I spent ten days in Norway this summer. What follows are reflections from my time there on Oslo, the Vikings, and WWII.

Oslo Vibes

“This place isn’t perfect Jordan,” a civil servant told me, “please tell me you won’t make that your angle.” I then asked him what the worst neighborhood in Oslo is, walked there, and felt it was nicer than half of Manhattan.

The first few days of 19 hours of sunlight in 72-degree weather were an unparalleled endorphin rush, but by day six I felt a little strung out.

Servicepeople regardless of your race start conversations in Norwegian so as to not make immigrants feel unwelcome.

I played some pickup sand volleyball in one of the thousand Oslo parks with a Kurdish culture affinity club. No-one on my team could tell me how to say “nice serve” in Kurdish but when some Kendrick came on their speakers, they all sang along to “certified Loverboy, certified pedophile.”

Chinese EV showrooms dotted Oslo, with Nio taking plum position on the main street right outside parliament. The salesman there said vibes are mostly good, though every few weeks someone walks in just to say “we don’t like Chinese cars here.” The XPENG 小鹏 saleswoman unprompted told me, “we are Chinese but a private company not owned by the government like BYD. Also, Volkswagen owns 5 percent and Norwegian oil fund owns some of us too.”

Norway up until the 70s was one of the biggest Israel supporters. Their two Labor parties both ran their countries for decades, and living on a kibbutz was a thing Norwegian lefties did. But Norwegian soldiers saw some shit as peacekeepers in Lebanon in the 80s, everyone got really invested in the Oslo Peace Process and felt burned by the Israelis in the subsequent decades. “We were a colonized country too, you know. First the Danes then the Swedes…”

Thanks presumably to oil wealth guilt, Norway might be the country most into ESG. The government in early June officially recognized Palestine but Parliament decisively voted down a push to make the Oil Fund divest from all companies with ties to Israel. They did recently sell $70m of Caterpillar stock…? The ratio of pride to Palestinian flags was maybe 5:1.

Haaretz recently ran a feature on rising antisemitism in Norway which convinced me I didn’t want to move there. For an illustrative excerpt on what happened when a group of Jews tried to join an International Women’s Day protest to raise awareness of Hamas. They got approval to join, and on parade day this happened:

The hostile reaction manifested almost immediately. Initially, the group was refused entry to the event and had to prove that they had the organizers' authorization to participate. "One of the organizers went on shouting and cursing, and then took one of our signs and threw it on the ground," Nilsen recalls. "After the police made sure he couldn't get close to us, more and more organizers told us that our message conflicted with the messages of the event.

"They looked at us with hatred and disgust and started to shout that we were Zionists and fascists. Then the crowd joined in with slogans and rhythmic chanting that we were already used to, like 'Murderers,' 'No to Zionists in our streets' and 'From the river to the sea, Palestine shall be free.'"

They avoided getting into a direct confrontation, Nilsen relates, "and we instructed our group not to scatter and not to respond. But when the atmosphere heated up, some of the other demonstrators – Norwegian men and women of my age – approached the members of the group very closely and whispered into their ear things like 'child murderer' and skadedyr' ['parasites' in Norwegian].

"I've had anti-Israeli calls shouted at me in the past," Nilsen continues. "But this time it was very different. The hatred came from people I thought we shared basic values with. The feeling was that we were being canceled as human beings. We weren't women and men – we were the embodiment of evil."

Parks midday on a Monday were packed. There’s an abundance of minigolf. Workdays in winter start very early so people can get some sunlight outside the office in the afternoon.

Norwegian youth wear the most boring clothes I’ve ever seen in a city. The one signature that stood out were these rainbow-tinted athletic glasses. A few years ago, a comedian made a hit song about the top brand which features a yodel.

Norway had the highest ratio of American to local music I’ve ever seen in a Spotify Top 50. The vast majority of what modern Norwegian hip hop, pop, and indie I came across was flat.

At first I thought there was some adverse selection going on where the best artists try to make it in English, but an arts and culture newspaper editor told me that actually that the cool thing nowadays is to sing in the local language. The Swedes have figured this out…what gives, Norway?

The closest to okay top Norwegian act I came across was Karpe, a rap duo of a Hindu and Muslim second generation immigrants. Electronic music was much stronger. I quite liked this mix and was told they do jazz well too.

Vikings

After flipping through a handful of intro to Vikings books, Children of Ash and Elm stood out for its writing and breadth. It an excellent portrait of the Vikings which brought the terror as well as the humanity to the culture. For instance, I quite liked this discursion into Viking bread.

Some more good writing:

And this:

This list of sea-king names was amazing:

The sagas were also surprisingly accessible and make for great audio books. The Poetic Edda would be my bet for an entry point.

But let’s not forget, the Vikings were actually horrible. This account of a king’s burial by a travelling Arab diplomat in the 900s is one of the most terrifying primary sources I’ve ever come across.

Sexual violence trigger warning.

Modern Norwegian History

Aside from non-fiction on Vikings and Hitler in Norway, the only book-length title I came across telling the history of modern Norway was The Norwegian Exception: Norway’s Liberal Democracy since 1814. I found its thesis hysterical: it’s been incredibly lucky. Its neighbors Sweden, Denmark, and Russia never invaded. The touchiest moment came in 1905 with Sweden…I’m sorry but I can’t help at laughing at the nationalist chest-puffing in Scandanavia.

But ultimately, good call by Norway conceding on the great reindeer dispute of 1905.

Other lucky turns: Norway’s time under Nazi Germany was the easiest ride of any country that got conquered in WWII (good book the occupation here). The country should get some credit for not having a civil war, fumbling the bag when it comes to exploiting the boom in global trade in the late 19th century, successfully leveraging water power to industrialize in the early 20th, and of course making the most out of its oil riches.

Final fun fact: Norway of course had an influential Maoist party! A paper if you’re curious.

Maoist skiing, who’d have thought!

But by the 70s, they somehow they became the party of no fun.

WWII

Aside from Vikings, you also have a number of incredibly detailed but not particularly engaging books on Hitler’s invasion. Here’s the case for caring:

The most interesting bits I found were on the strategic level, where before Germany made its move the UK was also dancing around a pre-emptive invasion primarily to secure iron ore. At one point, France pitched the UK to come into the Winter War on the side of the Finns, doing the enormously idiotic move of putting them directly in conflict with the USSR.

Can’t pass on another opportunity to clown on Chamberlain.

Photos

Oslo is big on public art and every other statue was naked. City Hall had some particularly suggestive murals.

I loved this 1919 woodcut.

Soy sauce is marketed at something for pasta sauce. I tried it and appreciated the umami boost—though I think fish sauce works better.

Commerce released its much-anticipated chip export-control updates earlier this month. To discuss, I was joined by Dylan Patel of SemiAnalysis and Greg Allen from CSIS. We were not impressed.

Below is part two of our discussion. We get into:

• Dylan’s and Greg’s pitches to incoming Commerce Secretary Howard Lutnick.

• Why America’s “scalpel approach” to chip controls backfired and what a “shotgun approach” could look like.

• How China’s focus on trailing-edge chips and power semiconductors creates vulnerabilities that current controls don’t address.

• How Trump’s team could use novel tariff strategies to turn China’s massive chip buildout into “ghost fabs”.

Click this link to listen to the show on your favorite podcast app.

And a job post! ChinaTalk is hiring for a dedicated China AI lab analyst. Chinese fluency and a technical background are required. Apply here!

Okay, Trump — Your Turn

Jordan Schneider: We have new regulations with significant gaps [discussed in depth in part 1 of our conversation], and a new president arriving in four weeks. What should Trump and his team do on chips? And what do you think they will do?

Greg Allen: Marco Rubio, our presumptive Secretary of State, has consistently criticized the Biden administration’s export-control packages as too lenient, citing numerous loopholes and oversights. While the Commerce Department leads on dual-use technology export controls, the State Department participates in the interagency decision process.

Rubio’s passion for addressing Chinese technology threats could make him an influential voice in this arena. Similarly, the incoming national security advisor, Mike Waltz, prioritizes Chinese technology competition. The Biden administration established this new approach to the Foreign Direct Product Rule — a tool now available to the US government. The Trump administration might wield this tool quite differently.

Jordan Schneider: Let’s revisit our strategic premises, particularly regarding allies and partners. Trump’s negotiation style with allies differs markedly. The irony would be if Trump confronts allies over minor issues like Mexican auto imports or Canadian timber while overlooking semiconductor manufacturing equipment — the EU’s primary export to China and Japan’s second-largest.

If Trump takes an aggressive, unilateral approach, allies might accept semiconductor restrictions while focusing on larger concerns like NATO’s stability or US troops in Okinawa. The impact on industry follows similar logic — these restrictions won’t collapse American, Dutch, or Japanese economies.

The crucial question becomes, “Do we abandon end-use controls for a nationwide approach?”

Should we implement straightforward restrictions on sub-300mm semiconductor equipment exports to China, eliminate servicing allowances, and replace 200-page rulebooks with five-page directives?

Greg Allen: The Trump administration initiated our modern semiconductor export control approach — from chip-level restrictions with ZTE to the Foreign Direct Product Rule affecting Huawei and TSMC, and equipment export controls involving Dutch EUV machine licensing. The question is whether they’ll follow this strategy to its logical conclusion.

No apology to China would dissuade their pursuit of domestic self-sufficiency and indigenization. They’re fully committed to this strategy regardless of any potential trade deals with Trump. The distinction lies between appearing tough and implementing effective policies.

Regarding countrywide export controls: they’ve proven unambiguously most effective among our policy iterations. The current 200-plus pages of regulations create enormous complexity for future negotiations. Simplicity benefits both companies and allies in understanding these policies. While I appreciate the nuanced logic behind these complex distinctions, countrywide controls offer valuable simplicity.

Dylan Patel: The real question is exactly what Greg said: “How tough will they be on China?” While they initiated these measures, they ultimately relented with ZTE. They didn’t follow through completely, allowing ZTE to survive and continue growing. The core question remains.

Banning 300-millimeter equipment seems like an extreme measure. Perhaps they’re just accelerating the tightening of restrictions. Most people presume they’ll take a tougher stance — they’ll certainly appear tougher, but the extent remains uncertain. If they were to ban all 300-millimeter equipment, it would completely halt the Chinese equipment industry, though such a drastic step seems unlikely.

