: You started your career in the early 90s and ended up as general counsel to Senate Commerce in the early 2010s. Thinking back on the arc of legislative ambition, principal quality, and staff quality — what trends did you observe over that time?

Bruce Andrews: Things have changed significantly since the early and mid-90s. The quality of staff — and this is not to say there aren’t still tremendous staff on Capitol Hill — but there used to be really deep expertise. The growth of lobbying is partly to blame for this change, as it has deprived Capitol Hill of many good staff members.

I’ve always believed we need to pay congressional staff more. Frankly, we should pay executive branch career civil servants more as well. When you’re a young Hill staffer or even a very experienced one, and you see your colleagues in the private sector making two or three times what you’re making, your incentive to stay on Capitol Hill and develop deep expertise is diminished.

Jordan Schneider: Last year, I did a show with Philip Wallach, who wrote the book Why Congress?, which examined the post-war arc of congressional capacity and willingness to put itself center stage. We’re recording this on May 6, and Congress is currently in a situation where money it appropriated isn’t being spent because an executive feels like withholding it, and they’re not doing much about it.

We’ve seen this before. After Nixon, Congress regained a real sense of institutional pride and reasserted itself in a way it hadn’t for decades. Who knows if that’s the future Donald Trump will leave us with in 2028? But if you’re imagining a more ambitious and energetic legislative branch, where does that leave the institution? Where does that leave America? What would need to happen to bring about a new flourishing?

The CHIPS and Science Act was a perfect storm of COVID, bipartisanship, and an eager executive that allowed for a significant bill. But for a broader shift in congressional ambition and execution capacity, what ingredients would we need to see in the body politic or what incentives would enable more legislation like the CHIPS and Science Act?

Bruce Andrews: I think success does beget success, but I also think it’s both sides coming together and identifying what the issues are. There are really three things. One is agreement and bipartisan agreement on what the issue is that you’re trying to solve. In the CHIPS and Science Act, there was real clarity on trying to get particularly advanced logic, but also trying to move semiconductor production back to the United States.

Second is an agreement on what tools the government has, or should have, in order to do that. In the CHIPS and Science case, people looked and they said, “Taiwan, Korea, and China have spent the last 30 years providing incentives to help their industries be successful. The US has sat on the sidelines and let the private sector do it. And we now have watched the majority of Atlantic Advanced Logic production move overseas.” Second is seeing the problem, which is the need to close the cost gap between the US and Asia, and putting in a solution that was able to do that.

Third is bipartisan support. There were a number of heroes of the CHIPS Act on both sides of the aisle. On the Democratic side you had Ro Khanna and Chuck Schumer and Doris Matsui and people who said there’s a problem. And then on the Republican side, you had great senators like Todd Young and John Cornyn, Mike McCall in the House who said, “We agree with you, this is a big problem and let’s work together and work even over the politics."

As you’ll recall, at the end, the CHIPS Act sort of got caught up in a little bit of last-minute politics because of some other things that were going on unrelated to the CHIPS Act. To their credit, the champions on the Republican side, including Mike McCall, John Cornyns, and Todd Young, really helped push it through and helped to get it done. You need all three. You need clear identification of an issue, you need a clear government solution in a narrow and tailored way to provide the tools to do it, and you need bipartisan support to be successful.

Jordan Schneider: That’s nice to hear, but it seems like we have never been further away from that. When you have a president who’s blowing up the NIH because he feels like it’s too big, we’re going to need to have some big thermostatic response to what we have now, because this is not the glide path. This is the plane that crash-lands, and only then we become motivated to do something.

Bruce Andrews: That’s right. You’ve got to have an agreement that there are solutions we can put in place. When you get down to the member level, you actually get a lot of good thinking and a lot of good bipartisan agreement. But then translating that — unfortunately, if I were going to have one critique of Congress right now, it would be that often we’re not legislating big issues. We’re more legislating when there’s a crisis.

There are lots of really important issues out there every single day that we need to be addressing. Unfortunately, it seems that we get to the level of a crisis, and then it’s easier to pass legislation. We need to get back to the old days — real bipartisan agreement and the ability to work in a bipartisan way, and not to be pressed by your colleagues in either party to say, “Why are you working with those people of the other party? Let’s just win the next election, and then we can do it our way.”

That’s been going on for a long time, where both sides have thought, “If we just wait until the next election, we’ll win — we’ll be in charge of the House, Senate, and the White House, and then we can get our package.” The reality is that it doesn’t work. With the filibuster in the Senate, with the need for getting things done in the close margins of the House, and with the nature of the White House, it’s a mistake to put off our problems because, “Oh, if we just win the next election, we’ll solve them.” It’s never that easy.

Beefing Up The Executive

Jordan Schneider: Let’s turn to the executive branch. The CHIPS and Science Act basically got to hire the pick of the litter because they had special hiring authorities and were able to really bring together this crack team from some government vets, but a lot of folks from Wall Street and a little bit from the semiconductor industry, too. Recently, Dan Kim said that in 2015, there were only two people who were thinking about the commercial semiconductor industry in government. What does good look like here? What are the institutions you would have loved to have had that were building that commercial understanding and institutional muscle for whenever we have to do this the next time, so it’s not from such a dead start?

Bruce Andrews: First of all, I don’t think the answer is just taking a chainsaw and eliminating agencies, but I do think having some flexibility to reorganize government for the 21st century and for the digital world would help. We still have a very 20th-century analog model that was built mostly post-World War II and over the second half of the 20th century for a very different world.

If I were king for the day, I would start by reorganizing the government to be much more focused and move some things around so that they made more sense. President Obama tried to do that or talked about doing that with government reorganization.

The Commerce Department is a perfect example. I would meet with counterparts from METI in Japan, or Ministry of Commerce in China, or the European Union. Counterparts would have a much clearer set of mandates and authorities and a clearer set of responsibilities, and would have basically all of the business-related functions within the country within one agency. Organizing government in the right way is important, but I don’t know if that’s going to happen anytime soon.

Jordan Schneider: No, let’s stay here. Let’s do a little more fan fiction. What are you pulling in and putting out?

Bruce Andrews: If it were up to me, I would pull all business-related economic development and competitive stuff into the department. I actually would rename it the Department of Competitiveness. I would focus on the economic tools, the commerce tools, the trade tools, the industry tools and give the authority for real industrial policy to work with public-private partnerships with the business community to make sure that we’re making these smart investments in R&D and building the future.

Second, I would set up a set of programs that help the Commerce Department, or hopefully the new Department of Competitiveness, have a set of tools that it can use to support industry. China, Japan, Korea, and Taiwan have all for the last 30 years had very focused policies, and they’ve been successful at encouraging certain industries.

We can criticize some of the competitive practices the Chinese used, but they put in a Made in China 2025 plan and set out key industries that they wanted to successfully dominate. If you look at those industries that they identified, they’ve actually done pretty well.

You need the magic of the private sector. A huge advantage that the United States has is our robust private sector. But you also need public-private partnerships in order for that leadership to take place. The world is too complicated right now for companies to just go at it alone.

When I was at Intel, I would always say, “We’re not just competing with companies, we’re competing with countries.” That’s the case — many US companies are going at it alone, competing not just against their foreign competitors, but the tools and resources of their foreign competitors’ governments as well. We don’t want to recreate that. We don’t want to copy, but we need to establish our own model that works.

Secretary Lutnick has proposed what I would call “SelectUSA on steroids.” During the Obama administration, we created the SelectUSA office to attract foreign investment. To Secretary Lutnick’s credit, I think he’s identified that there are investments and then there are what I would call the mega investments.

Having an office within the Department of Competitiveness that would help facilitate both US companies and foreign companies making those investments in the United States would be fantastic. Giving the US Government some more flexible tools to help incentivize those investments and to help those investments be successful is important for us to be competitive.

For 30 years, there were reasons why globalization was a good economic theory, and there was a lot that was good for consumers and a lot of other things. But we also live in a very different world now. We need to have a structure and tools that allow the US Government to be competitive and the US to be competitive in this very different world.

Jordan Schneider: Not to be your assignment editor, but I think this should be your first CSIS piece — what authorities you want to be here. It’s a fun future-casting exercise where you don’t really have to engage with the present messiness. But can we do one more pass on this? What do you give up? The Commerce is already a giant mess. What do you slough off it? I guess there are three buckets — what do you slough off, what do you take from other agencies, and aside from SelectUSA, what’s on your wish list for new authorities and power?

Bruce Andrews: First of all, I would point out that the Commerce Department is perfect. I would probably change nothing. But if I had to change something — Obama made a proposal, for example, to move NOAA (National Oceanic and Atmospheric Administration). I could argue that that’s important to business and that things like the National Weather Service and others actually are key facilitators of public goods that help business.

There was talk of moving the Small Business Administration into the Department of Commerce. It doesn’t necessarily make sense that we have SBA, we have SBIR programs around the government, we have Economic Development Administration in Commerce, and that we have the Minority Business Development Administration.

1. I would consolidate all of these different economic and small business minority business programs into one part of the Department of Competitiveness for it to be successful.

2. I would also take all the technology agencies around the government. We have NTIA, we have NIST, we have various technology programs, rural broadband at the Department of Agriculture. We have all these different programs around different agencies. I would consolidate them together and say the Department of Competitiveness has an economic development piece, it has a technology piece, and it has an international trade piece.

One of the things that was very controversial, and I could argue this both ways, is moving USTR within the Department of Commerce and having the International Trade Administration and the US Trade Representative’s Office be one super trade organization.

Government statistics — why are the Bureau of Labor Statistics, the Bureau of Economic Analysis, and the Census all separate organizations throughout the government? Take all government statistics and put them in one place.

I think there are a bunch of things that you could do to rationalize all this and to help the US really be supercharged and competitive. Frankly, one of the reasons that Obama ran into trying to get this consolidation authority was Congress didn’t want to give up the various committee jurisdictions. When I was at the Commerce Department, we had, I think, eight full committees and 79 subcommittees that had jurisdiction over the Department of Commerce. That doesn’t really make a whole lot of sense.

Jordan Schneider: Within this context, let’s do a little history lesson on how CHIPS and Science came to be.

Bruce Andrews: The interesting thing — you mentioned something that’s really important, in 2015, there were only two people within the US government who were experts on semiconductors. I learned that in November of 2015, when I spoke as the Deputy Secretary of the Commerce Department to the Semiconductor Industry Association.

Interestingly, at that time, the SIA (Semiconductor Industry Association) CEOs, who previously had all been very confident of “government stay out of our way, we don’t need your help, we’ve got this, we’re 10 years ahead of China, we don’t really need government assistance” — when I spoke to them in November of 2015, I saw what I would almost describe as a sense of fear in their eyes about the Made in China 2025 program and what was called “The Big Fund,” the $250 billion fund that the Chinese government had set up to help facilitate their semiconductor industry.

I took that back and sat down with my then-boss, Secretary Penny Pritzker. Penny and I said, “Let’s put a plan together to help the US Semiconductor industry. What would that look like to help the US semiconductor industry compete with Made in China 2025?”

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What’s funny is I called the Assistant Secretary of the International Trade Administration for Industry and Analysis. I said, “Okay, we need to put together a semiconductor plan.” He said, “Okay, I’ll bring my one guy up and let’s talk about it.” We only had one guy doing this. Now, the good news is there’s a guy named Travis Mosier who is super talented, super smart, and knew these issues quite well.

We put together a plan, a playbook, and we said, “Okay, what can the US Government do?” Interestingly, we initially got some pushback because people said to us, “Why are semiconductors special?” Secondly, we got some pushback because people said, “Well, if we help the semiconductor industry, won’t other industries be unhappy and feel like we should help them too?” My response was, “Well, yes, but that doesn’t make it any less important.”

We spent several months working with the White House team and the interagency team. Interestingly, Paul Selva, who was the Vice Chair of the Joint Chiefs of Staff, was also really interested in microelectronics. Paul and I got together and pushed through the NSC process a plan to start having much more focus and attention on semiconductors.

We had none of the tools. Those came later. Eventually, Penny Pritzker gave a big speech that really helped define the challenge. We had a PCAST report, which is the President’s Committee of Advisors on Science and Technology, which for the first time made a series of recommendations. That was right at the end of Obama, but it then carried into the Trump administration, and all of that attention and focus eventually became the CHIPS and Science Act.

It shows two things. One is you need to identify a problem and start talking about the solutions to those problems. Two, you need focused energy and intensity because nothing happens fast, either in the federal government or in Congress. Even though it took several years for all of this stuff to come together, we were successful at both putting focus on the attention, setting a set of tools, and then enacting a program that represents by far and away the biggest piece of industrial policy we’ve seen, at least in the last 50 years.

The Policymaking Ecosystem

Jordan Schneider: Let’s continue the story from the perspective of an Intel executive. What is Government Affairs? And maybe using this story as a case study, what can and can’t — or what is easy and what is hard — for industry to do to make things happen in the legislative and executive branch?

Bruce Andrews: Government affairs is really about education. It is bringing information to government policymakers to help understand the challenges that the private sector is facing and then also help to start having a discussion about what the solutions look like.

The irony of the CHIPS Act is that it was actually not started by Intel, although Intel will be the biggest beneficiary. Where it started was actually Mike Pompeo trying to recruit TSMC to come to Arizona. What TSMC said to Pompeo was, “We have a huge cost gap. We get incentives in Taiwan to build. We need something in the United States."