Jordan Schneider: Different question. If you had half an hour with Howard Lutnick to pitch the right export control policy, what would your key points be?

Dylan Patel: First, don’t listen to tool company lobbyists — they’re motivated to maintain loopholes that allow them to continue selling for another year, worth over $5 billion to them.

Regarding tools being multipurpose: should we maintain the 14-nanometer logic threshold? Even above that, China has achieved significant indigenization in their military equipment, which the US lacks. Is that the right boundary? Moving it to 28 nanometers would eliminate many dual-purpose equipment issues. At 14 nanometers, some 20-nanometer equipment might work for 7-nanometer applications.

We must consider China’s breakthrough innovation capabilities. They’re developing interesting technologies beyond EUV. We could restrict these areas — for example, Zeiss lenses to China face minimal restrictions. Looking up the supply chain is crucial because even if China achieves breakthrough innovation in tools, they’d need to replicate entire companies like Zeiss and others across the industry.

Understanding the primary goal is essential. If it’s slowing China’s AI chip development to limit their economic and military projection power over the next decade, there’s much more to address beyond AI chips, though they remain the primary focus. The strategy should be tactful — ban subcomponents first, then tools at a lesser level, followed by chips at an even lesser level. This framework still needs refinement.

South Korea presents a crucial consideration, particularly regarding Samsung and SK hynix’s large Chinese facilities. We need their alliance while preventing IP transfer from their Chinese operations. Perhaps CHIPS Act 2.0 could provide significant support to Samsung and SK hynix in the US.

The diplomatic approach with South Korea requires more finesse than with the Netherlands. Dutch companies only make tools and rely heavily on US supply chains — while Korean manufacturers like CMS rank seventh globally in tool production. Their fabs lead in certain areas with significant Chinese capacity. We can’t simply impose blanket bans without considering the implications for Samsung.

Closing loopholes seems straightforward, but the strategic objectives and precise targets require careful consideration.

The current strategy resembles a jigsaw puzzle. Give a hundred-piece puzzle to an eight-year-old, and they’ll complete it. Remove one piece — they’ll still figure it out. Take away ten pieces — it becomes much harder. Remove fifty pieces — they can’t finish it. Remove all the edges — they’re completely stuck.

Right now, the strategy involves removing just a few puzzle pieces.

Greg Allen: And they’re doing it one at a time, giving China time to stockpile.

Jordan Schneider: Not to mention announcing it in Reuters six months before removing the puzzle piece — saying nothing of listening to Gina Raimondo’s phone calls. It’s all publicly available outside of paywalls.

Dylan Patel: This strategy is clearly failing. They remove a few puzzle pieces, but China responds by stockpiling equipment, accumulating HBM, buying subsystems, and dedicating significant engineering resources to solve each banned component.

Take high-aspect ratio etchers for 3D NAND: because the ban was telegraphed, they purchased substantial Lam Research equipment beforehand, including years of spare parts. They positioned new tools beside foreign equipment, analyzed the data from both, and now YMTC is close to developing domestic high aspect ratio etchers. The quality might not match Lam Research, but it’s progress. This happened because the 2022 restrictions for 3D NAND only removed one puzzle piece.

The key insight is that you need a shotgun approach, not a scalpel. If you precisely target one linchpin technology, they’ll solve it with their substantial engineering talent, capital, and industrial base. A shotgun approach increases both cost and time requirements — if you force them to simultaneously solve ten different technologies, splitting their engineering resources, they’ll advance more slowly and fall further behind in AI development.

Jordan Schneider: The irony here is fascinating:

• If you sell them the complete puzzle, they won’t learn to manufacture pieces — there’s no incentive.

• With a shotgun approach, they might decide it’s too challenging and redirect resources to other sectors like EV batteries.

• However, America’s current approach of leaving enough scaffolding actually creates the perfect industrial-policy scenario. Companies typically avoid researching existing technologies when ROI is low, but the Swiss-cheese nature of restrictions over the past two years keeps them in the game, pushing indigenization further than if the US had either implemented dramatic FDPR in 2022 or continued selling everything.

Greg Allen: Say you and your spouse are choosing where to build your house: you’ve selected the neighborhood, but are still debating which side of the street. The dumbest thing you could do is compromise and build your house in the middle of the street. You can make logically consistent arguments for selling almost everything or almost nothing to China. The illogical approach is telegraphing your intention to restrict China while leaving numerous loopholes that undermine the strategy’s effectiveness.

These policies emerge from political compromises, which can be problematic. However, the “sell everything” scenario wouldn’t have ended well either. We sold everything regarding solar manufacturing equipment, and China now dominates that industry. The same happened with electric vehicles. Chinese policy documents and industry patterns don’t support the hypothesis that unrestricted semiconductor sales would have yielded positive outcomes. At this point, we’re committed to the export control strategy — we need to implement it effectively.

Jordan Schneider: Let’s create an alternate history. Up until October 2022, we sold everything to China. Huawei controlled one-third of global market share while Apple struggled in China. Meanwhile, SMIC was approaching competition levels with Intel, TSMC, and Samsung...

Dylan Patel: In this alternate history, Huawei had unlimited purchasing power until the Trump administration implemented restrictions. Huawei became TSMC’s largest customer and dominated Apple in the Chinese phone market. They emerged as the world’s largest phone manufacturer — not quite as profitable as Apple, but they were getting there. They dominated global telecom equipment markets, only facing resistance in regions where we explicitly banned their equipment due to security concerns, despite their technical superiority.

When companies have unrestricted purchasing power, they overtake industries. Take SMIC, for instance. With unlimited access to resources, they achieved 7-nanometer technology independently. Even though they could access TSMC’s 7-nanometer technology since 2018, SMIC still developed their own capabilities and found a market for it.

Their capacity today would be significantly larger without restrictions. Consider NAURA before the October 7, 2022, restrictions. Why did they maintain hundreds of millions in revenue when Applied Materials and Lam Research could sell freely to China? Because China’s industrial policy focuses on replication and building domestic supply chains. In an unrestricted scenario, it’s like giving them the complete puzzle, which they then recreate independently. Now, we’re only withholding one piece, yet they’re still determined to complete the puzzle themselves.

‘We Must Decide’

Jordan Schneider: Final thoughts — what’s the “America First” argument for investing in domestic semiconductor industry while restricting China’s semiconductor development?

Dylan Patel: Making American chips great again requires more than just the current CHIPS Act. $50 billion barely scratches the surface — Intel alone spends $20 billion annually on R&D, plus additional capital expenditure. The current allocation represents less than one year of spending, with Intel receiving under $10 billion spread across multiple years.

The renewable energy subsidies in the Inflation Reduction Act represents about the same cost as securing even 5% domestic market share in chips. The semiconductor industry, where we currently hold significant market share, requires proportionally less investment. Industrial policy must be implemented before we lose our competitive edge.

To maintain at least 20% market share in memory, advanced logic, and other sectors, we need to act now. The cost increases dramatically if we wait five years. Tariffs alone won’t relocate chip manufacturing since the focus should be on end systems and servers. Manufacturing servers should happen in places like Vietnam and Mexico.

We need industrial policy that encourages significant capacity development. Should TSMC allocate 15-20% of their leading-edge capacity here, or should we aim for 30-40%? This goal is achievable with modest additional investment relative to government spending. Companies like Samsung, SK hynix, STMicroelectronics, and Infineon should be manufacturing in the US.

The CHIPS Act focuses primarily on leading-edge technology. We need expanded funding for both leading-edge and trailing-edge technologies to counter China’s dominance in the latter. Between 2022 and 2025, China’s IGBT [insulated-gate bipolar transistor] capacity growth exceeds the world’s existing capacity. While their yields may initially be lower, they’re positioning to control 50% of global capacity in power semiconductors. This creates significant supply chain security concerns that require strategic industrial policy rather than blanket restrictions.

Greg Allen: My question regarding everything you said is that Donald Trump considers himself “tariff man” and loves tariffs. The current tariffs on Chinese semiconductors apply only at the chip level when shipped as standalone items. While it would be complex to apply tariffs to the component value of chips in finished goods, it’s not impossible.

I’ve been wondering if the Trump administration might say that they don’t want what Trump has called “corporate welfare” through the CHIPS Act. Instead of industrial policy through subsidies, they may prefer industrial policy through tariffs. The current tariffs on Chinese semiconductors aren’t effective, but a different approach to tariffs might work. Though I’m not certain this is what they’ll pursue, it seems consistent with their messaging.

Dylan Patel: The question is, “Are you going to tariff electronic systems manufactured in China? Are you going to tariff 90% of iPhones?”

Greg Allen: We’re entirely speculating here, but I think they would say if an iPhone contains Chinese chips, the tariff applies based on the value of those Chinese chips. We’re always tariffing chips, whether they arrive in a box labeled “chips” or in telecommunications equipment.

Dylan Patel: Presumably it would be tiered — Chinese chips at a 500% tariff and Taiwan chips at a 10% tariff.

Greg Allen: Exactly. All this Chinese legacy buildout we’ve discussed — some of which might be advanced node production disguised as legacy node — could become the industrial equivalent of those ghost apartment buildings in China. If there’s no end market for these Chinese semiconductors, their industrial policy would be a disaster. They would have built a bridge of subsidies to nowhere. While I haven’t heard from Howard Lutnick or others in the Trump administration that this is their planned policy, I could see this approach being attractive.

Dylan Patel: But if you want to prevent China from gaining global market share in trailing chips outside of China, the primary task is moving electronic manufacturing out of China. The US market share for most products — excluding high-end AI servers — is only about 30% to 40%. For AI servers, it’s around 70%. We can dictate policy on AI servers, assuming we resolve the data center shortage, which requires significant regulatory changes.

Greg Allen: You’d have to persuade Europe and Japan to participate.

Dylan Patel: Exactly. Otherwise, why wouldn’t Xiaomi phones — which hold 20% global market share — and other Chinese phone makers like OPPO simply use Chinese RF chips, power management ICs, and antennas? They clearly will, unless we can move both manufacturing and vendors out of China.

Consumer goods, especially phones, are dominated by China. For laptops, you’d need to convince Dell and HP — through their ODMs [original design manufactures] like Compal — to completely relocate to southeast Asia, India, or elsewhere. A tariff on chip value made in China doesn’t solve this issue.

Since we’re speculating about the Trump administration’s approach, why not be more heavy-handed? We could tariff everything shipped from China, with lesser tariffs on Taiwan and southeast Asia. This would make moving out of China a massive cost saver — perhaps not enough to justify Mexico, but definitely southeast Asia.

Greg Allen: We’re at a point in the story where the Biden administration has assessed the policy toolbox created by the first Trump administration. Now we’ll see how a second Trump administration utilizes the toolbox Biden’s team has created. While some people in DC — certainly not me — may be tired of the semiconductor and AI great power competition narrative, I don’t think it’s going anywhere. This will remain a significant part of geopolitical competition and a key focus for the Trump administration.

Jordan Schneider: I got one more riff.

The intellectual- and execution-level challenges the Biden administration encountered with export controls exemplify broader Democratic Party challenges. There’s a tendency to believe they can devise the perfect algorithm that balances all competing interests. They think with solving enough integrals, extensive legal review, and track changes on docs, they’ll reach the optimal solution.

This pattern emerged with the Inflation Reduction Act’s lengthy development, the CHIPS Act’s extended negotiations, the periodic reassessment of Ukraine arms distribution, and these export controls. The problem is that, if you can’t make tough strategic decisions upfront and execute them — accepting that not everyone will be happy — you end up in limbo. You achieve worse results by trying to moderately satisfy five variables instead of maximizing the two most critical ones.

Greg Allen: Another way to put it: faster and good enough is almost always better than slower and theoretically perfect.

Jordan Schneider: As a new American dad returning from paternity leave, I’ve been exercising by birthright by reading Civil War history. There’s an excellent quote from Colonel James Rusling’s memoir about how Grant made decisions.

The irony is that October 2022 really felt like a decision point. Jake Sullivan gave a dramatic speech stating we needed to stay as far ahead of China as possible in critical strategic emerging technologies. A month later, ChatGPT emerged, clearly demonstrating AI as the critical emerging strategic technology. They were onto something, but now we’re left with this muddle.

Part 1 of our conversation:

Mood music:

The global race to build humanoid robots is heating up, and Beijing aims to dominate the industry by 2027. Our deep dive today explores:

• Why it’s worth it to build humanoid robots instead of the strictly industrial robots we covered in part 1 of our robot series

• How leading Chinese players stack up against Tesla and Boston Dynamics and where China is still reliant on western technology

• The challenges of data acquisition for LLMs vs for humanoid robots

• Why the Chinese auto industry is key to humanoid robot success

Human toddlers, on average, take 17 tumbles and toddle 2,368 steps each and every hour as they learn how to walk. By the age of two, children make walking look easy. But make no mistake — after a century of research, neuroscientists still don’t fully understand how the human brain learns to execute such a wide array of complex physical activities.

Natural selection has refined the human form over billions of years. And yet, companies around the world are now betting that they can artificially imitate the human body on a much shorter timescale, to create AI-driven general-purpose bi-manual, bipedal robots.

The question is, will this marriage of AI and robotics (also known as ‘embodied intelligence’ 具身智能) produce viable offspring?

The allure of humanoid robots

Generative AI and humanoid robotics seem like a perfect match. If combined successfully, they could replicate optimal human performance on a massive scale.

By mimicking human form, humanoid robots can operate in working environments originally designed for people (e.g. mine shafts). By mimicking human behavior, humanoids can integrate more easily into human social and emotional contexts (e.g. waiting tables or modeling clothing).

In the face of pervasive labor shortages, Goldman Sachs stuck a finger in the wind and guessed that the global market for humanoid robots could be worth US$38 billion in a decade.1 With such a large potential payoff, western firms like Tesla, Boston Dynamics, Figure AI, and Apptronik are making huge investments in humanoid robot development. But at least one third of that global market value will come from imminent Chinese demand for humanoids — and the CCP wants to make sure those industrial androids are home grown.

In 2023, China’s Ministry of Industry and Information Technology proclaimed that China would aim to be the world’s top producer of cutting-edge humanoid robots by 2027. Models by Chinese firms like AGIBOT, Astribot, and Galbot threaten to outcompete Tesla’s Optimus bot, thanks in part to Chinese advantages in supply-chain integration and mass production.

Given China’s shrinking labor force, general-purpose bipedal robots have clear appeal. Of course, humanoids could revolutionize industries characterized by dirty, dangerous and demeaning work,2 such as agriculture, construction, manufacturing, mining, or transportation.

The perfect job for a humanoid. Source.

But humanoids could also be valuable in the service sector. As personal assistants, personalized tutors, and caregivers for the elderly and children, humanoids could automate rote daily monitoring tasks while offering companionship. Maybe one day they could even provide entertainment as street performers.

Finally, China’s existing prowess in industrial automation could serve as an additional motivator. With the power to directly access, operate, and repair existing automation and computer systems, humanoids could unlock a number of creative multiplier effects that we analog humans haven’t even imagined yet.

So, what’s needed for these sci-fi fantasies to become day-to-day reality?

The technology we lack

A multi-functional humanoid robot requires advancements in both hardware and software. Beijing’s Embodied Intelligent Robot Action Plan 具身智能机器人行动计划 breaks this down into three core technologies: robotic body components (the “limbs” 肢体), motion control and balance (the “cerebellum” 小脑), and AI (the “brain” 大脑). Designing every part comes with trade-offs — complexity, power systems, weight, and size each influence cost, durability, stability, and control.

Hardware for the “limbs” 肢体 needs to mimic the complex array of joint and muscle movements possible in a human body. In robotics, the concept of “degrees of freedom” (DOF) refers to the number of independently controllable joints on a robot. A basic robotic arm might have three DOFs (forward/back, left/right, up/down). In contrast, a functional humanoid robot might require a staggering 28 DOFs just for its limbs (3-DOF hip or shoulder, 3-DOF ankle or wrist, one-DOF knee or elbow). Robot hands are a major challenge — human hands have at least 27 DOFs, a difficult target for hand-sized hardware to achieve. Recently, Shanghai-based Fourier launched a model with 12-DOF hands; Tesla’s Optimus is meant to upgrade to 22-DOF hands by the end of 2024. A robot that can manipulate objects at the level of an experienced human worker on the factory floor remains elusive.

For safety, these humanoid bodies need to be stable, accurate, and reliable. The physical world tends to be less forgiving of mistakes than the digital world—one wrong move could cause a seventy-kilogram metallic mass to crush a nearby object or human, so no room for error. Achieving coordination, balance, and posture in the robotic “cerebellum” 小脑 requires complex autonomous control systems that integrate sensory inputs into motor outputs. And, with all that out of the way, these robot bodies are still not fit for commercial use unless they can run reliably without frequent maintenance.

Meanwhile, the AI-powered “brain” 大脑 needs to substitute for human thinking and behavior.

In contrast to internet AI (those that only operate online), embodied AI learns by interacting with a physical environment. Such AI-powered robots need to be able to continuously monitor, process, and quickly respond to massive quantities of sensory input in real-time. Can the robot pick any object from a messy pile, shift it to the correct orientation, identify it, and transport it to the right place, all without damaging it? These are the kinds of questions that robot “brain” developers are asking.

Moreover, one of the key targets for a general-purpose robot brain is emergent behavior — defined as a robot’s ability to perform actions not present in its training data, such as catching an unexpected falling object. Robots have yet to master the “commonsense knowledge” to handle everyday environmental variations that humans take for granted. Even something as simple as pouring tea into a mug has countless “edge cases” that would challenge a robot. What if the mug is upside down? What if the mug is already full? What if the mug accidentally falls? Composed of many actions in a sequence, such seemingly simple tasks have long time horizons with many opportunities for errors to compound.

Techniques like end-to-end neural networks can help companies to research, develop, and iterate their products more quickly.3 But creating humanoid robots fundamentally requires big science — that means big datasets, investment budgets, talent pools, and teams of collaborators. The time has not yet come for them to break into reality.

But if not now, when?

Where data might come from

As with many AI applications, many researchers argue that enormous training datasets are the key to develop a general-purpose robot. But obtaining this data is not easy.

There is no internet-equivalent that can spin up a data flywheel for AI+robotics. Comprehensive robotic datasets often require sensory, motion, environmental, interaction, social, and task-specific data. That requires a lot of time, money, and coordination. The diversity of robot shapes and sizes, along with the variety of environments in which they can be deployed, complicates data collection further.

With tools like NVIDIA’s Isaac Sim, Researchers can generate synthetic data and run virtual simulations to train and test their humanoid models. These methods are increasingly advanced and safer than real-world operations, but synthetic datasets still risk producing results that are incomplete, biased, inaccurate, or ungeneralizable. Ultimately, before deployment, a humanoid robot must be trained and tested in real environments.

But where?

Automotive industry, meet Optimus

The automotive industry — in China and elsewhere — is full of problems that humanoid robots could help solve.

Manufacturers are grappling with the global EV reckoning, a fiercely competitive export market, and supply chain uncertainty. Meanwhile, consumers' tastes have grown more complicated than ever, as demonstrated by the rising popularity of built-to-order models.

The dwindling automotive workforce isn’t enough to handle these challenges. In China, government data forecasts a 1.03 million shortage of talent in the new electric vehicle industry by 2025.

But most manufacturing tasks can be automated by non-general-purpose, non-pipedal industrial robots. So why use humanoids?

The answer lies in the fact that car manufacturers can provide data and training environments that robot designers desperately need.

Factories and warehouses are “behind-the scenes” use cases in which a general-purpose robot can train and prove value without high costs of failure.

Manufacturing facilities already have structure and safeguards, and are only occupied by people with specific safety and hazard training.

Vehicle manufacturing is an especially good fit for training and testing humanoids. Standardized, process-oriented tasks like handling, sorting, welding, assembly, and quality inspection are perfect activities to help robots accumulate training data and build task libraries. Auto manufacturing factories also provide the physical ingredients for a humanoid training gym — varied terrain and dynamic elements from which robotics can learn in a relatively safe and controlled space. Through these “factory internships,” humanoids can perform relatively simple tasks to collect data, learn and generalize, and show practical value for broader commercialization.