Ironically, when I was Deputy Secretary of the Commerce Department, I met with Terry Gou, the chairman and CEO of Foxconn, who basically said to me, “I want to build in the United States, but you need to give me big federal incentives.” I said, “Well, here’s the problem. We don’t have federal incentive programs in the United States. It doesn’t work the same way it does in China and Taiwan.” Terry eventually did start that project, but it ended up not working.

People were starting to realize that if we wanted to bring manufacturing back — and I give Secretary Pompeo a lot of credit because I think he recognized that was the way to get TSMC back. Interestingly, when Pat Gelsinger came in as the Intel CEO, he recognized that Intel needed to become a contract manufacturer for other companies. Foundry would provide more competition to TSMC and Samsung. The CHIPS and Science Act allowed Intel to do the construction in the United States. It allowed Intel to really make a fundamental change to its business model, moving manufacturing or building manufacturing in the United States.

It’s often forgotten that the CHIPS Act started in the Trump administration. It didn’t get passed, but when Biden came in, it got passed quite quickly. That set off the debate for funding the CHIPS and Science Act, which was eventually passed in July of 2022.

Jordan Schneider: Coming back again to — what does education mean? How does one educate? Is it easier or harder today versus back in the day where you have more or less sophisticated staffers and all the stuff we were talking about?

Bruce Andrews: In the same way that you did not have expertise within the Commerce Department, I’m not sure there was a single person who had any level of expertise on semiconductors in the Congress. Someone’s probably going to call me and say, “Hey, I was that person. You’re wrong.” But let’s just say for the purposes of argument, there really was not a deep level of expertise.

The good thing about a company like Intel is it’s got a huge number of very smart experts who are thinking about understanding the global industry. Being able to present a picture through data — and I will say the Semiconductor Industry Association is actually really good at providing data and information that gives a very full and complete picture to help educate lawmakers.

Generally you’ve got to assume lawmakers start at a relatively low level of understanding just because they’re not experts. You do get some members who come in as experts or you get a guy like Todd Young who really learns about the semiconductor industry and has a state like Indiana and a university like Purdue that want to focus on how to be effective and successful in the semiconductor space. You generally start with not a huge amount of information, but you start with an interest.

I give Doris Matsui and Mike McCall credit in the House. As I mentioned, you had Young, Cornyn, and Schumer in the Senate who said, “This is really important.” They then turned to industry and said, “Help educate us on two things. First, what is the status of the global industry? What’s the problem we want to solve? Second, what tools do you need to help us?”

In the case of the CHIPS Act, it was identifying that there was a 30-55% cost gap between manufacturing in the United States and manufacturing in Asia. The CHIPS Act — including the grants, but also the 25% investment tax credit — was all about filling that gap and helping US manufacturing to be competitive. That’s not necessarily something that members of Congress or the people in the administration would totally understand well on their own. That’s where private sector actors can come in and help educate them as to what those tools would look like to be the most successful.

Jordan Schneider: That is a nice story. Perhaps your average American — or maybe your average independent tech policy podcaster — would see this and see something wrong here. The fact that the US government had one guy, the fact that Congress, the executive branch had one guy, the fact that Congress had no one, and that there were not think tanks — we can debate how independent they are from corporate money — academics, we can also debate how they are from corporate money, particularly when you’re talking about these high technology industries where there’s a lot of university to industry connection.

As a big fan of the CHIPS Act, it was kind of concerning to me seeing that every voice in this debate was funded or connected to industry. If we end up doing more and more industrial policy, it would be nice to have voices whose paychecks are not necessarily connected to these outcomes to also be able to inform legislators.

Bruce Andrews: I would say two things to that. The American people had a real crash course in the importance of the semiconductor industry during COVID when they couldn’t buy products because there was not an availability of semiconductors because they were all being sourced out of Asia.

I hear you, and obviously this is why I think bipartisanship is so important. You bring members from both sides who have different constituencies, but they come to the table and they say, “Let’s get the best policy we can and reflect a lot of views.”

The semiconductor industry has never been a particularly big or politically active industry. They don’t have big PACs. It’s not like a lot of industries where there’s a huge amount of money flowing through. It’s actually been relatively unsophisticated in Washington.

That’s where the identification of the problem was so important. I think there were two voices that were critical. One was actual consumers. I’ll never forget when we went to meet with a very senior senator, and he told us that he had autos sitting on lots in his state waiting for semiconductors to be put in so that they could go out to dealers. One senator told us he actually bought a Ford F150, but it didn’t have the heated seat yet because the chip that would heat his seat was not available. This is a guy who lived in a really northern state that was super cold. I felt bad for him.

The second piece of this is the voice of the national security community. What also makes semiconductors kind of unique is the national security implications. As I mentioned, Paul Selva, the Vice Chair of the Joint Chiefs, was very focused on microelectronics and having a trustworthy supply of microelectronics in the United States.

You saw a lot of leading members of the national security community and the committees in Congress. Mark Warner is a great example — both a tech guy and a national security leader, as the chair of the Senate Intelligence Committee — is one of the most vocal voices for the CHIPS Act. Not because Virginia is a big semiconductor manufacturing state, although I think Mark would like that. It was more out of a recognition that this is a huge national security imperative that he was very supportive of.

There’s no doubt that there’s lots of stuff where there needs to be public scrutiny, there needs to be public debate. You need to hear all kinds of voices to make sure that special interests don’t just take advantage of a process. But I think in this case there were two pieces. One was the passage of the congressional legislation, and then the second was the implementation by the CHIPS Program Office to try to make sure that this was done in the way that was most focused on the national interest.

Jordan Schneider: Do you have any thoughts about think tanks as institutions and what they can and can’t do and what their purpose is?

Bruce Andrews: I think think tanks are actually very important. I should have mentioned them earlier. My experience with think tanks is, yes, they need money to run and some do take corporate and other types of money. It’s not just corporate — there’s all kinds of money that help fund think tanks. But in my experience, people tend to be very independent because their reputation is on the line. They’re very focused on doing the highest quality work.

Think tanks are really important because they do provide an independent perspective and sometimes an independent validation. Sometimes they can do studies that a company can’t do. I’ll give you an example. I just saw this morning that the Rhodium Group came out with a study about the China Made in 2025 plan’s effectiveness. That’s not something that a single company could do.

There are a lot of good think tanks with a lot of really smart, thoughtful people who are adding to the debate.

When I was a policymaker, both in Congress at the Senate Commerce Committee as a very senior staffer and general counsel, but also as the Deputy Secretary of the Commerce Department, everybody who came in had their self-interest. Part of my job was to get enough voices to make sure that someone’s self-interest was validated, to try to incorporate other perspectives.

My rule when I was in government was always I would meet with anybody and listen to you. I might tell you no and I might tell you that I think you’re completely wrong. But that’s okay. That’s actually how the system works. It should be a dialogue and it should be a back-and-forth. It should be a really robust public debate and we should have hearings in Congress and we should have lots of different perspectives aired. And then you’ve got people who in the end are going to have to make decisions, but at least you’ve had a broad set of opinions and views and data put on the table.

Policymakers have to be able to sort through all that. That’s one of the reasons both policymakers having expertise, but also having staff with expertise, helps to sort through this massive amount of information that comes in. I’ve many times seen think tank reports that really help to shape legislation or help to shape either the identification of problems or identification of solutions and frankly sometimes bring bipartisanship — my three components for what you need to be successful. Think tanks play a very important part in that.

Jordan Schneider: You mentioned America or senators getting lessons in the semiconductor industry from cold butts. America’s also about to get a whole lot of lessons in trade policy thanks to what’s been happening over the past few months. What do you want to say about this stuff? We can do chip specific economy in general.

Bruce Andrews: No, I mean, look, this is obviously a very complicated topic. You know, I get that. What President Trump has said, I agree with him on two things. One is that we need to identify strategic sectors where we need to be investing as a country in manufacturing. I wouldn’t say that it’s everything because there are a lot of things that we just can’t do. But one level should be what can we do strategically, both out of our own economic interest, national security interest, and where we can be successful.

Second is how do we work with allies? When I was at the Commerce Department, there was a lot of discussion about NAFTA and Mexico because a good that was made in Mexico had 46% US content. A good that was made in China had 4% US content. Everybody realized — this light bulb went off to people with that data — basically saying, “Hey, for things that we can’t economically or cost effectively do in the United States, it’s actually in our interest to have them be done in Mexico or Canada.” You’ve seen a lot of work with various allies to try to have things manufactured in ways that are good for the United States.

Third is the availability for consumers. On one level, you’ve got to protect the workers. The story I told you earlier about when Penny Pritzker and I decided to make semiconductors a priority for the Department of Commerce, one of the reasons was I had met with the steel industry executives and the National Steel Workers union several days before. I literally said to Penny, “I don’t want to be in a position in 10 years,” and in meeting with the steel workers, I basically said, “Hey, look, we don’t have the tools to be able to be helpful to you. We want to help you, but the statutory tools and authorities we have will not allow us to be helpful to you here.”

Penny and I said, “Okay, let’s make sure that’s not the semiconductor industry in 10 years — the experience we’re having with the steel unions and the steel industry today.” I do think that’s important — identifying what is really in our core national interest, and what can we as a country be successful at.

Tariffing everything in sort of a broad way isn’t necessarily going to be effective. We’re already starting to see some of the economic effects of that. I’m hoping that the administration looks and says, “Okay, what are we trying to solve for here?” What are the authorities we have and how do we do it? Thus far it doesn’t feel like we have clarity on what problem we’re trying to solve or exactly what solutions we’re trying to enact to do that. I’m hoping that the administration, as they do these negotiations with other countries, will get more clarity on that. Otherwise, I do worry that this is going to be a trade war that isn’t successful for the United States, for American consumers, but also American companies.

I’ll give you an example. One of the things that really concerns me is if you are a US manufacturer, there are a lot of things that you have to import from overseas as inputs into machinery and all kinds of things. A great example is Intel and an Intel fab. There is a $450 million ASML EUV lithography machine. What happens if you put a 25% tariff on an EUV lithography machine coming from Europe? Intel has to buy with those tariffs, but their foreign competitors in Taiwan, Korea, China don’t. What happens fairly quickly is it makes US companies completely non-competitive as manufacturers.

If our goal is to be successful in manufacturing, which it should be — I think that’s actually really important — helping US manufacturers, then we need to be doing everything we can to help them be successful, not tariffing intermediate goods in a way that actually harms the competitiveness of US manufacturers.

Jordan Schneider: Anything else you want to say about the future of Intel? Your well wishes for the new squad over there?

Bruce Andrews: Intel is a very important company to the United States, and it was one of the reasons I went there when Pat Gelsinger laid out his vision for a third US competitor. TSMC is a remarkably impressive company. Samsung’s a great company as well, but having a not over-consolidated industry and having manufacturing in the United States is really important. Intel is actually a very important company to this country. I spent a lot of time there because I believe in the mission and American manufacturing, but also the importance of having a leading advanced logic manufacturing company who does its R&D and whose primary operations are in the United States.

Jordan Schneider: Ben Thompson of Stratechery’s diagnosis of the challenge of the CHIPS Act was that it focused too far on the supply side and not enough on the demand side. His vision of what Intel is going to need to succeed on the foundry side at least is designated customers. On one hand, Qualcomm, Nvidia, Apple — they’re not excited to live under a monopoly decade going forward where the only people who can supply them are TSMC. But it is hard to be the first mover to go in with Intel and work with them to get all the tooling right and be that sort of guinea pig when on the other hand, you have someone who can charge you a huge markup, but you know they’re going to deliver.

His vision is that you solve the collective action problem with the government stepping in and banging heads and forcing everyone to go in on Intel. That seems like a high degree of difficulty to put on Howard Lutnick. How would you work on the demand side from a policy perspective to give Intel Foundry a boost?

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Bruce Andrews: I tend to be a carrot guy, not a stick guy. The stick can work in certain cases, but you’re better off having the carrots. One example is that a number of companies on the fabless side have talked about having a design tax credit for American fabless companies. During the CHIPS Act, they lobbied, but Congress did not add an investment design tax credit for the fabless industry.

I could see, and I know there are policymakers who would say, let’s give them a design tax credit, but let’s do it if they manufacture in the United States, because what we don’t want to do is give them a design tax credit to then go and manufacture in Korea or Taiwan or China. That’s one possibility.

There’s going to be a set of discussions because we have identified this as a national priority. Trying to find some tailored solutions is important — Intel’s got to do its piece to be competitive. On the other side, having some carrots to encourage companies to embrace manufacturing here in the United States would actually be a really good thing.

Jordan Schneider: Earlier you mentioned as Deputy Secretary of Commerce and in the Senate as well, you meet with everyone. I’m curious, thinking back to that, before you spent the past few years in the semiconductor industry, were there other industries where you’re just like, “Oh, man, these guys really get it. They’re super sharp?”

Bruce Andrews: It’s a really good question. The short answer is yes. There are a lot of really smart and talented companies out there. I was constantly surprised by the quality, and I think the tech space is one. There are a whole bunch of areas where you have really sharp, really talented leaders in those companies.

Tech was definitely one because tech, particularly since the late 90s, has attracted a lot of great talent. The people running these companies are actually very smart, talented people. When I meet them I go, “Wow, they are really smart.”

Every once in a while I would meet with people and I’d think, “God, your arguments suck. I could help you write your talking points better than you have written them.” But for the most part, I found most companies, particularly in areas that tended to be both technical but very competitive industries — I actually found people to be quite smart and impressive most of the time.