Now, Chinese car manufacturers can preorder humanoid prototypes from Shenzhen-based robot manufacturer UBTech — presumably at steep discounts. UBTech’s plan is simple: achieve general-purpose commercialization by first rolling out humanoids in the auto industry and then expanding horizontally into consumer electronics and other industries. UBTech has reportedly already received intention orders for over 500 units from a slew of Chinese automakers. The humanoid collaboration club now includes SOEs like Dongfeng Liuzhou Motor and FAW, the privately-owned Geely Automobile, publicly-listed EV makers Zeekr and Nio, and the multinational joint venture FAW-Volkswagen (which produces VW and Audi cars for the Chinese market).

Similar strategies are taking shape outside of China as well. Figure AI’s first commercial partnership involves deploying robots in BMW’s South Carolina facility. Apptronik is sending its 160-pound bipedal Apollo bot to Mercedes-Benz’s facilities in Hungary, where the company has faced a sustained labor shortage. Toyota is investing in in-house R&D for humanoid robots and partnering with Boston Dynamics. The automotive sector is the largest source of new robot installations in all of North America, with many partnerships going beyond training to include collaboration in the eventual production and use of humanoids.

According to an anonymous industry insider, once humanoids are viable for factory applications, consumer applications could follow within two to five years.

Given that a robust manufacturing sector is critical for national defense, the auto industry’s adoption of humanoid robots could have far-reaching geopolitical implications.

Moreover, because of the unique difficulties associated with high-quality training data for humanoid robots, any entity with high-quality, proprietary, real-world data locks in an immense incumbent advantage.

China’s Strengths and Weaknesses

While data is limited, it appears Chinese humanoid models are behind the global cutting edge in a few areas.

A report from the US-China Economic and Security Commission finds that Chinese firms are on par with the US regarding robot weight, height, and speed, but lagging on key sensor technologies.

A recent Goldman Sachs analysis reveals that while both global and Chinese entities are proficient in AI “navigation,” technology is still lacking in “manipulation” and “interaction” abilities, with China slightly behind international competitors in these areas.

For a few specific hardware components — such as planetary roller screws and sensors —- China’s domestic companies seem to encounter bottlenecks not faced by their global counterparts. Chinese humanoid companies also rely on US-based NVIDIA for processing units and software. Nevertheless, some hardware suppliers like Shanghai KGG, humanoid manufacturers like Kepler Robotics, and AI companies like Huawei have made attempts to help the industry move towards localization.

However, when it comes to the inputs for humanoid robots, China is competitive thanks to its low-cost and manufacturing advantages. By taking a “fast-follower, rapid scaling” strategy, Chinese companies may become global leaders in humanoid manufacturing, even while relying on foreign innovations.

In China’s fragmented landscape of over 3,400 robotic startups, there are a few players who might become leaders in innovation as well. Two firms worth highlighting:

• Unitree Robotics: producing both quadrupeds and humanoids, this company has been responsible for flashy displays at the Super Bowl and the Winter Olympics. Its H1 humanoid demonstrates dynamic motion capabilities, including a record speed of 7.38 miles per hour. The robot will be rolled out at a price around USD $90,000, comparable to models by Tesla and Boston Robotics.

• Fourier Intelligence: specializing in medical and rehabilitation robots, this firm started its GRx series of general-purpose bipedal bots in 2023. GR-2, the latest edition, offers 53 degrees of freedom, longer battery life, and a streamlined design. Not yet commercialized, the G-2 is compatible with open-source software like MuJoCo and NVIDIA’s Isaac Lab for further robotic development.

Bolstered by government support, more advancements in Chinese robotics are likely forthcoming. Consider the timeline of Chinese electric vehicles: after prioritizing EVs in national economic policy throughout the 2010s, China is now recognized as a global leader in 2024. If Beijing follows through on its recent commitment to humanoid robotics, it’s not unreasonable to imagine significant strides in the next decade.

Zooming Out

Humanoid robots are a highly visible way for China to demonstrate its progress in robotics relative to the rest of the world. However, it’s important to remember that improvements in embodied intelligence — and the enhanced supply chains that follow — will come with knock-on effects that impact the rest of the economy. For example, improvements in humanoid technology could spill over to unlock new alternative robotic forms. After all, the human body does have its flaws.

Regardless of form, AI-driven robots raise thorny safety and ethical questions. A robot in the real world can collect all sorts of data — biometrics, building layouts, social behavioral data, continuous streams of audio and video, and more. Few regulations currently exist to safeguard transparency and personal privacy in the face of this increasingly robotic future. The IEEE’s study group to develop a roadmap for standards has only just started, and is set to release findings next year.

In the scenario that China dominates the humanoid robot market, some US politicians worry that the presence of Chinese-made robots on US soil could threaten national security (much like the FBI’s concerns about drones made by DJI).

There are concerns about unregulated humanoids in China as well. At present, no official safety standards exist for humanoid design. A group of Shanghai industry leaders published China’s first-ever governance guidelines for humanoid robots in July 2024, in which they floated a number of proposals including risk controls, emergency response systems, consensus-based regulation, ethical use training, and global collaboration guidelines for humanoids.

With industry leaders so eager to make their Asimovian fantasies a reality, ethical concerns are likely to arise within the next decade. The US and China have an opportunity to shape global governance frameworks together.

Admittedly, this will be difficult given geopolitical tensions. But without cross-border collaboration, firms can lobby against ethical regulations on the basis that international competitors won’t be bound by the same standards.

Behind fantasies of robot bartenders, technology is steadily advancing as hardware and software meet biology, neuroscience, and psychology. Our society is not prepared.

Still curious about humanoid robots? ChinaTalk has you covered. Write your questions in the comment section below for a chance to get insight from an anonymous industry expert coming soon to ChinaTalk.

3

Intuitively, end-to-end learning refers to the process of “training a single model to perform a task from raw input to final output, without any intermediate steps or feature engineering.” Tesla has implemented end-to-end neural networks in the development of their full self-driving features.

$10K GRANTS FOR PARADIGM-BREAKING DEFENSE ANALYSIS

Last month, I published a piece on how no organization today captures 1950s RAND energy. To answer my lament, a shadowy cabal calling themselves The Defense Analyses and Research Corporation have decided that it’s time to build. DARC’s manifesto:

Since we launched, the team at @DefenseAnalyses has been hearing more and more from current and former defense thinktankers who are straightjacketed by the stifling bureaucracy and deep risk aversion endemic among @RANDCorporation, @CSIS, @CFR_org, @BrookingsInst and elsewhere. This is an unforced error of gigantic proportions. In this critical time, the United States must ensure that the dynamism of its strategic thinking keeps up with the pace of global change.

We must foster a new generation of defense intellectuals that follow in the best traditions of Andy Marshall, Herman Kahn, and Edward Luttwak. Instead, a sclerotic establishment continues to pile on its limp everything bagel statecraft in the pages of rags like @ForeignAffairs: saying nothing, proposing nothing, committing to nothing.

DARC seeks to create a coalition of those unwilling to wait for the retirement party to bring about change. We believe there would be much progress in defense thinking if analysts simply did not fear the career impact of saying what needed to be said.

To that end, DARC will be publishing an ongoing series of working papers as part of its new Senior Fellows program. These papers will be published pseudonymously, allowing for a candid expression of real views. We are seeking work on the following topics:

1. Defense Strategy: What are the sacred cows of the defense strategy and foreign policy world when it comes to the war and conflict? Why are they wrong?

2. Procurement and Supply Chain: What must be done to revitalize armaments innovation and production in the United States? What are authorities that could be used to accelerate progress rapidly?

3. Future of Conflict: Where is war and conflict going? How does conflict in other domains such as politics, culture, and gaming inform our forecast?

4. Thinktanks: What has gone wrong with the defense thinktank ecosystem? What can be done to make it better?

To support this work, Senior Fellows will receive between $5,000 and $10,000, depending on the complexity and depth of the work.

No, this is not a joke. DM them to apply.

再见爱人4—divorce reality tv road trip

The biggest show right now in China (and by big I mean national phenomenon blocking out the sun on weibo and wechat) is a reality show where three celebrity couples all married for at least ten years and on the verge of divorces take an 18-day road trip together. It is some of the most gripping content I've ever seen.

I’ve assembled a starter pack of clips on YouTube below to get you all hooked. There are English subs which are subpar but enough to give nonspeakers the gist. We’ll be recording a special episode to discuss with Emily of the excellent Substack next week.

For some biographical context because you'll be jumping around…From left to right in the image:

couple 1:

Maimai, housewife with no hobbies who doesn’t care about music. Li Xingliang, singer who's moderately but not super successful. They have two kids.

They bicker alot in the first few eps where she wants to be comforted emotionally and he is super logical and not empathetic, then he has his big revelation: 5 min here then the conversation continues over into next ep. Next, the husband breaks down in car and a very helpful friend helps them see things more clearly. That evening they have a conversation in bed where for the first time in their 20-year relationship about how their parents raised them!

couple 2: Jessica Alba and an even more awful Tony Robbins

Huang Shengyi, the most famous person on the show, an actress whose biggest role was 20 years ago in the classic Kung Fu Hustle. ChatGPT says her American celebrity analogue is Jessica Alba. I’d suggest Hillary Duff. Yangzi, her husband (who started out as her manager...) is a former actor now a dilettante who does antiques and livestreaming and random things. They have two kids, live mostly separately, but she really wants him to still be a part of their kids' lives and he comes in thinking there's nothing wrong with their relationship.

Scene-setting argument featuring Yangzi mansplaining why he stays up till 3am every night with his friends and doesn't on ski vacations with his kids because he doesn't want to support 'western' as opposed to Chinese hobbies (the other couples make fun of him for 'mansplaining' and he doesn't know the word and thinks its a compliment!)

Next up, another legendary argument about him not supporting her professionally where you start to see her push back! Finally, there’s a friend lunch where he talks about his childhood and argues "my parents weren’t around and I turned out fine so why should I be around for my kids..." In the latest episode Yangzi was tolerable for a day and Huang Shengyi said she didn’t want to divorce him but the whole country is hoping she comes to her senses…

couple 3: Scott Disick and someone he doesn’t deserve

Ge Xi, housewife who's now more of an influencer, can support herself and sells things online. Her husband is Liu Shuang, who used to be a very big personality on weibo but is less famous now. They have no kids.

We're gunna skip them for now as they're a little less engaging, but basically he's depressed and not nice to her and she is flowering as a person and realizing she doesn't need him.

If you're intrigued by the clips, I'd next watch the first episode as it gives broader context to the relationships.

Immigration Reform…ish

This is a thing that happened.

Divyansh continues: “The J-1 Skills List required international students from certain countries to return home for 2 years after studying in the U.S. For Chinese STEM scholars, this meant being forced back to China to share cutting-edge knowledge with CCP-controlled industries and participate in its civil-military fusion strategy. The State Department deserves credit for recognizing and addressing this glaring vulnerability. However, the fact that it took nearly 16 years to fix this speaks volumes.”

It is absurd for the Bureau of Consular Affairs to take this long to emerge from their bureaucratic coma to be 2% less terrible to America’s most talented immigrants (not that they should be terrible to any immigrants, which of course they are to thousands on a daily basis…).

This was the most obvious fix Biden’s politicals clearly have been hammering on for years. The fact that they deep stated this change of all things until December 2024 underscores the rot in CA. Here’s to hoping against hope that Trump sticks to what he said about green cards and the Rubio team takes a hammer to CA to make sure it happens.

America spends $700m a year on “Consular Systems and Technology” In 2023 OIG found practically no progress on IT modernization, uncovering that in the 2010s the “CA’s original procurement package” was so bad that “the acquisition process had to be started over, delaying implementation of the CSM program by approximately 58 months.” That five-year clock started in 2012. As of Jan 2023, of the 90 things that IT effort was supposed to modernize, only one was half-fixed. The rot runs back decades.

State shells out another $300m a year on visa adjudication that could be done for $1m of o1 tokens, and a cool billion dollars on passport services. Dear DOGE: we can shave billions off the CA budget while cutting lines to process visas and passports by letting AI do first pass adjudication!

Outro music brought to you by the Defense Analyses and Research Corporation

The following is a guest column from , a longtime reporter formerly at TechCrunch.

Recently, I met a Chinese entrepreneur pitching his AI startup to TechCrunch. As the only writer focused on China at the site for five years, I’ve been the go-to for all China-related stories. I asked for a call, but the founder backed out last minute, worried that my byline would make his company appear “too Chinese.”

The company had already done much in pursuit of geographic ambiguity: it’s registered in Delaware and targets mostly the US market. But there’s a catch: it operates from both Shanghai and California, and the co-founders are Chinese citizens.

I was disappointed at missing out on an up-and-coming company, but more troubling was my realization that he was probably right. An article by me — the Chinese face for TechCrunch (despite my coverage of many global stories) — might spoil the startup’s effort to obscure its origins. In today’s geopolitical climate, any mention of China could unfairly prejudice a startup’s chances, even while I’m simply doing my job as a journalist to disclose all relevant facts.

Changing perception

Over the last two years, my China tech beat has drifted far away from its original form. 

During China’s tech boom of the previous decade, Western reporters in China wrote with curiosity, empathy, and a necessary dose of skepticism about the country’s historically opaque business environment. American venture capital was flooding into China when I started covering the sector in 2017. Chinese tech stocks listed in New York were investor darlings. Silicon Valley’s tech workers marveled at China’s mobile internet and the speed with which new tech developed.

It was an exciting and rewarding time for tech reporters, who enjoyed both an eager Western audience and open-minded local sources. Journalists, myself included, competed to break stories on future unicorns. And staff from these fast-growing firms were keen to see foreign media hold their employers accountable.

My analysis of business models like WeChat’s mini apps or Pinduoduo’s social commerce sometimes drew hundreds of thousands of views. Chinese firms proudly touted their “China edge” — affordable engineers, a hardworking culture, and a robust supply chain — as they pitched foreign investors.

Then in 2019, the mood shifted. Trust between Chinese entrepreneurs and foreign press waned amid escalating US-China tensions. Washington added Huawei and its affiliates to the Entity List, barring them from access to US technologies. Panic spread among Chinese firms reliant on the US for tech, funding, and market expansion. The “Chinese” label took on renewed negative connotations.

The view that Chinese tech was accompanied by national-security risks wasn’t new, but ongoing geopolitical tensions intensified it. As Western scrutiny grew, Chinese firms became wary of their association with home and sought to obscure their roots. This posed unprecedented challenges to my coverage.

Domestic crackdown

Western hostility against Chinese firms grew at the exact time that they most needed to accelerate their global expansion. Growth at home was suddenly and violently halted in late 2020 when the Beijing government initiated a wave of crackdowns on the tech industry. Ant Group — Jack Ma’s fintech empire — was the first to be caught in the crosshairs. Regulators pressed on by squeezing the ride-hailing giant Didi, the whole online education sector, and the video-game industry.

VC funding dried up, and tech giants decided to lay low. HongShan 红杉 (formerly Sequoia Capital China), funneled about $31 billion into 354 companies in 2021; in 2023, the investor deployed only $4.17 billion to 86 firms, per data from PitchBook. As a result, my daily routine went from uncovering key decisions at large tech companies and identifying promising underdogs to monitoring regulatory websites for policy shifts that could cripple another segment of the industry.

Regulations are crucial news, but over time they become repetitive and demoralizing. To do my job, I tried to explain the broader impact of changing regulations to readers, but I quickly became jaded with the staleness of the legalities. I had to find a new area with more action — and I saw the best opportunities outside China.

The globalizing years

Chinese tech firms have a history of global influence, from video games to e-commerce and hardware. Competition in the domestic market is cutthroat, but the country’s cost advantage, large talent pool, and supply-chain resources offer an edge over foreign companies.

In 2020, I started following globalizing Chinese founders more closely. Companies like Shein and TikTok were taking off internationally. Many other firms followed their path. Amid China’s tech crackdown, sluggish economic growth, and pandemic lockdowns, these firms were seeking opportunities overseas just like I was. I found myself a new, exciting beat.

But the thrill was short-lived. One evening in late 2020, a startup I had covered called me to request that I remove all mentions of China from my article. Instead, they wanted to be known as a “global” company. Granted, it had a small team of marketing and R&D staff in Silicon Valley, but the majority of its engineers were in China. It had the typical Variable Interest Entity (VIE) structure, with an offshore entity controlling its Chinese operations. It’s a classic setup used by tech startups to circumvent China’s restrictions on foreign investment.

The company argued that, since it had a team in Silicon Valley, it shouldn’t be called “Chinese.” I countered with examples like Alibaba and Tencent, which have long kept a presence in the US, yet disclosed the Chinese identity of their offshoots. I asked the startup to respect my editorial independence. I never heard from them again.

Reckoning

My self-righteousness soon fell apart following another such incident. One day in late 2021, I got a message from a founder asking me to remove “Chinese” from a few old stories I had written, fearing the description would scare off American customers. That was when I realized: I could harm young startups just by doing my job.

When I covered the company, it was based in China. Its story is fairly typical: after gaining experience in Silicon Valley, the Chinese founder returned home to start an AI business, hoping to ride China’s tech boom. His pursuit crashed right into the onset of the pandemic and China’s tech crackdown, so he pivoted to focus on the US instead. That strategic shift was met with another stumbling block — rising Western scrutiny over Chinese tech.

To assuage concerns from his clients, the company adopted “de-China” tactics: redomiciling overseas, relocating the management team abroad, selling shares held by Chinese investors, and even changing the founders’ nationality. Aside from the problem that such measures shouldn’t be necessary for an average startup, the question of when a company truly qualifies as non-Chinese is often a subjective judgment left to the journalist to make.

Many Chinese-founded startups I subsequently featured began asking me to downplay their Chinese ties. I was stuck between a rock and a hard place. I couldn’t unlearn the Chinese stories crucial to their success, nor abandon journalistic principles — but I could see the harm arising from discussing them in detail.

I felt increasingly conflicted. The stories I wanted to tell — about their upbringing, overseas education, investor network, engineering talent, and work ethic — were all tied to their Chinese background. But these became taboo topics that could unfairly subject them to scrutiny from foreign governments over alleged national-security threats.

Capturing the China edge was my job, but as Western suspicions grew, China’s strength had become a double-edged sword. A frustrated Chinese entrepreneur once confided in me, “We work for no government. We just want to build businesses.” But amid the Sino-American battle for technological supremacy, this apolitical mindset now seems unrealistic.

I still wanted to tell their stories, so I started a podcast to talk about Chinese founders, as well as founders from other underreported regions. The podcast focuses on how globalizing entrepreneurs traverse borders without labeling their nationality.

The fact is, many of these founders have lived in multiple countries, their operations are global, and their investors are from around the world. Traditional media, with little room or patience for their backgrounds, often fails to tell the full and fair stories.

ChinaTalk is hiring for a dedicated China AI lab analyst. Chinese fluency and a technical background are strongly preferred. Apply here!

We’ve got a new show up on the podcast feed with of the Interconnects Substack talking through the biggest AI stories of this year and next. Listen in on Apple Podcasts or Spotify.

Today we’re running a guest piece from Ray Wang, a Washington-based analyst.

On December 2, the Department of Commerce released new export control packages targeting Chinese access to high-bandwidth memory (HBM) with semiconductor manufacturing equipment, including tools essential for HBM manufacturing and packaging, along with the addition of over 140 Chinese chipmakers and chip toolmakers on the Entity List. The new control on HBM — an essential component for AI chips used to train complex AI models and support the AI data center, will constrain China’s AI development which is already hampered by earlier rounds of export controls, including those announced in October 2022, October 2023, and April 2024

.Why HBM Matters

The proliferation of large language models (LLMs) has prompted substantial demand for high-performance computing (HPC) and AI data center infrastructure. HBM, or High-Bandwidth Memory, a type of dynamic random-access memory (DRAM), has become a key component of AI chips — specifically Graphics Processing Units (GPUs) and application-specific integrated circuits (ASICs) that train AI models and power data centers.