Jordan Schneider: There’s a story that Nvidia had like two government affairs officials before October 7, 2022. You were talking earlier about how the semiconductor industry was quite hands-off for a while. But even Robert Noyce in the 80s was like, “We’re going to do Sematech.” It’s this weird ebb and flow of caring about Washington, not caring about Washington, really realizing you have to care about Washington again. Is it a California thing? At what point, maybe for semiconductors and industries broadly, does the light bulb turn on that this place is really important to us and we’ve got to get serious about it?

Bruce Andrews: I think it’s been an evolution over the course, but particularly it’s accelerated in recent years. For manufacturing companies, they tend to get it more because they actually had physical locations. For a company like Intel or Global Foundries or Texas Instruments, you understand the importance of interrelationship with the government.

Nvidia is a good example where they didn’t have a PAC, they didn’t have any lobby, they didn’t have anybody registered to lobby probably until 2022. When I first met them when I was at SoftBank, they said, “Oh yeah, we have nobody registered to lobby in Washington. We don’t do lobbying.”

A couple things have happened. One is the world has become much more complicated. The geopolitics are driving a lot of the technology policies. Second is things like export controls which directly impact companies.

There has always been, particularly in Silicon Valley, but in a lot of other industries, a deep libertarian streak where it’s like, “Hey, we don’t need help from government. Leave us alone, we’ll compete, we’ll be successful, we can do this, we don’t need you.”

Other industries— pharmaceuticals is a good example where government health policies have always been very directly related because you have Medicare and Medicaid funding, or the auto industry where government policies on CAFE standards matter.

The semiconductor industry had not been particularly heavily regulated, particularly true on the fabless side — the companies that just did design but didn’t do their own manufacturing. The world has changed, and as the world changed, people realized, “Wow, we really have to engage here and we have to be in the game.”

That is not unusual of many other industries. The libertarian ‘leave us alone’ streak in Silicon Valley really tended to be much deeper than a lot of other places.

Jordan Schneider: Yeah, I think Trump trade policy is going to put that to bed for literally every industry probably.

Bruce Andrews: It has been a wake up call to a lot of companies, for sure.

Jordan Schneider: I’m curious for your reflections from a sort of GR corporate messaging perspective on how you bend to the prevailing winds in Washington. There have been a lot of examples, I think, over the first few months of the Trump administration, which almost show the extreme of this, with corporations really bending over backwards to kind of use the language and rhetoric of the Trump administration. But this is something that happens all the time. I’m curious, to what extent you see this as a disjuncture versus just kind of par for the course of trying to ingratiate yourself with the party in power.

Bruce Andrews: Look, I would say it’s a little of each. Historically, all players — it’s not just companies and corporate CEOs and lobbyists or whoever — have always tailored their message to how they think it will be best received by policymakers in power. I do think starting in 2017, but accelerating, China has become a much more used argument for almost every regulatory policy or whatever. When you see Meta saying ‘Oh, we need to not be regulated as much because we need to compete with China’, you realize that’s something probably because it actually appeals to policymakers. The speakers are always going to tailor their message to what they think is going to be most effective with the audiences. That’s one piece.

President Trump is very assertive. Companies have approached the administration carefully, wanting to get on their good side and understanding what those things are that President Trump sees as part of his priorities and his legacy. You have seen companies tailor their messaging as they have for pretty much every other administration. But they have definitely tailored that messaging as part of dealing with the administration.

Jordan Schneider: Can we reflect back a little bit on the PAT era? Because it was sort of remarkable, right, where he wouldn’t say China, he would say American national competitiveness or what have you. But then I remember he still had to go to China every once in a while because it was such an important market for Intel to sell into. Reflecting back as you guys were sort of managing that and then managing annoying podcasters like me whining that Intel is investing in Chinese chip design companies or whatever— how do you think through that calculus as you’re trying to maintain market access to a country that the US is not super happy you get so much revenue from?

Bruce Andrews: Well, I mean, I guess I would say two things. One is you’ve got to look at facts. For everybody in the semiconductor industry, and Intel is probably in the pack sort of average, but there are definitely companies that have a much higher amount of their revenue come from China. For American semiconductor companies to remain not just competitive, but to remain as leaders, the Chinese market is quite important because about anywhere from 30 to 40% of the market is in China.

That’s changing a little bit now that Apple’s moving phones out and Dell and HP are moving laptop production out. You’re seeing changes in the footprint, but you’re still going to see China be a very significant market for all these companies. The companies have a balance, right? Because on one hand, in order to continue investing in R&D and investing in factories and other things in the United States, you can’t drop your revenue 30%. If you lose 30% of your revenue, you’re dead. If you lose 30% of your revenue, you stop being competitive.

The question is how to find a balance which is to remain competitive and be successful while also respecting US national security concerns, which is a lot of what has driven the government to make policies that tend to reduce companies’ access to the Chinese market.

What’s interesting about this is each company has its own profile. They have to make a decision — how important is access to the Chinese market? What percentage of the revenues and then how are those revenues spent? What does it mean to their long-term and future competitiveness? It’s a very challenging calculation for any company to make.

For companies that want or need to be successful in the Chinese market to remain competitive, it is definitely a delicate process. How do you maintain that? I do think you see a lot of companies trying to do that because they recognize the importance of the Chinese market.

I don’t know if you’ve read Eric Schmidt’s piece in the New York Times, but there are a lot of very successful Chinese companies. Sometimes, if you go too far on export controls, what you actually end up doing is accelerating indigenous innovation in China. There are plenty of Chinese companies that would much rather buy, for example, Nvidia chips. But then you’ve got people in the United States government who are saying there are national security concerns.

It’s finding that balance and recognizing that there are really two pieces to this. One — how do we help American companies run faster to remain competitive and successful? Two, how do we balance the national security concerns?

Jake Sullivan called it the small yard and high fence. People in the industry always said, “Sure, but just keep the yard small and the fence low.” That is a constant balance. Industry is always going to prioritize self-interest, and they’ve got a fiduciary duty to their shareholders to try to maximize revenue. US government officials — there are plenty of people who’d say, “Oh, let’s just not sell anything to China,” which I don’t think is realistic because it will both undermine the long-term competitiveness of US companies, but also undermine the short-term competitiveness because of massive revenue loss where there’s not really a clear national security interest.

Jordan Schneider: I think that might be a nice place to end it. Bruce, thank you so much for being a part of ChinaTalk and looking forward to having you back once you’ve fleshed out your Department of Competitiveness.

Bruce Andrews: I’m excited for that. The Department of Competitiveness is actually very important — something that I used to spend a lot of time thinking about, I have thought less about. But it’s one of the things that has really struck me in reading about Ezra Klein’s new book, Abundance, is the need for having a government that works well. We are not organized for how the world exists today. We’re organized for how it used to exist.

Mood Music

From an anon

On April 25, observers of China’s AI scene got an important new statement of Xi Jinping’s views on AI in the form of remarks concluding a Politburo “study session” on AI led by Xi’an Jiaotong University professor Zheng Nanning. Couched in the turgid language of Partyspeak, the readout nevertheless merits close attention as one of precious few utterances direct from the General Secretary himself on AI. To read this new tea leaf, we need to understand some background on study sessions in general, and this one in particular.

What are study sessions?

Politburo study sessions, or 集体学习 (literally, “collective study”), are regular two-hour meetings of top CCP leadership devoted to learning about some topic deemed a priority by the General Secretary. Typically, most of the session is taken up by a lecture from an academic expert in the matter in question, but occasionally Politburo members themselves make presentations. The structure was originally established by Hu Jintao shortly after he was elevated to General Secretary of the CCP in 2002, and used to consolidate his power and promote his policy priorities.

These study sessions are a far cry from your undergrad TA office hours. The topics reflect key focus areas of the paramount leader, ranging from foreign policy to technology to stuff like “Opening New Frontiers in the Sinicization and Era-ification of Marxism”. The process for putting them together is extremely involved. Party functionaries choose an expert and work with them to ensure the lecture is pitch perfect for the leader’s priorities. A professor brought in to recant the gospel of historical materialism for the group in 2013 said it took over three months to prepare for his session. There can be as many as three dress rehearsals. Study sessions typically serve to solidify and broadcast the leader’s views on some developing policy topic, not to workshop or introduce new policy. However, they do sometimes signal further action coming down the pike — occasionally to dramatic effect. A 2023 July study session on “governance of military affairs,” for example, preceded a wave of PLA purges including the ouster of 9 generals in December 2023, and more in 2024. Leader’s comments in readouts are sometimes referenced in later policies, as with “guiding opinions” on blockchain from the Ministry of Industry and Information Technology in 2021 that quoted a 2019 study session.

Why study AI now?

With plenty of other signs of attention to AI coming out of Beijing these days, it’s not surprising that Xi would want to get everyone on exactly the same page on this notoriously complex topic. The last time the Politburo had a study session on AI was in 2018, led by Peking University Professor and Chinese Academy of Engineering Academician Gao Wen. This study session followed the publication of China’s landmark New Generation AI Development Plan in 2017 and presumably served to clarify how that plan should be interpreted and implemented. It could be that this April’s study session was intended partly to inform the several new funding programs announced recently.

The obvious answer, of course, is Deepseek. DeepSeek’s impressive releases of late 2024 and early 2025 catapulted the previously “low-key” company to direct attention from the very top echelons of the CCP. If the process for organizing a study session was initiated in January 2025, then a few months of preparation time would land us exactly in April. (Perhaps coincidentally, last week’s study session also comes exactly 2 and a half years after the launch of ChatGPT in November 2022 — almost precisely the same amount of time as between AlphaGo’s victory over Lee Sedol in November 2016 and the last Politburo study session on AI in October 2018. This gives some indication of the metabolic speed of the CCP system.)

What did Xi have to say about it?

Alas, the Politburo neither livestreams their study sessions on Zoom, nor even shares the slides after class. But we do have a summarized version of Xi’s closing comments for the session. Given the role of study sessions in communicating the leader’s views, this is at least as important as the content of the lecture itself.

China’s approach to AI has demonstrated a lot of consistency since 2018, so Xi’s comments on this study session hit many familiar notes. The topline summary, as given in the first paragraph, is that China will use the advantages of its “whole of nation” system to persist in “self-strengthening,” with an orientation towards applications, promoting “healthy and orderly” development in a “beneficial, safe and fair” direction. Self-strengthening should especially target “core, high and foundational” technologies. Essentially, China will maintain aggressive industrial policy in an attempt to indigenize important tech supply chains, while also developing valuable applications of AI, but all subject to certain guardrails and, of course, the salubrious guidance of the Party.

Similar themes through the two texts include concerns about China’s weakness in basic research and foundational tech but confidence about strengths in scale of data and market, a goal of properly integrating research and industry, and cultivating a thriving talent ecosystem. On many counts, however, the exact language is tweaked, often expanded or made more specific.

But some things are new! This year’s mention of “application-orientation” is similar in nature to mentions of “needs-orientation” or “problem-orientation” in 2018’s readout, but it’s now far more prominently placed, alongside “self-strengthening” in the title and in the one-sentence summary in the first paragraph. It also seems to imply more of a focus on diffusing technologies that already exist rather than creating new ones, even if “mere” engineering rather than fundamental breakthroughs, to serve national goals. This year’s readout also calls specifically for developing strategic emerging and future industries (战略性新兴产业和未来产业) and seems to give a nod to “AI for science” by referring to “a revolution in the paradigm of scientific research led by AI” (以人工智能引领科研范式变革).

As analysts have pointed out, Xi’s discussion of safety issues here is more forward-leaning than in 2018, or possibly any statement coming directly from the leader’s mouth. He describes risks from AI as “unprecedented,” and suggests implementing systems for “technology monitoring, risk early warning, and emergency response.” This is much more specific than previous policy statements calling to establish an “AI safety supervision and regulation system” or to strengthen “forward-looking (risk) prevention.” The study session readout’s language almost more closely echoes that of documents passed around at the recent Paris AI Action Summit by China’s new AISI-equivalent body, the China AI Safety and Development Association. Among a litany of priorities for the new organization, one of the more ambitious referred to setting “early warning thresholds for AI systems that may pose catastrophic or existential risks to humans.” Clearly, the thinking of safety-concerned AI experts such as famous computer scientist Andrew Yao and Tsinghua professor Xue Lan, who himself has lectured at study sessions thrice, most recently on emergency management in 2019, is finding resonance at the very top of the Party hierarchy.

A wholly novel component of the 2025 readout is the discussion of international engagement. While vague enough to be consistent with an intention to engage productively with the US and its partners’ efforts on AI governance, Xi’s focus on capacity building in the Global South and closing the “global intelligence gap” (全球智能鸿沟), as well as calling elsewhere to “grasp the initiative” in governance, suggests that this is also viewed at least partly as a dimension of international AI competition. We can imagine that Xue Lan, in particular, may have taken note of Xi’s description of AI as a potential “international public good” (国际公共产品) benefiting humanity. Xue was the lead author on a report that framed AI safety as a “global public good.” The same language later appeared in a statement from a group including Xue at the International Dialogue on AI Safety in Venice, and in a paper published by Oxford University including coauthors who work closely with Xue. Although it seems plausible that Xi’s language was influenced by this meme, there are two key differences here.

1. Here, Xi is referring to the benefits of AI development being a boon to the world. Though the paragraph does mention strengthening governance and creating a global governance framework, it is in the context of AI capacity-building. The most natural interpretation is that the idea here is to ensure a harmonized global regulatory regime to facilitate global diffusion and adoption of, and preempt backlash against, Chinese AI. This is distinct from the idea that AI safety is a public good, in that mitigating the downsides of AI development is beneficial to all by reducing transnational risks.