Integrating HBM with GPUs or ASICs effectively addresses the so-called “memory wall” bottleneck — a performance constraint caused by the gap between processor speeds and memory access rates. By enabling rapid access to data with lower energy consumption, HBM improves the efficiency of data-intensive AI workloads. This is why most GPUs and ASICs need to incorporate HBM to optimize performance in AI training and inference tasks.

Even from a cost structure perspective, HBM is vital as well, as it accounts for 50% or more of the total cost of an AI chip. Nvidia H100 GPU for example, HBM accounts for 50% of the total cost, followed by 40% of advanced packaging and advanced manufacturing of logic chips, which in Nvidia’s case, are both done by the global foundry leader TSMC. The rest of the materials like printed circuit boards (PCBs) share the last 10% of the total cost.

The global demand for HBM has soared over the past two years, driven by increasing demand for GPUs and ASICs to support AI model training and data center buildout. Morgan Stanley’s December report forecasts the global demand for HBM in 2025 will double that of the 2024 levels. The HBM market size is previously projected to reach up to $33 billion by 2027 — an eightfold increase from $4 billion in 2023. Indeed, there are early signs that prove such a bullish outlook. For instance, HBM suppliers like SK Hynix and Micron have already sold out their HBM production until late 2025.

HBM’s unique function has made it an indispensable component for AI accelerators, as well as the broader AI chip supply chain. Today, almost all leading GPUs and ASICs, including those from Nvidia, AMD, Intel, Google, Amazon, Tesla, Microsoft, and Huawei — integrate HBM to enhance their chips’ performance (see Figure 1). Its essential role has elevated HBM’s strategic value, positioning it as a linchpin in the AI chip supply chain — one of the key reasons prompting the Biden administration’s decision on HBM restriction.

Asian Chipmakers Run the Game

According to Goldman Sachs, SK Hynix and Samsung Electronics dominate the market with more than 90% of the global HBM market (see Figure 2). Notably, SK Hynix and Micron are leading the race in the most advanced HBM, outpacing Samsung, which is struggling to qualify for Nvidia’s standard to supply the most advanced HBM.

SK Hynix, in particular, has emerged as the world’s leading HBM manufacturer, securing the bulk of orders from Nvidia’s advanced GPU — the top HBM buyer in the market. SK Hynix’s success in high-margin HBM has even led to its financial performance outperforming its long-time rival Samsung’s chip sector, which has struggled in both the foundry and HBM sectors (Figure 3).

In addition to memory makers, TSMC is another critical player in this equation. Apart from its renowned capability in advanced logic chip manufacturing — another key component for AI chips, TSMC also controls approximately 90% of the annual global capacity for Chip-on-Wafer-on-Substrate (CoWoS) — an advanced packaging technology required for integrating HBM and logic dies on a silicon interposer and then positions on top of the packaging substrate.

TSMC’s CoWoS advanced packaging capabilities are indispensable because nearly all of the integration of existing GPUs or ASICs with HBMs relies on its advanced packaging in Taiwan. This includes companies such as Nvidia, AMD, Marvell, Broadcom, and AWS. While TSMC’s leadership in advanced logic chip manufacturing already positions itself as one of the most important actors in the AI chip supply chain, its global dominance in CoWoS packaging further consolidates its central role. Interestingly, AI chip packaging is a bottleneck that has yet to be treated with enough attention.

Is China Falling Behind?

China has been lagging behind in both HBM and AI chip packaging — more because of underinvestment as opposed to export controls. HBM has only begun attracting significant attention within the memory industry in the past two years. Before that, it remained largely overlooked. Since 2013, SK Hynix has been developing HBM, initially in partnership with AMD for HBM1. Despite its industry-leading start, it did not translate to instant success for either SK Hynix or AMD due to minimal demand for HBM, generating negligible revenue for its overall DRAM sector. The same dilemma confronted other memory giants as well. Samsung, for example, even dissolved its HBM team in 2019, citing the segment’s limited market potential.

Similarly, while Chinese biggest DRAM makers like CXMT have narrowed the technology gap with competitors in traditional DRAM, they have skipped on HBM development — likely because of its perceived limited market potential. These years of insufficient investment in HBM have left the Chinese memory industry behind the market leader. The same logic applies to the domestic packaging for AI chips.

This gap becomes even clearer when closely examining the product roadmap of the four major DRAM manufacturers closely (see Figure 5). Samsung commenced mass production of HBM2 (2nd generation of HBM) in 2016, followed by SK Hynix in 2018. Chinese memory maker CXMT however, only recently began its massive production of HBM2, suggesting that China is roughly 6 to 8 years or three generations behind the front-running manufacturers. This gap is evident in earlier reports of Huawei and Baidu stockpiling Samsung’s HBM2E (3rd generation of HBM) and Chinese domestic firms still in the process of developing HBM2.

Based on the product roadmap, CXMT should be able to catch up with existing advanced HBM in roughly six to eight years. Yet, the existing and recent restrictions on semiconductor manufacturing equipment (SME), including manufacturing and packaging tools for HBM could push out that timeline. Many SMEs have overlapping functions (e.g. etching, lithography) for HBM and logic chip manufacturing, as well as advanced packaging processes. As a result, these restrictions, whether directly targeting logic chipmaking, HBM manufacturing, or packaging, are likely to hamper firm’s progress in HBM and the advanced packaging it requires. These challenges are further exacerbated by existing curbs on advanced lithography tools critical for cutting-edge HBM production.

It is also worth considering how the previous restrictions on advanced memory chips might affect China’s HBM development. Since HBM is essentially a memory technology that stacks several DRAM dies, limitations on advanced DRAM chips could continue to be a roadblock to China’s HBM advancement.

More importantly, taking the pace of development into account is pivotal. If Chinese memory makers continue to advance slower than market leaders in the coming years, the technological gap will be hard to narrow. In 2024, Chinese GPUs and ASICs are estimated to account for merely 1% of global HBM consumption. The rest is comprised of consumption from U.S. firms like Nvidia, Google, AMD, AWS, Intel, Microsoft, and Tesla — all reliant on the HBM from SK Hynix, Samsung, and Micron. The 1% share of HBM consumption by Chinese GPUs and ASIC, is mainly supplied by Samsung, instead of Chinese memory makers.

To that end, SK Hynix, Samsung, and Micron can generate much more revenue than Chinese memory makers from global GPUs/ASICs firms in coming years and reinvest it in R&D for the next generation of HBM or other areas essential for the company’s development. HBM’s strong market growth also makes it easier for these firms to compel their leadership and investors to allocate more resources to HBM development to maintain or even expand its edge — a trend already evident in companies like SK Hynix and Samsung. These business rationales, in contrast, will not necessarily apply to the Chinese memory firms given the limited demand for now.

Samsung is also a big loser for BIS’ new rule. 20% of its HBM revenue in 2024 was to China, and those sales are now banned. This impact should be soon shown in Samsung’s earnings in the coming quarters. On the other hand, the new rule should have a relatively small impact on SK Hynix and Micron, which both supply their HBM mostly to Nvidia and other non-Chinese firms.

Lastly, China's advanced packaging technologies and capacity remain limited. Compounding this challenge, AI chip packaging leader TSMC is unlikely to provide services to leading Chinese AI firms due to existing restrictions. With that in mind, even if China makes advancements in HBM technology in the coming years, its ability to close the gap with TSMC in advanced packaging remains uncertain under enhanced SME restrictions. Without advanced packaging capability, Chinese HBM will struggle to optimally incorporate it with GPUs or ASICs, which will ultimately affect their AI chips’ performance. Admittedly, emerging Chinese packagers like JCET and Tongfu Microelectronics have “CoWoS-like” packaging capability, it is yet unclear how successfully these firms can package the domestic HBM and GPU given the limited information.

That said, one should not underestimate the Chinese capability to close the gap with the market leader. Leading memory makers like YMTC and CXMT have proved their ability to rapidly narrow the gap in NAND Flash and DRAM with the ability to rapidly ramp up capacity to disrupt the market. Given the optimistic outlook for domestic HBM demand for GPUs and ASICs, increasing R&D investment, and continued government support, Chinese memory and packaging firms are poised to accelerate technological advancements. This is likely true at a time when both government and industry have heightened urgency to develop domestic HBM and AI chip supply chains amid increasing U.S. restrictions. Moreover, Chinese President Xi’s pursuit of “High-Quality Productive Forces” and “Self-Sufficiency” is likely to bring more government support for domestic HBM and AI chip supply chains.

These factors are likely to compel domestic GPU and ASIC providers to adopt homegrown HBM, stimulating the memory industry’s growth and spurring more public and private investment in this area. Chinese AI chip companies are also expected to enlarge their collaboration with domestic HBM maker and advanced packaging firms given their limited access to foreign products and the imperative to strengthen the local AI chip supply chain.

In fact, there are already some signs indicating these trends. Following Beijing's call earlier this year to prioritize domestic chip adoption, several Chinese industry groups issued statements on Monday, warning domestic firms that "U.S. chips are unreliable" in response to the BIS's new restrictions on Monday. Recent reports also suggested that Huawei, for example, alongside the government, is supporting local HBM and advanced packaging capabilities. Additionally, domestic foundries like XMC are reportedly ramping up efforts to produce HBM, signaling early efforts in building a Chinese ecosystem for HBM.

China’s AI development may not face immediate setbacks given that much of the advanced hardware supporting its AI industry is still mostly foreign made. For instance, most leading AI firms — such as Alibaba, Baidu, and Tencent still train their models with Nvidia GPUs procured before restrictions. Similarly, Huawei’s latest Ascend GPUs still use SK Hynix and Samsung’s HBM2 and HBM2E, also sourced before the restrictions took effect. China's semiconductor industry is likely to feel the impact in late 2025 or 2026, considering many Chinese firms have been preparing for this restriction by purchasing additional equipment over the past year. Nevertheless, China’s AI and semiconductor industry are ultimately on track to encounter a substantial “hardware bottleneck.” They will increasingly feel the impact of restrictions on high-end logic and memory chips (including HBM), as well as SMEs. Huawie’s chipmaking partner, SMIC, for example, is already struggling with producing logic chips below 7nm with commercially viable yield rates, despite earlier progress. The memory leader CXMT, is likely to face a similar struggle as the SME restriction disrupts its HBM product development and production. .