2. The second distinction is more subtle: Xi’s vision of AI as a public good is “international” (国际) rather than “global” (全球), notwithstanding Xinhua’s mistranslation in its English reporting on the comments. “Global” implies the whole world, taken as one single entity (especially in Chinese where the word is literally 全球 quánqíu “whole globe”). “International,” on the other hand, merely implies something that occurs between nations — and if we know one thing about nations, it’s that they don’t always treat all their fellow nations equally. In the context of a paragraph about diffusing AI technology in the Global South, a cynical read is that what this is saying is essentially: “work with China on AI, you’ll get a good deal.” In the past, the Chinese government has rhetorically promoted “open source” as a pillar of international cooperation and capacity building; here, Xi does not go so far as to use those exact words, but the fact that AI tinkerers in Indonesia can download and build on DeepSeek’s R1 may in fact be what he’s gesturing towards. The upshot here may be not so much that China hopes to save the world with, or much less from, AI, as that they are willing to cut deals with positive externalities to bind a sphere of influence together into a “community of common destiny.”

Whether in the intervening years or during their cram session, the Party has clearly learned some things about AI development.

What does this all mean for AI in China?

Although an important statement of policy, this study session may or may not indicate any significant change in policy. As discussed above, study sessions are typically less inflection points than moments of crystallization. Thus, it is most important as evidence for things we have the least evidence for otherwise.

Most striking here may be the surprising introduction of new language related to risk management. It is notable that both of the two experts to ever brief the Politburo on AI have been vocal on potential risks, with Gao Wen coauthoring a paper in 2021 on “Technical Countermeasures for Security Risks of Artificial General Intelligence” (though he is better known as the Director of the military-associated Peng Cheng Laboratory in Shenzhen). Let’s not forget either Xi Jinping’s personal letter of high praise to Andrew Yao, a key leader in the development of China’s STEM talent but also one of the key pillars on the Chinese side of the International Dialogues on AI Safety. Xi’s hand-chosen experts on AI seem more like the Yoshua Bengios and Geoffrey Hintons of the Chinese AI world than the Yann LeCuns. This would seem to bode well for the prospects of China making reasonable efforts to mitigate risks in AI development domestically, as well as via international coordination. However, besides the establishment of the China AI Safety and Development Association, a body seemingly mostly positioned currently as a talk shop to engage with the barbarians, the mention of “constructing an AI safety supervision and regulation system” in July 2024’s Third Plenum decision has yet to bear any substantive fruit. Whether they’re serious about risk mitigation will ultimately be decided by actions, not words.

For our recent debate on whether China is “racing towards AGI,” this study session is a continuation of ambiguity. Xi definitively did not signal any particular emphasis on AGI, and the focus on “application-orientation” and overall ecosystem development falsifies any kind of specific, singular technological goal for China’s AI policy. At the same time, it shows that AI is indeed a top priority for Xi. The intent to “comprehensively plan” compute resources and promote data sharing point towards the kind of national-scale mobilization of resources that would likely accompany a push for breakthroughs in general intelligence. And the Party clearly has very concrete ideas about how to compete in AI. Things are serious now.

What this study session should impress on us more than anything, however, is that top CCP leadership is not only thinking about AI, but may even be having relatively in-the-weeds shower thoughts about things like data resources, talent pipelines, and risk indicators. This attention may facilitate prudent action to avert catastrophe, but it is guaranteed to stimulate action to advance China’s long-standing goals of achieving supply chain independence and strategic technological breakthroughs. Their success will be decided by the cooperation or contention of millions of ordinary Chinese with their own hopes, fears and uncertainties for their lives in a world with AI, as well as the sharp strikes and careless fumbles of China’s geopolitical competitors, and the assistance of what partners they can muster.

But who is Zheng Nanning in any case?

Experts selected to deliver study session lectures are not so much chosen to bring something new of their own to the table as much as to bring exactly what Xi expects. So, what does the ideal avatar of Xi’s preferences for AI look like?

Zheng Nanning is an accomplished academic who takes his broader role in society seriously. His expertise lies particularly in computer vision and pattern recognition, but he has increasingly also been involved in robotics and industrial automation, promoting an idea of “intuitive intelligence” focused on enabling AIs to interact with an uncertain physical world based on semantic understanding. While we don't have the slides of the Politburo's study session, we do for a talk on “Machine Behavior and Embodied Intelligence” Zheng gave in 2023, with wide ranging discussion of machine perception, robustness, human-AI coordination and more. An academician in the Chinese Academy of Engineering, he has served as Chief Scientist in the Information Science field with the 863 Program, one of China’s longstanding key strategic technology development programs, as a member of the first Expert Advisory Committee for State Informatization, and as President of his alma mater Xi’an Jiaotong University. He has also been active in talent development efforts, leading the establishment of one of China’s first experimental undergraduate AI majors.

A profile on Zheng from last year paints him as empathetic and well-rounded: during a graduation speech in which he takes personal responsibility for the failings of super seniors and dropouts who didn’t graduate on time, he quoted from Lu Yao’s thousand-page novel Ordinary World, famous for depicting the struggles and aspirations of ordinary rural Chinese during the 1970s and 1980s. He is something of a fitness influencer, who claims to be able to do 50 pushups in one go and encourages students to set their hearts on “50 years of healthy work for the motherland.” Although it may seem cringe for your professor to try to get you to pick up a jogging habit, it instead reads as poignant in the context of a recent spate of early deaths of high-profile AI leaders in China which many attributed to the intense pressures of the field. Zheng even describes his educational philosophy as importing the “physical education spirit” into academics, saying that studies and research require the same tolerance for loneliness and constant pursuit of breakthroughs as athletics. Nor does he ignore imparting a moral formation on his pupils, stressing the importance of giving students “full and correct faith” in the CCP’s socialist core values.

Give him credit he practices what he preaches!

This personal history is a close match for much of China’s focus in AI currently: computer vision is key to the extensive surveillance apparatus of the Chinese state and a field where China leads the world technologically; “embodied intelligence,” and especially industrial robotics, is a core part of China’s bet on AI to produce “industrial upgrading” and escape the middle-income trap, called out as one of four priority “future industries” at the 2025 Two Sessions; talent development is a fundamental pillar underlying China’s goals in both basic research and diffusing AI into commercially valuable applications; and while Xi seeks to re-engineer China’s economy towards a high-end, high-tech structure, he is also attempting to re-engineer Chinese society towards cultural self-confidence, greater athleticism, and — as always — ubiquitous, intimate alignment with the Party.

There is one subtle surprise in Zheng’s profile, however. Though he attended Xi’an Jiaotong University for his bachelor’s and master’s, he did his PhD at Japan’s Keio University in the early 1980s. In recent years, foreign educational experience has flipped from a coveted asset in the Chinese professional landscape to arguably more of a liability, especially for roles with the government. In Xi’s increasingly nationalist China, a history of immersion in Western cultures suggests possible spiritual corruption. (In an overview of the study session, one Chinese blogger jokingly referred to recent comments from the chairwoman of appliance manufacturer Gree Electric that she refuses to hire such “returnees,” as there are “spies among them.”) We should not read too much into this, as education in Japan was very common for Zheng’s cohort and is generally viewed as less potentially problematic than education in the US. However, if Party planners had at all wanted to choose someone who was only educated domestically and is at least as impressive as Zheng, they probably easily could have. Under Xi, study session lecturers have increasingly come not even from academia, but from within the party-state system itself. It’s possible that, like the inclusion of an apparent foreigner in the audience at Xi’s recent visit to an AI hub in Shanghai, this weak signal of endorsement of international exchange was, though not actively sought, at least passively welcomed to communicate a marginally more open attitude to foreign and foreign-educated talent in AI. With the Trump administration giving anyone on a visa in the United States a new gray hair daily, China must certainly recognize an opportunity to win back diaspora STEM talent, and potentially even some from third countries.

Zheng also has a long history of giving comments on AI and society which appear to attune closely with Xi’s approach to AI. Already back in 2016 he was talking about the need to pursue both basic research and application-driven development as “grabbing with both hands.” He has discussed in detail the dilemma inherent in this two-pronged approach, where heavy pressure to produce scientific work can lead to researchers feeling “like ants on a hot wok” and choosing projects less ambitiously as a result. In line with Xi’s focus on attending to both safety and development, he has cautioned that AI is a double-edged sword, noting that technology has been used in the past to “stymie societal development and even cause disasters for humanity.” As a well-rounded scholar, he has pointed to the need for interdisciplinary contributions from the humanities, philosophy and law to address the risks of AI. He carves a middle path unfortunately rare also in the Western AI ecosystem in calling for scientists to neither buy into hype or spread unrealistic projects regarding AI, nor to engage in goalpost-shifting or downplaying advancements.

What does Zheng see for the future of AI? Since at least 2016 and as recently as 2021, he has described the field as facing three major challenges. The first is to make machines “learn without teachers.” Arguably, this has already been achieved by LLMs, pretrained on massive datasets via unsupervised learning and capable of impressively broad in-context learning with mere prompting. The second is to make machines perceive and understand the world like humans do. It’s unclear what exactly this would entail but it's hard to feel like we aren’t on the way there with, for instance, AI systems that can distinguish any arbitrary object in any scene. The final challenge in Zheng’s telling is to endow machines with “self-awareness, emotions and the ability to reflect on their situations and behaviors.” Hopefully, thoughtful AI researchers such as Zheng will reflect on the complex risks and philosophical questions which situational awareness and AI sentience may pose before the wrong edge of the sword cuts.

Jordan is in Tel Aviv for the next two weeks. It would be fun to do a meet up if there’s a critical mass! Respond to this email to connect.

Best Podcasts

Inside the Soviet Cold War Machine

Sergey Radchenko’s To Run the World explores the Cold War not as a clash of ideologies, but as a tragic and often absurd contest for prestige, legitimacy, and recognition among insecure leaders struggling to validate their power, both externally and at home. In this interview, Radchenko argues that authoritarian regimes, especially the USSR and China, pursued global influence to compensate for internal weakness.

Part two came out in April, and it’s even better than part one! In this deep-dive, Radchenko unravels how personal egos and the battle for international prestige shaped Soviet decision-making — from Khrushchev’s downfall to Brezhnev’s Vietnam gamble, the paranoid Sino-Soviet split, Nixon’s unlikely détente, and the disastrous invasion of Afghanistan. This episode asks the question, what if boredom, not grand strategy, is what starts wars?

Allied Scale and Net Assessment with Rush Doshi

This interview with Rush Doshi explores how the U.S. should strategically compete with China by leveraging partnerships with allies. While China faces real challenges like demographics and debt, Doshi argues that China’s scale, manufacturing dominance, and industrial capacity pose enduring strategic threats. He critiques both the Biden and Trump approaches to alliances: Biden’s overemphasis on persuasion and Trump’s heavy-handed use of coercion. Instead, Doshi emphasizes the need for capacity-centric statecraft, where allies help each other build economic, technological, and military strength.

EMERGENCY EDITION: Trump's Pivot to Putin + AGI and the Future of War

Defense analyst and Economist columnist Shashank Joshi alongside former Pentagon official Michael Horowitz explore the future of war. So much talk online around AI and national security flattens out to “AGI is a nuclear bomb, the first to get there wins” that it was a real treat to get to explore a richer vision of the future with two true experts. I want to point you in particular toward the second half of the episode, where we explore the Pentagon’s bureaucratic inertia, the potential for AI to reshape warfare, and the possibility that an adversary launches a first strike on the eve of AGI.

I’m hoping to expand on this show with an interview series exploring AI’s impact on national security. Too often today, debates center on “superweapons” lazily pattern-matched to the nuclear era or go in circles on cyber offense vs defense. The goal instead is to repeat the exercise Dario did for biotech in Machines of Loving Grace: deeply explore the bottlenecks and potential futures across domains like autonomy, decision-support, stealth, electronic warfare, robotics, and missile defense. Guests will be engineers and technologists who can also explore second-order operational and strategic impacts.

But this needs a sponsor in order to happen! If you work at an AI firm, defense tech, VC, university or think tank and want to help facilitate the best conversations about the future of warfare, please reach out to jordan@chinatalk.media.

China AI

Is China Racing to AGI?

This article explores whether China is truly racing toward artificial general intelligence (AGI) by staging a debate between two perspectives: the Believer, who argues that China is committed to beating the US to AGI, and the Skeptic, who contends that China’s focus remains on practical, application-driven AI development rather than AGI moonshots. While China has prioritized AI in general, the article argues that China's fragmented AI ecosystem, bureaucratic caution, and investor risk-aversion could disincentivize transformative superintelligence-focused research.

DeepSeek and Destiny: A National Vibe Shift

This guest post by Afra is a must-read. The rise of Chinese AI startup DeepSeek has ignited a nationwide wave of techno-cultural euphoria, reawakening the traditional concept of Guóyùn (國運) — the belief in a nation’s destiny. Viewed as both a technological milestone and a symbol of China’s long-awaited ascension, DeepSeek has become a focal point for patriotic pride after the trauma of COVID-19. As state rhetoric, popular culture, and grassroots sentiment converge around national destiny, DeepSeek's story reveals how technology in China is never just utilitarian — it is deeply entwined with myth-making, nationalism, and a collective need to prove that China’s time has finally come.

Manus: A DeepSeek Moment?