In short, the forthcoming restrictions on advanced HBM access will impede the performance of future Chinese AI chips, including those from major players like Huawei, and startups like Biren and Moore Thread. The broader SME export control will undermine China’s ability to develop and enhance its HBM and AI chips.

Despite export controls significantly impacting the industry, they cannot entirely block Chinese firms from advancing in critical technologies but instead force progress through costlier, slower, and more challenging paths.

HBM Architecture Series

Bjarke Ingels Group

Zaha Hadid

Frank Lloyd Wright

Frank Gehry

Before he became the CEO of world-beating AI lab Deepseek, Liang Wenfeng 梁文锋 was best known for founding High-Flyer (幻方), one of China’s top hedge funds.

High-Flyer is a quantitative fund that manages around $8 billion worth of assets. In Mandarin, the company’s name is “magic square,” a reference to the quirky mathematical object thought to have been first discovered in China.

How and why did High-Flyer start down the path of frontier LLM research? In this interview from May 2023, translated here by former Deepseek intern and first-year CS PhD student at Northwestern Zihan Wang, Deepseek’s CEO lays out a grand strategy for AGI development. It explores:

• Why High-Flyer decided to make early GPU purchases,

• Liang’s belief in LLMs and the linguistic nature of human intelligence,

• Methods to sustainably manage high research costs, including innovative uses of philanthropic budgets,

• How High-Flyer plans to democratize AI access,

• Organizational designs that facilitate innovation, from unconventional hiring to rejecting KPIs,

• How curiosity-driven startups can succeed in an era dominated by tech giants,

• Why High-Flyer pursues “hardcore innovation” instead of a business model based on imitation.

ChinaTalk is at NeurIPS this week! Respond to this email if you’d like to meet up.

WeChat, Archive link. Interview by An Yong Waves (暗涌Waves, a 36kr subbrand), published May 24, 2023. Text by Lily Yu 于丽丽. Edited by Liu Jing 刘旌. Translated by Zihan Wang 王子涵.

In the crowded battlefield of large models, High-Flyer stands out as perhaps the most unconventional player.

This is a game destined for a select few. Many startups, after large corporations enter the market, begin to adjust their direction or even consider retreating, but this quant fund continues to forge ahead alone.

In May 2023, High-Flyer launched an independent new organization called DeepSeek for its large-model venture, emphasizing its dedication to building truly human-level AI. Their goal isn’t just to replicate ChatGPT but to research and unravel more mysteries of Artificial General Intelligence (AGI).

Moreover, in this field, which is considered highly reliant on scarce talent, High-Flyer is striving to assemble a group of dedicated individuals, wielding what they believe to be their greatest weapon: the collective curiosity of a bunch of people.

In the quant investment field, High-Flyer is a top-tier fund that has reached a scale of hundreds of billions. However, its spotlight in this new wave of AI attention is quite dramatic.

As the shortage of high-performance GPU chips became a direct constraint on the development of generative AI in China, a report from Finance Eleven (财经十一人) revealed that fewer than five companies in the country owned over 10,000 GPUs. Apart from major tech giants, one of them was High-Flyer. Generally, 10,000 NVIDIA A100 chips are considered the computational power threshold for training large models.

In fact, High-Flyer, a company rarely scrutinized through the lens of AI, has long been a mysterious AI giant. In 2019, it launched an AI company and invested nearly 200 million RMB (28M USD) in developing its proprietary deep learning training platform, “Yinghuo 萤火 (Firefly) One,” equipped with 1,100 GPUs. Two years later, it invested 1 billion RMB (140M USD) in “Yinghuo Two,” which featured around 10,000 NVIDIA A100 GPUs.

This means that, in terms of computational resources alone, High-Flyer had secured its entry ticket to developing a ‘ChatGPT-like’ model earlier than many tech giants.

However, large-scale models are heavily dependent on computational power, algorithms, and data, making the initial investment as high as $50 million and each round of training costing tens of millions. Sustaining the race is nearly impossible for companies without multi-billion-dollar resources. Despite these challenges, High-Flyer remains optimistic. Founder Liang Wenfeng told us, “The key is that we want to do this, can do this, so we are one of the best-suited candidates.”

This inexplicable optimism stems first from High-Flyer’s unique growth path.

Quant-investing originated in the United States, which is why almost all of the founding teams behind China’s leading quant funds have, to some extent, experience working at U.S. or European hedge funds. High-Flyer, however, is an exception: it was founded entirely by a local team and has grown independently through its own exploration.

By 2021, just six years after its founding, High-Flyer had surpassed the 100 billion RMB milestone and was recognized as one of the “Four Kings of Quant-Investing".

As an outsider breaking into the field, High-Flyer has always been viewed as a disruptor. Multiple industry insiders told us that High-Flyer consistently uses innovative approaches in research, product development, and sales to carve out its place in the industry.

A leading Quant Fund founder remarked that High-Flyer “has never followed conventional paths” and do things “in their own way.” Even if it’s unorthodox or controversial, they would “boldly articulate their views and act accordingly".

High-Flyer attributes its development to “selecting high-potential while less-experienced individuals, supported by an innovation-driven structure and culture". They believe this approach could also enable startups to compete with tech giants in the large-model arena.

But perhaps the most critical factor is the vision of High-Flyer’s founder, Liang Wenfeng.

While pursuing an AI degree at Zhejiang University, Liang was convinced that “artificial intelligence would change the world” — a belief dismissed by many in 2008.

Upon graduation, instead of joining a tech giant as a programmer like his peers, he retreated to a cheap rental in Chengdu. There, he experienced multiple failures in applying AI to various fields before tackling one of the most complex areas: finance, leading to High-Flyer’s founding.

An interesting detail is that, in the early years, a similarly eccentric friend who was building “quirky” flying devices in an urban village in Shenzhen invited him to join his venture. That friend went on to create DJI, a company now valued at tens of billions of dollars.

Thus, beyond the discussions of funding, talent, and computational power, we also spoke with High-Flyer’s founder, Liang Wenfeng, about how to build an organization that fosters innovation and how long human “madness” can endure.

After more than a decade in entrepreneurship, this was the first public interview with this reclusive “tech nerd” founder.

Coincidentally, on April 11, when High-Flyer announced its entry into the large-model field, they quoted a remark by François Truffaut, a French New Wave director, who once advised young filmmakers: “Be desperately ambitious, and desperately sincere.”

On Research and Exploration

Waves: High-Flyer recently announced its entry into the large-model space. Why is a Quant Fund undertaking such an endeavor?

Liang Wenfeng: Our large-model project is unrelated to our quant and financial activities. We’ve established an independent company called DeepSeek, to focus on this.

Many in our High-Flyer team come from an AI background. Years ago, we experimented with various applications before entering the complex domain of finance. AGI may be one of the next most challenging frontiers, so for us, the question is not “why” but “how".

Waves: Are you training a general-purpose model, or focusing on vertical domains like finance?

Liang: We’re working on AGI — Artificial General Intelligence. Language models are likely a prerequisite for AGI and already exhibit some AGI characteristics. So we’ll start there and later expand into areas like computer vision.

Waves: Due to the entry of tech giants, many startup companies have abandoned the pursuit of solely developing general-purpose large models.

Liang: We won’t prematurely focus on applications. Our focus is solely on the large model itself.

Waves: Some say it’s too late for startups to enter this space after tech giants have reached a consensus.

Liang: Currently, neither tech giants nor startups have an unassailable lead. With OpenAI paving the way, everyone is working with published papers and open-source code. By next year, both groups will likely have their own large-language models.

Both major corporations and startups have their own opportunities. Existing vertical scenarios are not controlled by startups, making this phase less favorable for them. However, as these scenarios involve dispersed and fragmented niche demands, they are actually better suited to the flexibility of entrepreneurial organizations. In the long term, as the barriers to applying large models continue to lower, startups will have opportunities to enter the field at any time over the next 20 years.

Our goal is clear: to focus on research and exploration rather than vertical domains and applications.

Waves: Why do you define your goal as “to focus on research and exploration"?

Liang: It’s driven by curiosity. From a broader perspective, we want to validate certain hypotheses. For example, we hypothesize that the essence of human intelligence might be language, and human thought could essentially be a linguistic process. What you think of as “thinking” might actually be your brain weaving language. This suggests that human-like AGI could potentially emerge from large language models.

From a closer perspective, GPT-4 still holds many mysteries waiting to be unraveled. While reproducing it, we are also conducting research to uncover these secrets.

Waves: But research comes at a higher cost.

Liang: Reproduction alone is relatively cheap — based on public papers and open-source code, minimal times of training, or even fine-tuning, suffices. Research, however, involves extensive experiments, comparisons, and higher computational and talent demands.

Waves: How do you fund research?

Liang: High-Flyer is one of our investors, with ample R&D budgets. Additionally, we have several hundred million RMB allocated annually for philanthropy, which we could redirect if necessary.

Waves: However, building foundational large models requires at least two to three hundred million dollars just to get a seat at the table. How can we sustain such continuous investment?

Liang: We’re in discussions with different funding sources. From our interactions so far, many VCs seem hesitant about investing in research. They have exit requirements and prioritize rapid product commercialization, which makes it difficult to secure funding from VCs given our research-first approach. But we already have computing power and an engineering team, which is equivalent to holding half the stakes in hand.

Waves: What analyses and projections have been made regarding the business model?

Liang: What we’re considering now is to make most of our training results publicly available in the future, which could also align with commercialization efforts. We hope that more people, even small app developers, can access large models at a low cost, rather than the technology being controlled by only a few individuals or companies, leading to monopolization.

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Waves: Tech giants will also offer services at later stages. What differentiates you from them?

Liang: Giants may integrate their models with their platforms or ecosystems. Our offering is entirely open and independent.

Waves: After all, a commercial company embarking on limitless research seems irrational.

Liang: It might be hard if we must find a commercial justification, because it’s not cost-effective.

From a business perspective, fundamental research has a very low return on investment. When early investors backed OpenAI, their motivation was certainly not about how much return they would get, but a genuine desire to pursue the mission.