In this podcast discussion, Rohit Krishnan, Shawn Wang, and (now White House official!) Dean Ball analyze the potential of AI agents and the degree to which Manus matters overall. Unlike the research-heavy ethos of Western labs, Manus reflects a pragmatic, product-focused approach, prioritizing functionality over grand AGI visions. The conversation explores why Western AI giants have lagged in building compelling agents, citing safety concerns and regulatory risk aversion.

We also took a look in an article at Manus’ founder. Founded by pragmatic serial entrepreneur Xiao Hong and prodigy Ji Yichao, Monica evolved from a browser plugin into an AI agent business focused on product-market fit and international expansion, eschewing grand AGI ambitions in favor of practical use cases and aggressive data collection. With a flashy invite-only launch, Manus positions itself as a user-friendly, multilingual AI tool targeting overseas markets — a strategic move amid geopolitical tensions and growing scrutiny of Chinese tech.

Tariffs

How the Drive for Autarchy Caused WWII

In this sweeping conversation from the ChinaTalk archives, historian Nick Mulder explains how the obsession with national self-sufficiency fueled the economic insecurities that led to World War II. From the League of Nations’ failed sanctions on Italy to the Nazi quest for “raw materials freedom” and Japan’s desperate turn to war after facing an ABCD (America, Britain, China, Dutch East Indies) embargo, the episode shows how economic pressure, when mishandled, can backfire and accelerate conflict.

MAGA: A Guide for the Perplexed with Tanner Greer

In this podcast episode, Tanner Greer analyzes the chaotic dynamics of Trump’s second administration, particularly its approach to China and global trade. Greer explains Trump’s unpredictable decision-making style, his use of internal factional conflict as a management tool, and the administration's disjointed tariff policies. The conversation explores four quadrants of Trump World ideology and how adherents of each quadrant approach trade, industrial policy, and Taiwan.

Dylan Breaks Huawei and Tariffs Right

In this podcast, Dylan Patel of SemiAnalysis outlines a smarter semiconductor tariff policy aimed at boosting US manufacturing, moving supply chains out of China, and increasing America’s capital-intensive domestic production. This podcast also includes discussion from Dylan and Doug O’Laughlin about how Huawei is successfully circumventing US export controls by leveraging its vertical integration, supply chain workarounds, and large-scale system engineering.

Are We Cooked?

In this podcast, Peter Harrell, Kevin Xu, and Matt Klein discuss the chaotic implementation of Trump's new tariffs, the damage they’ll cause to international alliances, and the broader risks of US governance failures. The conversation explores the interaction between structural American strengths — innovation, entrepreneurship, and private R&D — and damage from erratic policymaking, attacks on the rule of law, and capricious foreign policy. The guests cautiously conclude that America is not yet “cooked,” though the heat is rising.

Trump's Semis Trade Policy

This CSIS Chip Chat episode explores the conflicting goals of Trump’s semiconductor tariff strategy. Bill Reinsch and Jay Goldberg highlight how poorly coordinated tariffs risk undermining enforcement of semiconductor manufacturing equipment controls, inadvertently benefit Chinese chip firms, and alienate allies needed for collective action.

Export Controls and Chinese Compute Infrastructure

Why China's Cloud Lags

This article by JS Tan analyzes why China’s cloud computing sector lags behind the US, despite massive investments from tech giants like Alibaba. While Chinese cloud providers have built extensive low-margin Infrastructure-as-a-Service (IaaS) capacity, they struggle with the high-value Platform-as-a-Service (PaaS) offerings that drive profitability in the US. Factors such as low enterprise IT spending, cheap labor, a weak enterprise software ecosystem, and the absence of professional IT consulting services hinder China’s cloud adoption beyond basic functions. Additionally, state-owned enterprises dominate China’s cloud landscape, prioritizing strategic control over compute capacity rather than developing profitable software services.

Mapping China's HBM Advances

This article by Ray Wang examines China's accelerating progress in high-bandwidth memory development, focusing on CXMT's narrowing gap with global leaders like SK Hynix, Samsung, and Micron. Despite US export controls aiming to restrict China's AI capabilities by targeting HBM supply chains, CXMT is now only 3-4 years behind in HBM technology. China's cloud and AI sectors, especially firms like Huawei, drive demand for advanced HBM, pushing CXMT to leapfrog into higher-value technologies. While CXMT’s still faces major obstacles, its rapid progress could reshape market dynamics, especially within China, and pressure global memory players on pricing, even if technological parity remains elusive.

Chinese AI Will Match America's, But Will That Matter?

While China may achieve AI model parity with the US in 2025, this article argues that America’s real advantage lies in its vastly superior compute capacity, which enables broad economic integration, innovation, and global AI leadership. Despite setbacks like TSMC's illicit chip production for Huawei, US export controls have successfully slowed China's AI progress by raising costs and limiting scale. The author contends that US policymakers should focus less on temporary model comparisons and more on leveraging compute dominance for sustained technological and economic leadership, warning against complacency and policy missteps that could squander this critical edge.

Ban the H20: Competing in the Inference Age

This article argued that China's AI ecosystem, long hampered by fragmented infrastructure, is increasingly well-positioned to dominate in an inference-heavy era, thanks to access to inference-optimized chips like NVIDIA’s H20, stockpiles of older GPUs, domestic alternatives like Huawei’s Ascend 910C, and major advances in inference efficiency. Evidently, the call to ban the H20 reached the right person, and the Trump administration has since cracked down on China-bound H20 exports.

Chinese Industry

Unitree CEO on China's Robot Revolution

In this translated interview, Unitree Robotics CEO Wang Xingxing lays out a bold, techno-optimist vision for the future of humanoid robots, predicting they will transform every industry within our lifetime — from manufacturing and construction to healthcare and even environmental restructuring at the microscopic level. While dismissing large language models as insufficient for robotics, Wang anticipates a breakthrough in general-purpose AI models tailored for robots by the end of 2025. He discusses Unitree’s competitive edge and the strengths of China’s domestic supply chains for manufacturing cost-effective robots. Despite skepticism toward Silicon Valley hype, Wang remains confident in China’s potential to lead the humanoid revolution, citing a rapid pace of development, youthful entrepreneurial energy, and abundant capital inflows.

Humanoid Robots: The Long Road Ahead

In this Q&A with Angela Shen, robotics PhD “KL Divergence” outlines the challenges and future trajectory of humanoid robotics, emphasizing that true viability hinges on achieving a “data flywheel” where robots deployed in real-world settings collect diverse, high-quality data to train better models. Industrial applications like logistics and manufacturing will likely see robots first, while home use remains at least a decade away. This article discusses what it will take to succeed in the humanoid robot race — as the field rapidly evolves, companies must navigate tough trade-offs between making robots in-house versus partnering, and focus on amassing the data, talent, and infrastructure that will ultimately determine long-term advantage.

Pharma Access with Chinese Characteristics

Angela Shen investigates China’s pharmaceutical landscape as it undergoes major government-led reform. Through programs like the National Reimbursement Drug List (NRDL) and centralized volume-based procurement (CVBP), authorities have dramatically slashed drug prices, yet concerns about the quality and effectiveness of low-cost generics persist. Corruption and inefficiencies remain endemic, while access to cutting-edge imported drugs is still limited, partly due to Beijing’s protectionist tilt toward local firms. As China’s disease burden shifts toward chronic and complex conditions, its ambitious vision of “Healthy China 2030” hinges on whether it can deliver innovative treatments through a system strained by economic and political pressures.

WWIII

Nuclearization

In this interview, Vipin Narang, Pranay Vaddi, and Junichi Fukuda explores how the Trump administration’s approach to alliances is shaking the foundations of America’s nuclear umbrella. They discuss America’s historical role in preventing ally proliferation, and analyze the “hardware” (military capability) and “software” (political will) components of deterrence. While hardware investments continue, allies like Japan, South Korea, and Poland are increasingly hedging against perceived US retrenchment. China's rapid nuclear expansion compounds these fears. The panel warns that allied proliferation would weaken U.S. security, destabilize the global order, and risk entangling the US in unwanted conflicts.

Industrial Policy and Grand Strategy

Rickover’s Lessons

This article by Charles Yang highlights the enduring relevance of Admiral Hyman Rickover’s approach to industrial leadership. Rickover, known as the “Father of the Nuclear Navy,” spearheaded the development of nuclear propulsion through a hands-on, deeply technical, and unorthodox management style that emphasized personal responsibility, rigorous training, and relentless oversight. His success lay not just in technological breakthroughs but in building a resilient industrial ecosystem.

Manufacturing’s Missing Revolution

Despite early hype, the US has largely failed to realize the promise of the Industrial Internet of Things (IIoT). In this article, Gary Wang argues that the IIoT “revolution” faltered not due to a lack of technology, but because of deep coordination failures. IIoT is a patchwork of technologies requiring complex integration across connectivity, cloud computing, cybersecurity, and machine learning — a challenge the free market struggles to solve alone. While US manufacturers remain stuck in pilot projects, China has leapfrogged ahead by using top-down industrial policy to address technical bottlenecks and platform fragmentation, enabling broad adoption of automation and AI in “dark factories.” Wang warns that similar challenges threaten US leadership in AI and quantum computing, and calls for industrial policy that supports entire ecosystems, not just headline-grabbing tech — before the US falls even further behind.

How to Build Compute in America

As US demand for AI computing infrastructure surges, a looming bottleneck in power generation threatens to stall progress. This podcast explores the challenges in energy, permitting, and financing for scaling America’s AI infrastructure. Arnab Datta, Tim Fist, and Ben Della Rocca also discuss the promise of next-generation geothermal energy as a power solution alongside gas and solar, as well as fusion and small modular reactors in the long term.

How to Compete

In this podcast episode, “Tony Stark,” author of Breaking Beijing and Ex Supra, discusses what the US must prioritize to compete with China throughout each decade of the 21st century. Stark critiques Washington's lack of a coherent China strategy and warns that without decisive action, the US risks strategic drift while China expands its global influence and military capabilities. The conversation also explores how AI will change warfare, how foreign aid supports U.S. security interests, why literacy and education are critical to military effectiveness, and how thoughtful, independent writing can shape policy discourse.

Weapons of Cold War 2.0 + 'People's War' Invasion Fleet

In this installment of Friday Bites, Kyle Chan argues that the US-China conflict is a full-scale cold war, not just a trade war, encompassing economic, technological, military, and ideological competition. Both sides are wielding a range of tools — from tariffs to cyberattacks and supply chain disruptions — without clear escalation dominance, as each action inevitably harms both parties due to deep economic interdependence. In the second half, Joseph Webster argues that Taiwan is unprepared to confront an invasion assisted by civilian ships armed with drone fleets, and suggests ways to get serious about national defense.

Media mentions

Jordan and Angela Shen coauthored an opinion piece in the Washington Post, entitled “Trump’s crackdown on foreign students is a gift to China.”

Jordan had a ton of fun on TBPN discussing business in China, Deepseek, and the search for truth:

That was way too fun so I went in for a second time, not too happy about Trump’s S&T policy.

I also went on CNBC to discuss export controls and chip smuggling.

Finally, ChinaTalk got a shout-out in FTSG’s report on tech trends in 2025 as a “pioneer and power player.”

ChinaTalk is so lucky to have such a supportive audience. Thank you for being a part of this project!

Could America pursue an abundance agenda without the threat of the PRC? And can podcasters change the world?

To discuss, ChinaTalk interviewed Ezra Klein and Derek Thompson, who need no introduction, as well as Dan Wang, who has written all those beautiful annual letters and is back in the US as a research fellow at Kotkin’s Hoover History Lab. He has an excellent book called Breakneck coming out this August, but we’re saving that show for a little later this year.

Today, our conversation covers…

• The use of China as a rhetorical device in US domestic discourse,

• Oversimplified aspects of Chinese development, and why the bipartisan consensus surrounding Beijing might fail to produce a coherent strategy,

• The abundance agenda and technocratic vs prophetic strategies for policy change,

• How to conceptualize political actors complexly, including unions, corporations, and environmental groups,

• The value of podcasting and strategies for positively impacting the modern media environment.

Listen now on iTunes, Spotify, or your favorite podcast app.

So last week we published our 400th episode! I’ll be doing a Q&A show in the next few weeks. Leave your questions in the comments.

The Thucydides Stimulus

Jordan Schneider: Let me start with a line from Ezra’s show with Tom Friedman. Friedman said, “Whether I’m writing about China from Washington, or whether I’m writing about China from China, I’m always just writing about America. My goal is to use China as my permanent Sputnik.”

Ezra, you mentioned over email that initially there was more China in “Abundance,” but in the final text, I think it primarily just plays that Sputnik role too. What do we lose when policymakers and policy advocates treat China primarily as a rhetorical device rather than a complex object of study?

Ezra Klein: Those feel like two separate questions. One reason “Abundance” is not heavily about China is that I’m perfectly aware I don’t understand China. What I do understand is the gravity that China exerts on American politics.

We have a very complex relationship of antagonism, competitiveness, and envy with China.

Going back to at least the 2010s, probably before, I’ve begun to really notice this feeling in American politics that they can build and we can’t. This became a pathway through which different kinds of bipartisan legislation that would not otherwise have been bipartisan began to emerge.

The re-emergence of industrial policy in America is 100% about China. Take China out of the equation, and there is no re-emergence of American industrial policy. It’s reasonable from the American perspective, when you’re trying to understand American politics, to understand China as an American political object, because that’s what it actually is in our discourse.

American policymakers don’t understand China at all. Most of what they think about it has a high chance of proving to be dangerously misguided. Dan will be much more expert here than I will, but I’m very skeptical of the bipartisan consensus that has emerged. Nevertheless, it’s completely trackable that China exerts a force on American politics. It has reshaped the American political consensus, often in ways that operate in the shadows because they don’t become part of the major partisan fights of modern American politics.

Derek Thompson: The only thing I would add, because I also don’t think I understand China, is that this was primarily a book about trying to deeply understand not all of America, but some very specific questions — Why can’t America build houses? Why can’t America build clean energy? What’s wrong with America’s invention agenda? These are very narrow questions about this country. The book’s scope did not include a deep dive into Chinese industrial policy or the nature of Chinese politics.

My interest in China is one of relatively blue-sky curiosity. We have this term “the Thucydides trap,” which explains how throughout history, when you have a dominant geopolitical power and a new rival emerges, that new rival discombobulates the status quo power. Modern American history has demonstrated something more like not necessarily the Thucydides trap, but the “Thucydides stimulus" — the idea that when a new rival emerges, it can inspire the existing superpower to think differently.

Sometimes that Thucydides stimulus comes through a sense of geopolitical threat. I’m very interested in the history of Sputnik and how the Sputnik moment inspired all sorts of changes in American policy in the 1950s and 1960s. But there’s also an approach that isn’t based on fear of geopolitical threat, but rather on open curiosity. How does China build its trains so quickly? How does China build so many bike paths that are beautifully integrated into the environment? What are the different ways in which Chinese versus American politicians think about designing their society such that each could learn from the other?

Without venturing too far into territory we’re saving for Dan’s wonderful book, there’s a way to engage with this idea of the Thucydides stimulus that isn’t exclusively motivated by fear, but rather by open curiosity.

Jordan Schneider: I’m going to throw it to Dan, but I love how your response to my first question shows that you guys are the masters and I’m still the student. I was debating for a whole week what my first question should be, and then I just gave it to OpenAI and asked them to squish these two ideas together. Your seeing through that is very impressive. Dan?

Dan Wang: I would always be the first person to put my hand up to say I know nothing about what’s going on in China. That is always true.

Ezra Klein: Welcome to ChinaTalk, where nobody knows anything about China.

Dan Wang: Well, Jordan knows something about China.

Jordan Schneider: Less than Dan.

Dan Wang: China is very messy. That is always my first proposition about China — it is very big, and many things are true about China all at the same time. They are a country that claims to be pursuing “socialism with Chinese characteristics,” which is still one of the most wonderful political science terms ever.

What sort of socialism is this? In my view, this is one of the most right-wing regimes in the world. A country that would make any American conservative salivate in terms of its immigration restrictions, its incredible amount of manufacturing prowess, and its enforcement of very traditional gender roles in which men have to be very macho and women have to bear children.

China is all of these things. It is also a place where there are really wonderful bike paths, specifically in Shanghai. This year, Shanghai has completed around 500 parks. By 2030, they want to create 500 more parks. It is a country that is getting better and getting worse all at the same time.

Ezra Klein: This goes back to this idea of envy — the degree to which the right envies China is fascinating. It doesn’t just want to compete with it or beat it. It’s not just afraid of it. What it wants is to be more like it.

In wanting to be more like China, the right is now overlooking virtually every advantage and competitive strength America itself has.

America’s politicians are so obsessed with trying to take manufacturing back from China, which I don’t think they have a well-thought-through approach to doing, that they look quite ready to give up America’s financial power. They seem to have reconceived of dollar dominance, which used to be called the “exorbitant privilege” because we got so many advantages from it, as some sort of terrible weakness that has hollowed out our industrial base and that we need to shatter.

Throughout history, being the power that controls the money flows has proven to be an extraordinary lever of control. But it has been recast in current New Right thinking as a sort of feminized decadence — something that “not real” countries and “not real” powers do, a distraction from the “real economy” and the “real work” of making things.

I’m not against bringing back manufacturing. I support the CHIPS Act. There are many aspects of manufacturing that I would like to bring back. But we can become so envious that it becomes hard to see our own advantages and strengths, and then make serious policy built on what we are doing well. That strikes me as one of the profound weaknesses of Washington’s approach to policymaking. It is so obsessed with what we are not doing well that it seems ready to set fire to what we are doing well.

Dan Wang: Edward Luttwak has this term “great state autism,” which he created regarding the US thinking about the Soviet Union. There is certainly an aspect, once you are a “superpower,” of becoming obsessed with the other party. You have to choose your enemies very carefully because you will end up looking quite a lot like them.

I wonder in which way the US is actually quite mimetic in thinking about how to be like the other superpower. In my sense, China — after the 2008 financial crisis, or perhaps after 2012 when Xi came into power — Beijing decided it does not really want to look too much like the US, which has been driven by Wall Street on one coast and Silicon Valley on the other in terms of economic growth.

Rather, Beijing has this purely mercantilist view, which would be recognizable to anyone in the 18th century, which is, “Let’s just make a ton of products. That is our source of power, that is our source of advantage.”

Jordan Schneider: Maybe now’s the time to bring up Gerstle and his book, which Ezra has been referencing frequently lately. His argument is that the Soviet Union as a memetic object facilitated a long 20th century of liberal governance. People don’t date it to the 1940s but to 1917 with Lenin and all the progressivism that unlocked. We saw Eisenhower buying into Social Security and domestic politics, plus the role of the USSR in the US Civil Rights movement. It’s interesting because there’s a bit of that with Todd Young and Mike Gallagher trying to implement a different version of self-strengthening than the one dominant in the White House today. I’m curious about lessons from how the Soviet Union shaped American politics. What different futures could that suggest for the US over the next few decades?

Derek Thompson: Gary Gerstle, the Cambridge historian, has this beautiful theory of political orders, which says American political eras are essentially defined by both an internal conflict and an external threat. Together, these create a consensus between parties that lasts for decades, even as headline disputes make it seem like parties are at each other’s throats.

The two big political orders are the New Deal order from the 1930s through the 1960s-70s. The initial internal crisis was the Great Depression, while the external threat was the rise of communism and socialism around the world, particularly in Europe. The New Deal order essentially synthesized these ideas by responding to the Great Depression and softening the introduction of socialism to American politics. It created a political order that was much more expansive with aggressive and muscular domestic policy, spending to reduce unemployment and poverty through the Social Security Act, employing millions of people.

As you mentioned, Dwight Eisenhower in many ways acquiesced to that political order in the 1950s. He was a strong advocate of social welfare policies and a proponent of continuing to build in America. He built the highway system.

In the 1970s and 1980s, that order broke down. Instead of the Great Depression, you had economic stagnation in the 1970s. Instead of the spectral threat of socialism in Europe, you had the direct threat of the Soviet Union and its capacities. A new political order emerged, defined by individualism rather than the collectivism of the New Deal era. Gerstle calls this the neoliberal order, which reigned over American politics from the 1980s to roughly the 2010s.

Gerstle’s theory, which I think Ezra and I subscribe to, is that we’ve seen a decline in that neoliberal order. Today’s problems cannot just be solved by cutting taxes or embracing Reaganite conservatism. Housing scarcity, building sufficient clean energy, and building the technology we invent in the US — these aren’t problems solved merely by cutting taxes and deregulating at the national level. We need more specific solutions.

Abundance liberalism is our answer to these new problems. It tries to synthesize the best of the New Deal order and the neoliberal order. The New Deal order taught us about the power of government to intervene and see what markets themselves cannot see. The neoliberal order recognized that government bureaucracy can sometimes get in its own way. We’re trying to advance a theory of progressive governance that sees how government creates rules for itself that make it harder to achieve outcomes.

Abundance liberalism finds a way to advance a muscular theory of government that says we can build houses, clean energy, and do extraordinary things with technology. But this requires identifying how we’ve written rules that get in our own way.

Dan Wang: Derek, why fold neoliberalism into this big package? Why not just embrace the New Deal agenda in its classical flavor? When I think about the New Deal, I think about the construction of power plants, homes, and broader infrastructure. They’d pack the courts if necessary because that was part of the agenda. What are we adding with the neoliberal flavor here?

Derek Thompson: When I say we’re adding a neoliberal flavor, I mean there were insights in the 1970s and 1980s about failures of the New Deal order that were accurate diagnoses. The New Deal order built extensively, often without consideration for either the voices of the marginalized or the poor, or for the environment. As a result, one legacy of the New Deal order is that the amount of construction was partially responsible for creating a groundswell against the state and against the growth machine. This empowered the legalistic revolution of the 1960s and 1970s that we now see across the country — in NEPA, in CEQA, in the proceduralism fetish, in adversarial legalism at many different levels of government. We are, in many ways, a society defined by a very activist lawyer class.

It’s important to recognize that there were legitimate legal responses to the growth machine that emerged in the 1960s and 1970s. Another part is environmentalism. The world of the 1940s and 1950s bequeathed to us by the New Deal age was truly disgusting — the rivers and air were disgusting, and tailpipe emissions from our cars were choking the planet. It was important to pass environmental rules to allow cleaner growth. We succeeded in many ways — the air is cleaner, the water is cleaner, and tailpipe emissions are a lot lower.

Now we need a new synthesis because climate change presents different environmental problems than those of the 1940s and 1950s. We need ways to build clean energy that allow people to live modern lives without choking the biosphere. That’s why we need a new synthesis rather than returning to the 1930s.

The last point: when people ask why we can’t just roll back the clock to 1932, remember that the government then, responding to the Great Depression, hired millions of people through the Works Progress Administration. Today’s US government, with its deficit and current interest rates, not to mention the political climate, simply doesn’t have the ability to hire 5 million people to build something like the Tennessee Valley Authority. It’s not going to happen.

To build houses, energy infrastructure, or transit today, we need the private sector to do much of that building. This means we need to build a legal architecture that allows the private sector to build without despoiling the planet or running roughshod over consumer or environmental interests.

Jordan Schneider: I understand your Iraq War hangover perspective — if there’s this much consensus, maybe something is fishy. But I’m frustrated, and perhaps this shows a broader frustration with how the show has evolved into “Jordan, Media Critic.” It seems to be less about learning about a field and more about booking someone to let Ezra make a point. Over the past five years, you’ve had Tom Friedman, Jessica Chenweis, and Dan, but the show with Dan wasn’t really about Chinese foreign policy. You’re leaning heavily on one side of the professional community when it’s now split roughly 90-10 in the other direction. You have a big platform, Ezra, and I’m curious how you feel about weighing in versus interrogating policy questions that aren’t directly in your area of expertise.

Ezra Klein: One pattern I notice in media criticism is that people feel you aren’t using your platform in a curious enough way when they disagree with you, but when they agree, they find it perfectly curious. I get this from many different perspectives.

When I think the consensus is wrong, my show goes counter-consensus. When I thought Joe Biden was too old to run again while most people believed the primary had settled it, I was willing to take heat for saying Democrats should have an open convention. In this particular case, I think the ambient coverage of China on my show — except for a few specific China episodes, of which there have only been three or four — reflects the broadly speaking Washington consensus that we need industrial policy to recapture major industrial sectors from China.

What worries me most, having covered Washington for a long time, is when things become unsayable without good evidence for why they shouldn’t be said. I don’t mean within the professional China debate community, but within the political community of people who need to win elections and advance their careers. I’m not a dove who thinks there are no problems with the Chinese Communist Party, but I’m not convinced the relentless buildup of antagonism and increasingly harsh policies is working — or that we’re even evaluating if they’re working.

My show isn’t unwilling to give air to mainstream perspectives. I had Ben Buchanan on AI policy and Jake Sullivan, who defended efforts to deny China certain technological exports that would allow them to attain leadership. At the same time, Tom Friedman’s point — which you might call dovishness — is that Washington tends to compete with China as it was 15 years ago, failing to recognize how much manufacturing innovation they’re currently capable of. The belief that we can simply wall ourselves off or engage in a trade war and rebuild the manufacturing sector they’ve painstakingly developed over time isn’t clearly supported. Maybe it’s clear to you — I’d actually like to hear you defend whether tariff policy as currently structured will achieve that goal.

More broadly, is it so bad for the world if China makes many solar panels and EVs? If climate change is as significant a problem as I believe, that rapidly accelerates the dispersion of renewable energy and electric vehicles. I understand why the Biden administration made its decisions. I’m not even sure they’re wrong, but I would like to hear the other side argued more publicly.

Similarly, in AI governance, is the race dynamic between our countries beneficial? If you have concerns about AI safety — and I still do, even as it’s become somewhat gauche to express them — the fact that both countries are willing to disregard other concerns to beat each other to usable AGI should raise concerns about the structure of development emerging on both sides.

I don’t see the preconditions for wise policymaking here. The absence of those preconditions is one reason the Trump administration, in its careening effort to construct some kind of sensible tariff policy, retreated from an all-out trade war with the entire world to focusing on China. They thought that would be more defensible, but did they plan for it? Did they think through the outcomes?

I’d turn this question back to you, Jordan: Do you think the current direction of US-China conversation is leading us toward good policy?

Jordan Schneider: Obviously not, but that feels like a straw man. You’re asking me to defend Trump’s tariffs.

Ezra Klein: Hold on. I want to push this because you brought it up. The Friedman conversation is about Trump’s tariffs. It’s a view that we are getting these policies because of the views that have begun to take hold, at least in the Republican Party, about China.

Jordan Schneider: The issue is that Jake Sullivan and Ben Buchanan are not people who have spent much time reading party documents. Fundamental to all of this is understanding the system and its intentions because China is relatively equal to the US from a national power perspective and will remain so for the coming decades, regardless of what we do. Understanding Xi and the broader system is a very important intellectual foundation that deserves rigorous interrogation. Tom Friedman spending a week at the Huawei Campus won’t necessarily give you that.

Ezra Klein: But this is a trade policy conversation. What would change in your trade policy from understanding their objectives? Let’s have the concrete conversation here. I agree my show hasn’t dug into party documents — there are reasons for that, but regardless, we haven’t done it. In terms of what we’re trying to examine, which is the output of US policy and whether it will achieve our goals, what do you think is being missed? What premise needs to be inserted?

Jordan Schneider: What are we missing? The world has the potential to go in different directions. It’s more difficult in the context of Trump because I’m not sure that China being a boogeyman is what’s empowering Trump. Yes, at some level it helped him get elected, but he could say whatever he wanted because he has this hypnotic control of the Republican Party. I don’t know why I was scared of this show, Dan, because I don’t have podcast hosts who just throw this stuff back at me.

Ezra Klein: I’m not —

Derek Thompson: Can I ask a version of the question?

Ezra Klein: Yeah.

Derek Thompson: Let’s say that I am a dedicated listener of the Ezra Klein show. I just mainline the podcast, and his ideas become my ideology. What is my ideology missing right now regarding China?

Jordan Schneider: That China is an ideologically driven system. The world in which China is able to more dramatically reshape the global balance of power over a 15-year horizon is one we should be really concerned about. I have a deep discomfort with the timeline where America and its friends are waning relative to China on a multi-decadal horizon.

It is not possible to know with a high degree of confidence what China really wants, but there’s at least a 25% chance that the Chinese government we get in the coming decades is a deeply Leninist and expansionary one. That is a scary timeline that the world needs to price in and prepare for.

That’s for the modal Ezra listener. For the modal DC Hawk, I’d just say that Chinese people are people too.

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Dan Wang: I definitely want to defend the dulcet tones of both Ezra and Derek, but as an amateur member of the community of China watchers, there are debates that aren’t easily resolved. For example, a question I would pose to US policymakers would be: Do you judge it is in America’s interest that China is richer, or is America better off if China is poorer? Having that answer would help structure many subsequent policy choices.

There is debate within the China community about how expansionist China is. They certainly want Taiwan — no question there. But is the next step that they want to take Vietnam, Philippines, as well as Japan? People are extensively debating this. When we can answer these more technocratic questions and reach some agreement, many things become easier.

This isn’t about Ezra’s show, but in the US there aren’t many experts really trying to debate and resolve these questions. In my field studying Chinese technology development and manufacturing, policymakers frequently use the laziest trope that China got where it is totally through stealing. This is easily disprovable, yet we hear it all the time. As long as we can’t move beyond these tropes, it becomes much more difficult to resolve even the harder questions.

Ezra Klein: It’s funny because I definitely didn’t expect to come on the show and articulate my own quite weak philosophy of China. But this goes back to what Tom was saying and what I’ve said in the book — this is a way of talking about America. Jordan, if your disagreement with me is that you think I’m excited for a world in 15 years where America has broken substantially and China has reshaped the global order, let me set your mind at ease. As dulcet as my tones may be, I don’t want that world. What I want is a world where we try to achieve our goals through sensible policy aims.

My views are actually quite weak on many of these things. There are areas where I have very strong views about how America should build more and faster. A big portion of the book Derek and I wrote is fundamentally motivated, as we say at the end, by competition with China. We believe we won’t continue thriving as a nation in terms of our own strength if we don’t get better at manufacturing, construction, deployment, innovation, and cyclical experimental policy. There’s something for us to learn and compete with there.

On the narrower level, there’s a view that has taken hold in Washington that some version of decoupling is the way forward. One place where I’m uncertain — not certain I disagree, but the conventional view is so dominant that I’m more interested in the counter-argument — is Tom’s argument from the Huawei campus and his other experiences. He suggests we should do with China in the 2020s what we did with Japan in the 1980s and 1990s when they were outcompeting us on cars: create joint ventures in America where we develop their technological and manufacturing processes and embed them in our own companies. China did this with us too.

In Washington, this is considered virtually unsayable. I’d like to hear a better argument against it than I’ve heard because it’s not obvious that our current approach will accelerate the sophistication of our manufacturing chains.

My view is similar to Dan’s — I’d like us to have more precise conversations about means and ends. But that’s difficult in the current political atmosphere where you have to out-compete others to be symbolically tough or hawkish.

The Taiwan problem and the Indonesia question are both very severe issues somewhat beyond my ability to address confidently. America has a very unclear internal stance on whether we would actually go to war to defend Taiwan — people don’t want to answer that, and I don’t even know what I think the answer should be.

Regarding what we need to do to accelerate our manufacturing and innovative ecosystems, the question of whether we should be decoupling or trying to couple and do tech transfer, engaging in more direct competition with products like Chinese EVs while heavily subsidizing our own industries with clear goals — that doesn’t seem completely crazy to me.

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Jordan Schneider: Maybe the distinction is between the technocratic and the prophetic. Once discussions turn into US-China World War III prophecy, that’s where all of us get frustrated. The way you both approached abundance — you started on the technocratic side of writing. There’s now more Frederick Douglass and MLK elements — creating a vision with moral force behind it to transform policy ideas into something rhetorical that resonates. I’m curious how you think about broader theories of policy change, technocratic versus prophetic voices, and how you grappled with that in framing the book and discussing it on your media tour.

Derek Thompson: The book is both poetry and prose. We have an introduction and conclusion with sentences that I described to Ezra as aphoristic and epigrammatic — sentences that wanted to be underlined, that wanted to have that glow on Kindle when 10,000 people highlight them. It’s strange to write for that piece of coding to become illuminated in the text, but that’s writing in a memetic way — a very 2025 approach. We want to write sentences people will quote and remember, and use terms that will infect the software of people’s minds. People talk about an abundance agenda now.

Neither Ezra nor I are trying to be shy about wanting aspects of this book to be highly memetic while other aspects are admittedly and painstakingly technical. The analysis of Tahanan (the affordable housing complex in San Francisco), the analysis of funding opportunities for chips, the history of the NIH in America, and the development of solar technology — these are highly technical sections. We’re not just trying to be pie-in-the-sky poets. We really want to understand how the world works, how government works, because there’s no way to understand how to make it work better without understanding the thing in the first place.

During the podcast and speaking tour, I’ve repeatedly been asked how we expect this book to make contact with the 2026 midterms or the 2028 presidential election cycle. My feeling, which I deeply believe, is that nobody votes for books. Even in American history, where you could weakly argue a president was influenced by a book, people are still voting for that person. People vote for people. FDR voters didn’t elect John Maynard Keynes in 1932 — they elected someone inspired by Keynes. No one elected Milton Friedman in 1980, but Ronald Reagan was inspired by Friedman.

The job of writers, podcasters, and public intellectuals is this — in a crisis, and crises will come perhaps twice as fast in this decade as previous ones, people in power reach for ideas that are on the shelf around them. They throw out an arm and say, “What’s the idea nearest to me that can help explain this moment of chaos?"

What we’re trying to do with a book like this is stock the shelves with better ideas, allowing Democrats to respond to housing crises in San Francisco or Los Angeles, clean energy construction challenges in Massachusetts, or the general problem that America invents many things but can’t seem to build them the way the Chinese can. How do we resolve these observed crises? You reach for ideas on the shelf, and abundance is trying to be on that shelf.

We are trying to influence people, but we understand no one’s ultimately going to vote for a book. The world changes because of people filling out institutions — ultimately a result of personalities we can’t directly influence.

Jordan Schneider: Ezra, do you want to address the “Ezra as America’s only real rabbi” angle? I felt like I got more substantive Israel content after October 7th from you than anywhere else. You started doing very wonky Obamacare analysis, and now there’s a values discussion that you inject into more people’s lives than perhaps anyone else in the country.

Ezra Klein: I appreciate that. The reputation I developed in my wonk blog days, in my Obamacare days, as somebody who only cared about appendix tables and CBO documents was never true. I do care about appendix tables and CBO documents and the granular sections Derek described. I believe you need the narrow, granular texture of things to understand them.

I also believe that moments and eras have zeitgeists and values. I’m probably more of a mystic than people realize — although a coming podcast with Ross Douthat, probably out by the time this airs, will reveal some of that. I try to be honest about my own reactions and struggles with the moments we’re in. Like anyone else, my reaction in many of these moments is emotional.

Something I believe strongly about my work is that if you aren’t making space for the emotional layer of reaction, you aren’t making space for the reaction itself. If you can’t speak to where the audience is emotionally — which may or may not be where you are — it will be very hard to get them to listen. If people don’t feel understood, they won’t listen to you, and maybe they shouldn’t.

I don’t think I’m alone in doing this, but it has needed doing. I’ve always felt as a writer, and maybe as a person, that the emotional layer of moments isn’t unusually visible to me — it’s something that feels unusually invisible to others. I don’t know what it’s like to walk through the world and not be incredibly affected by the emotional currents of every room you’re in. I meet people who don’t seem as overwhelmed by this, and their lives seem blissful to me. It’s just how I experience the world, and I think it comes out in the show.

When you’re writing a piece or doing a podcast — and I’d be curious for Derek’s reflection on this because he’s very good at it too — you have the audience’s beliefs in your head. What am I arguing with? What is the structure of prevailing sentiment? How is the audience feeling at moments of high emotion, like October 7th or this period with Donald Trump? That’s part of the structure you’re engaging with. To ignore it makes no sense.

I was never a fan of the Ben Shapiro line that “facts don’t care about your feelings.” Maybe facts don’t care, but people sure care. Feelings sometimes should sensitize us to the idea that there are facts we don’t yet know or experiences we haven’t absorbed. It would be hard to find many people in journalism more interested in the wonky details of policy than I am, but perhaps because of that interest, I understand that wonkiness only goes so far and misses a lot. We never have full understanding of anything. We were saying this at the beginning with China — the idea that any of us, anybody in this debate, even anybody in China itself, can understand a country that big? I don’t understand America. You have to recognize that there are many ways of knowing.

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Derek Thompson: I love all of that. I agree with just about all of it. What we do — me, Ezra, Jordan, Dan — we make media. I don’t know if the full value of media is feelings, but certainly an enormous amount of the value of media is feelings, even when you read a very detailed analysis of wonky things.

Just the other day, I had a conversation with an astrophysicist about transmission spectroscopy, which is how we measure faraway starlight passing through planets 100 light years away. As that light passes through those planets’ atmospheres, we can analyze the wavelengths to determine which chemicals have blocked aspects of that starlight. By determining that, we can guess what chemicals are present on that distant planet. We can say, “That blur on a telescope — that’s ammonia, methane, dimethyl sulfide. That means that planet 100 million light years away has aquatic life, has algae."

The details are technical, but the value is wonder. The value is a feeling. Ultimately what I want from people who listen to my podcast or read this book — it’s always nice to hear someone learned something, that the takeaway was informational. That’s beautiful. I love learning and information. But information itself feels like something — it feels like a dopamine hit, the relief of anxiety that I didn’t know something and now I do, or that my worldview, my understanding of what’s possible in human life, has expanded by one unit of new fact. That’s all feeling.

The greatest compliment I can receive is “your book made me feel hope” or “your podcast made me feel wonder.” When people came up to Ezra and me for book signings, many said, “You make me feel sane.” They had five seconds to speak to someone they’d listened to for hundreds or thousands of hours, and the words that came out were “you make me feel sane.” That’s the outcome of the work.

I agree with Ezra. Not only are my emotions front of mind when I’m writing, but also the audience’s emotions. That’s true both within podcasts and across podcasts. Within podcasts, I love the tension between going deep into something technical and then zooming out to the emotional impact. Across podcasts, after doing many shows about how problematic tariffs are, I might say, “We need to talk about aliens. We have to discuss transmission spectroscopy so people can get excited about detecting alien chemicals on planets 100 light years away.” We need to balance.

This play of feelings, this idea that our work exists as a kind of symphony of emotions within and across podcasts, is extremely present for me. It’s great to hear it’s present for Ezra as well.

Dan Wang: It’s really wonderful that these dulcet tones are getting more fiery. Maybe no one votes for a book, Derek, but I would vote for podcasts. I would cast a vote for Plain English, and I would cast a vote for the Ezra Klein Show.

Jordan Schneider: Now we have a choose-your-own-adventure here. Making people feel sane and heard is lovely, but there’s also a dark version of abundance. If you weren’t, as you self-describe, “pathologically agreeable,” where you have more enemies and villains — what would that book look like? How would that be embodied?

Alternatively, you partially answered this in the past 10 minutes, but are there other failure states you worry about for yourselves over the next five or ten years that you’re trying to orient away from in your work?

Ezra Klein: Let me take the first question about dark abundance. People kept telling Derek particularly that he’s too agreeable, but they tell me that too. Matt Yglesias had this funny reaction to the book where he said, “I read this book and thought it was good, but too agreeable. Nobody would argue over it because it was too soft" — and then everybody argued over it. So maybe he was wrong.

One thing I’ve learned on the tour is that I have a different sense of how to treat coalitional politics than many people I agree with, both to my right and left. Others seem more certain that you can create a group — call it corporations, unions, or whatever — and politics is really about deciding if that’s an in-group or out-group. If it’s an out-group, you should attack it as your villain. If it’s an in-group, you should ally with them as your partner.

I view this much more situationally. Environmentalists, unions, corporations — these are very big, diverse categories with a lot of internal fractiousness, as anyone who has reported on them knows, and I have reported on all of them. Different issues have different coalition structures.

It’s not that our book doesn’t have “villains,” although we don’t think many of the people we discuss are ill-intentioned. The book has plenty of instances where you can see who is standing in the way or governing poorly, and that’s led many people to get angry. When I talk to centrists, they often ask, “Aren’t public interest unions your real enemy?” From the left, the question is more, “When will you admit that corporations and corporate power are the real enemy?"

Jordan Schneider: And that’s just not interesting.

Ezra Klein: I wouldn’t say it’s not interesting. I’ve been preparing for a conversation with Zephyr Teachout and someone else that will reflect some of this debate. I’ve been reading her work and thinking about how she views the endpoint as power itself. Her critique of many she argues with across domains is that they focus on specific issues but not on power. There’s a sense that if you can move power from one place to another, you’ve solved the problem.

But what if that relocated power is used poorly? Her confidence seems to be that if you moved power from corporations to government, it would be well used. Maybe sometimes it would, but often it wouldn’t. Government gets captured by many different groups, not just corporations.

Similarly, the new left moved power from government to individuals, planning meetings, and people who can bring lawsuits, assuming individuals would be safer repositories of power than government and should tie government up in process. Sometimes that’s true; sometimes it’s not.

Many people seem to think there’s some secret “Straussian” version of Abundance in the back of our minds where we’re extremely clear about who the villains are, but due to our agreeable nature, we edited that out. Much of Abundance is an argument about being outcome-oriented, asking what we need more of and how to get it, then being rigorous about the answer.

Sometimes that leads to identifying corporate interventions that have blocked progress. In other places, it’s local homeowners or environmental groups. There are places where unions use environmental laws for reasons unrelated to the environment, making these laws potent tools of delay. Then we can’t reform environmental law in California because these groups are so committed to leveraging it that they resist any changes, even though these laws block things we need for other reasons.

There isn’t a “dark Abundance” book sitting somewhere. We don’t have the luxury of believing in some stable equilibrium of interests that gets us what we want. It’s about being deeply committed to achieving what we promise. If certain groups stand in the way of those achievements, then on that issue, they’re not our allies, and we should try to overcome that problem.

Derek Thompson: I want to ground Ezra’s principles in this current news moment because they’re so appropriate. When I talk with people on the left — I was just on Mehdi Hasan’s show the other day — they ask versions of this question: “Why isn’t your book more anti-corporate? Why isn’t it more anti-billionaire or anti-oligarchical?"

I wish I had this framing then: I don’t see business as the permanent out-group of progressivism, and I don’t see government as necessarily the singular, appropriate wielder of democratic interests. Look at what’s happening right now. The government is trying to take away the independence of the Federal Reserve. Trump has bragged about using tariff policy to try to crash the stock market. They’re using government power to entirely reshape the economy in ways that have been terrible for manufacturing.

Meanwhile, Wall Street is begging Scott Bessent to keep the Fed independent, to not crash the economy, and to remove these tariffs to protect the manufacturing sector. If your first principle is “if Wall Street asks for it, then it’s bad,” you find yourself questioning the independence of the Federal Reserve or defending the idea of trying to disrupt the stock market through random tariffs on various countries.

It’s much more helpful to recognize that in-groups and out-groups aren’t universal — they’re situational. It’s better to reason from first principles of politics rather than assigning entire groups as allies versus enemies. I hope that came across in the book, for better or worse. I’m really against designating entire groups as permanent enemies of progress, because economics is complicated and life is complicated, and sometimes people are on both sides of issues.

Jordan Schneider: Let’s speed it up. I’m going to ask you five different questions about hosting podcasts. You can pick whichever ones you want to answer: Do you have magic words you give as a pre-recording pep talk to guests? What goes through your heads during interviews? What tricks do you use to turn around guests who are performing at a B-minus level for the first 10 minutes? What are you working on as interviewers? Are there any content ideas or initiatives you’d pursue if you weren’t affiliated with large outlets?

Derek Thompson: Let me answer the meta question about shepherding guests who aren’t giving me what I want in the moment, because it’s a really tough challenge. Sometimes you can feel the conversation slipping out of your hands.

I’m never afraid to simply step up and say, “Hey, can we go back to the very first question? This is on me. I think I understand how to work our way through this conversation, and I’m going to ask a different set of questions. If you want to play with me here, let’s do A, B, C."

I try to be relatively explicit about what I want if the conversation isn’t going as planned. Much of this is to prevent the guest from feeling it’s their fault. If they become self-conscious, they develop this metacognitive layer of thought constantly judging their thinking, which prevents them from being expressive, interesting, and fluent. I try to blame it on myself and say, “Let’s try essentially a new game. We played game number one; let’s play game number two and see how it goes.” That’s how I massage the conversation.

Regarding the guidance I give guests, I don’t want to be overly prescriptive. Ezra and I were actually talking earlier about another podcaster who is unusually prescriptive at the beginning of interviews. I want to hear guests’ natural personalities come through. However, I remind them, especially those in technical fields: “This is a podcast for a generalist audience. I want you to use jargon — because jargon actually sounds cool — but please slow down and explain everything that isn’t basic 101 material in a class you might teach."

This encourages them to recognize when they’re using specific terminology. For example, as they begin talking about transmission spectroscopy, they’ll think, “Wow, that was super multisyllabic. I should definitely slow down here.” I want the conversation to be slow, conversational, and feel like a discussion after half a beer. But I typically don’t give them that level of specificity in my instructions.

Ezra Klein: When something isn’t working, you have to try something else. The more it’s not working, the more radically you need to pivot. I don’t always succeed at this. It’s very hard to abandon the mental map you had for the conversation.

Sometimes you’re just hoping things will improve later, and you’ll edit out the beginning. Sometimes I decide, “We’re throwing away the first 12 minutes of that one.” But you have to start trying riskier strategies to knock people off their current track.

The truly challenging situation is when a guest clams up — when they’re unwilling to be as open on mic as they were in previous reporting, or they’re simply nervous. To some degree, you sometimes have to rescue them. Usually, there’s a conversational vein that will activate them. Being very sensitive to people’s energy in the moment is important.

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Jordan Schneider: Aside from having a better one-line takeaway for what people should think about China, do you have other feedback for China Talk? What should we be doing more of here?

Derek Thompson: I learn so much from your Substack and your show. Sometimes I feel there’s a historical layer I always appreciate — understanding how things got to where they are. People who are experts in a particular domain often forget that others might want to walk the path they walked to arrive at that moment of relative expertise.

I’m always a fan — and maybe this is just my general preference for explainer media — of stepping back and providing a little bit of the “how we got here” context. That’s not so much a criticism as an observation, but it’s a type of media I always appreciate.

Ezra Klein: You can never have too much Dan Wang. He’s been the one on the island.

Jordan Schneider: Derek’s show is called Plain English, but I’m more in the Dwarkesh mindset of just doing podcasts at my level. The audience will get 80% of it, and if needed, they can Google things. ChatGPT can now fill in the gaps for you. But I hear your point.

Let me shift topics. Ezra, I went back to your Tim Ferriss interview where you spoke about how Matt Yglesias giving you an encouraging comment when you were 19 was a big psychological boost to continue down this unusual path of writing on the internet.

I’d like all three of us to do something similar now — highlight people in the sub-10,000 Substack follower range who we think are doing excellent work.

I’ll start — , who has a weird and offbeat perspective on China and broader Asia. She went to Taiwan recently and is taking an interesting approach to technology writing.

, who writes a Substack called Sinocities, exploring regions in China. There’s so much focus on Beijing, Shanghai, and Shenzhen that examining what’s happening in other provinces is really valuable.

is great. He actually dives deep into what Huawei and BYD are doing in the broader Chinese industrial ecosystem. He can be a better guide than someone like Tom Friedman.

Lastly , who publishes less frequently but offers deep dives into Chinese economic policy and communist ideology, covering both the Soviet Union and China, which I think are excellent.

Let’s go around. Who would you like to highlight?

Dan Wang: I have only one nomination — Jordan Schneider of ChinaTalk. He brings tremendous enthusiasm, making a potentially dry topic broadly accessible. Today, we heard not only from the mystical side of Ezra but also about starlight from Derek. You don’t expect that when you tune into ChinaTalk, but that’s what you get.

Ezra Klein: To be honest, having written a book with Derek, you can’t get this guy to stop talking about starlight. There was a beautiful starseed passage that I don’t think made it into the final book — I believe because we removed some of the nuclear material. Give Derek 30 minutes, and you’re guaranteed to hear about starlight.

I’ll recommend , whose “Programmable Matter” Substack is absolutely essential. He’s one of the great minds of our time.

— her Substack is called “Eating Policy” — it goes more deeply into how policy actually works in practice than almost anyone else.

I’ll also recommend , a professor and expert in administrative law and administrative complexity. His Substack is called “Can We Still Govern?”

Dan Wang: I second Henry Farrell. I think of Henry as a giant intellectual teddy bear. Whenever I see Henry, all I want to do is grab him in my arms and squeeze.

Derek Thompson: My two recommendations come from the world of science — and , both exquisite writers and wonderful thinkers on genetics, innovation, culture, and how science actually works. I’m incredibly interested in various scientific frontiers right now and always hungry for people who can explain complex concepts clearly and memorably. They both excel at what they do.

Mood Music:

Arrian Ebrahimi is a J.D. candidate at Georgetown Law and a former Yenching Scholar at Peking University. Today, he’ll attempt to quantify China’s state equity investments in semiconductor manufacturing equipment. You can read more of Arrian’s writing on the excellent Chip Capitols Substack. Special thanks to Lily Ottinger for assisting with the charts.

The recent tariff chaos — first exempting only the most advanced semiconductors, then exempting a broad base of electronics important, followed by the current waiting period for more calculated semiconductor tariffs — should not come as a surprise.

Not only was the President sounding a clarion call for tariffs through the 2024 campaign, but rumors were circulating in Washington and foreign capitals that the then-candidate Trump’s tariff wishes would manifest as a tariff on the Chinese semiconductor content of downstream electronics imported into the U.S. A New York Times article recently confirmed those rumors by unnamed administration sources.

Targeting the Chinese chip content of electronics reflects a concern over the PRC’s semiconductor industrial policy that is not unique to President Trump, nor even to U.S. policymakers. European policymakers have also sounded the alarm over China’s allegedly subsidy-induced mature node overcapacity, and your author spoke at a European Commission event in Brussels last November to address just those concerns.

Washington and Brussels’ concerns, however, sound as they grasp in the dark for answers to one as-yet unanswered question: How much public money is the Chinese government spending on semiconductors… total?

Many studies over the past half-decade have tried to figure out how public funds flow from the various organs of the Chinese government to the semiconductor sector. However, the use of conservative methodologies has prevented scholars from uncovering numbers for the entire ecosystem. The two standard approaches are:

1. Policy Announcement Hunting: China-watching platforms have tried compiling announcements of new semiconductor incentive schemes from China’s central and local governments (see Chip Capitols here on local government programs and here on central government tax subsidies). These program compilations help explain what sorts of policy tools the Chinese government deploys, but they cannot provide even a ballpark number for the total amount of RMB invested, because the Chinese government does not have transparency standards for public expenditures in the way the U.S. does.

2. Public Company Calculations: The OECD’s seminal 2019 report on market distortions in the semiconductor industry examined the subsidies that governments around the world, including China, gave to their champions. However, the study limited itself to 21 publicly listed firms, only 2 of which were Chinese, because private companies do not have annual financial filings from which they could pull statistics on state investments and subsidies. This approach offers greater accuracy, but only captures a small slice of the Chinese public investment pie.

I set out to compile data as comprehensively as possible on Chinese equity investments, subsidy grants, and tax credits for the country's key semiconductor manufacturing equipment (SME) companies — regardless of whether they are public or private. This challenge required estimation based on the limited public statistics available for private companies, but has allowed me to amass a treasure trove of insights about the Chinese SME sector.

Estimation is critical for reaching conclusions about the macro-state of upstream Chinese chipmaking equipment firms. The SME sector is small — relatively few firms are publicly listed, and some of the most important firms, like Shanghai Micro Electronics Equipment (上海微电子) (China’s only lithography firm), are notably absent from public markets. At the other end of the spectrum, Huawei has increasingly sought to integrate itself vertically by investing in Shenzhen’s SiCarrier (深圳市新凯来技术有限公司), but public numbers are not available about that nascent company which is yet to release most of its products to the open market. Notably, Huawei does not count among the top investors of any of the public SME firms surveyed in this article, suggesting its SME investments are focused nearly exclusively on firms like SiCarrier that haven’t attracted attention from the state-backed Big Fund or institutional private investors.

Ass more Chinese SME firms go public and their financial details become available, I will invariably need to revise these findings. Nonetheless, the world deserves a first (if fuzzy) glance at the totality of China’s industrial policy for chipmaking equipment. In this first of two articles, we find that:

• Government and private-sector investments into SME firms dropped precipitously in 2022, the year of China’s COVID lockdowns, and only recovered slightly in 2023 in the wake of the U.S.’s October 2022 export controls.

• Beijing’s investment decisions have no correlation, positively or negatively, with SOE investment decisions. Their choices of which SME firms to invest in and when to invest are entirely disjointed.

• The amount of liquidity created for companies via subsidies is much smaller than the liquidity the PRC government creates via equity investments. In 2021, subsidies stood at 27% of investments, in 2022 at 31%, and in 2023 at 28%.

• Within the subsidy bucket, tax credits have fallen sharply as a tool of industrial policy, and politically maleable grants have come to occupy the majority of China’s subsidy tools.