Things we are sure now are that we want to do this, can do this, and are capable of doing this, so we’re among the best-suited candidates to tackle it at this moment.

Ten Thousand GPUs and Their Cost

Waves: GPUs are the scarce commodity in this wave of ChatGPT-related startups, yet you had the foresight to stockpile 10,000 of them as early as 2021. Why?

Liang: It was a gradual process — from a single card in the early days to 100 cards in 2015, 1,000 cards in 2019, and then 10,000 cards. Up to a few hundred cards, we relied on external Internet data centers. When the scale expanded, we began building our own facilities.

People may think there’s some hidden business logic behind this, but it’s mainly driven by curiosity.

Waves: What kind of curiosity?

Liang: Curiosity about the boundaries of AI capabilities. For many outsiders, the wave triggered by ChatGPT has been particularly disruptive; however, for those within the field, the impact of AlexNet in 2012 has ushered in a new era. AlexNet’s error rate was significantly lower than that of other models at the time, reviving neural network research that had been dormant for decades.

While specific technical directions have constantly evolved, the combination of models, data, and computing power has remained a constant. Especially after OpenAI released GPT-3 in 2020, the direction became clear: massive computing power would be essential. Yet even in 2021, when we were investing in the construction of Yinghuo Two, most people still couldn’t grasp the rationale.

Waves: So you did start paying attention to computational power in 2012?

Liang: Researchers have an insatiable hunger for computational resources. Small experiments often lead to a desire for larger-scale trials, prompting us to continuously expand our capacity.

Waves: Some assumed your clusters were primarily for financial market predictions.

Liang: If purely for quant investing, even a small number of GPUs would suffice. Our broader research aims to understand what kind of paradigms can fully describe the entire financial market, whether there are simpler ways to express it, the boundaries of these paradigms’ capabilities, and whether they have broader applicability, among other questions.

Waves: But this process is also a money-burning endeavor.

Liang: An exciting endeavor perhaps cannot be measured purely in monetary terms. It’s like someone buying a piano for a home — first, they can afford it, and second, such a group of people are eager to play beautiful music on it.

Waves: GPUs typically depreciate at about 20% (annually).

Liang: We haven’t calculated precisely, but it’s likely less. NVIDIA GPUs hold their value well, and older cards still find buyers. Our previously retired GPUs still held decent value when sold second-hand, so we didn’t lose too much.

Waves: Clusters require significant expenses — maintenance, labor, and even electricity.

Liang: Electricity and maintenance are relatively inexpensive, constituting about 1% of hardware costs annually. Labor is more significant but represents an investment in our future and a key asset for the company. The people we choose tend to be relatively humble, driven by curiosity, and have the opportunity to conduct research here.

Waves: In 2021, High-Flyer was one of the first companies in the Asia-Pacific region to obtain A100 GPUs. How did you manage to acquire them earlier than some cloud providers?

Liang: We proactively tested and planned for new GPUs early on. Cloud providers historically catered to fragmented demands. It wasn’t until 2022 that some cloud providers began building the infrastructure, with the rise of autonomous driving and the need for rented machines to support training — along with the ability to pay for it. It is typically challenging for tech giants to focus purely on research or training, as their efforts are more driven by their business needs.

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Waves: What’s your view of the large-model competition?

Liang: Giants certainly have their advantages. However, without rapid application deployment, they may struggle to sustain, as they are more driven by the need to see the outcome.

Leading startups also have solid technical foundations, but like the earlier wave of AI startups, they still face significant challenges in commercialization.

Waves: Some think High-Flyer’s AI emphasis is PR for its other businesses as a quant fund.

Liang: In reality, our quant fund has mostly stopped external fundraising.

Waves: How do you distinguish AI believers from opportunists?

Liang: Believers were here before and will remain after the hype. They’re the ones buying GPUs in bulk or signing long-term agreements, not just renting short-term resources.

Enabling True Innovation

Waves: How is DeepSeek’s recruitment progressing?

Liang: The initial team is in place. We are borrowing temporary support from High-Flyer due to a shortage of human resources in the early stages. Since ChatGPT-3.5’s surge last year, we’ve been hiring actively, but we still need more people.

Waves: Talent in large-model startups is scarce. Investors say top talent is often confined to AI labs at giants like OpenAI and Facebook AI Research. Will you recruit from overseas AI labs?

Liang: For short-term goals, hiring experienced individuals makes sense. But long-term success does not depend that much on past experiences. Rather, it depends more on foundational skills, creativity, and passion. In this sense, domestic candidates are abundant.

Waves: Why does experience matter less?

Liang: The right person doesn’t always need prior experience. High-Flyer prioritizes capability over credentials. Core technical roles are primarily filled by recent grads or those 1–2 years out.

Waves: Is experience sometimes a hindrance to innovation?

Liang: Experienced people will tell you how something should be done without hesitation, while those without experience will explore repeatedly, think carefully, and find a solution that fits the current situation.

Waves: High-Flyer starts from an outsider to a top-tier quant fund within several years. Is this hiring philosophy a secret to its success?

Liang: Our core team, including myself, initially lacked quant experience, which is unique. It’s not necessarily a “secret” but part of our culture. We don’t deliberately avoid experienced individuals, but we focus more on ability.

For example, our top two salespeople were outsiders — one came from exporting German machinery, and the other wrote backend code at a securities firm. When they entered this field, they had no experience, no resources, and no prior connections.

Today, we might be the only large private equity firm primarily relying on direct sales — we don’t need to share fees with intermediaries, resulting in higher profit margins at the same scale and performance. Many firms have tried to imitate us, but none have succeeded.

Waves: Why hasn’t this model been successfully replicated by others?

Liang: Because this alone isn’t enough to drive innovation. It requires alignment with the company’s culture and management.

In fact, our sales team achieved nothing in their first year, and it was only in the second year that they started to see some results. But our evaluation standards are quite different from those of most companies. We don’t have KPIs or so-called quotas.

Waves: So, what are your evaluation standards to them?

Liang: Unlike most companies that focus on order volume, we don’t predefine commissions based on sales figures. Instead, we encourage our salespeople to build their own networks, connect with more people, and create greater influence.

We believe that an honest and trustworthy salesperson may not immediately drive orders in the short term, but they can make clients see them as reliable and dependable.

Waves: After selecting the right person, how do you help them get into the groove?

Liang: Assign them important tasks and avoid interfering. Let them figure things out and unleash their potential.

In reality, a company’s core essence is incredibly difficult to replicate. For example, hiring inexperienced individuals requires judging their potential and figuring out how to help them grow after they join — none of which can be directly copied.

Waves: What do you think are the necessary conditions for building an innovative organization?

Liang: In our experience, innovation requires as little intervention and management as possible, giving everyone the space to explore and the freedom to make mistakes. Innovation often arises naturally — it’s not something that can be deliberately planned or taught.

Waves: This is unconventional. How do you ensure that people work efficiently and head in the desired direction under such circumstances?

Liang: We ensure value alignment when hiring and rely on culture to maintain direction. There’s no written corporate culture, as rules can stifle innovation. More often, it’s about leadership setting an example — how you make decisions can become an unspoken guideline.

Waves: In this AI wave, could such an innovative structure of startups be a decisive edge against tech giants?

Liang: Conventional wisdom often concludes that startups with such ambitions can’t survive. However, in an ever-changing market, true success hinges on adaptability and the ability to adjust, rather than on fixed rules or conditions. Many giants struggle with inertia and can’t respond quickly to change, and this wave of AI will undoubtedly birth new companies.

True Madness

Waves: What excites you most about this endeavor?

Liang: Verifying whether our hypotheses are correct. If they are, that’s immensely satisfying.

Waves: What are the must-have criteria for your hiring talent for large models this time?

Liang: Passion and solid foundational skills. Everything else is secondary.

Waves: Are such individuals easy to find?

Liang: Their passion usually shows — they genuinely want to do this and they are often the ones actively seeking you out as well.

Waves: Large models may require endless investment. Does the cost make you hesitant?

Liang: Innovation is inherently expensive and inefficient, often accompanied by waste. That’s why it only emerges when economic development reaches a certain level. When resources are scarce or in industries not driven by innovation, cost and efficiency become essential. Even OpenAI only succeeded after burning through substantial funding.

Waves: Do you see your endeavor as madness?

Liang: I’m unsure if it’s madness, but many inexplicable phenomena exist in this world. Take many programmers, for example — they’re passionate contributors to open-source communities. Even after an exhausting day, they still dedicate time to contributing code.

Waves: There is a sense of spiritual reward in it.

Liang: It’s like walking 50 kilometers — your body is completely exhausted, but your spirit feels deeply fulfilled.

Waves: Do you think curiosity-driven madness lasts long-term?

Liang: Not everyone can stay passionate their entire life. But most people, in their younger years, can wholeheartedly dedicate themselves to something without any materialistic aims.

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For more, check out our translation of Liang’s 2024 longform interview.

Today we’re running a guest piece on lessons from the 2010 China-Japan critical minerals kerfuffle to the recent export controls China dropped in response to the revised Biden semiconductor controls. Authors Seaver Wang, Peter Cook, and Lauren Teixeira are analysts at The Breakthrough Institute, an environmental think tank based in Berkeley.

ChinaTalk is heading to NeurIPS next week! Respond to this email to connect we’d love to meet up in person.

Unpacking the Cautionary Tale of the China-Japan Rare Earths Incident

Following the Biden administration’s recent expansion of restrictions on the sale of advanced semiconductor chip and manufacturing technologies to China, Chinese policymakers have responded rapidly by restricting exports of the critical minerals germanium, gallium, and antimony to the United States. Other new provisions, whose specifics remain unclear at the time of writing, may target additional materials like tungsten and graphite. This announcement comes in the wake of recent moves by Beijing to establish stricter export permit frameworks for a range of critical commodities including tungsten, graphite, magnesium, and aluminum alloys.

With U.S.-China trade tensions only likely to intensify in coming months, such raw material supply chain risks are becoming increasingly relevant for energy transition efforts as a whole. Other critical mineral export restrictions relevant for clean energy technologies could conceivably soon follow, with effects that may not be limited to the United States.

In Myanmar, for instance, resistance fighters from the Kachin Independence Organisation recently captured much of Pang War township, shutting down Myanmar’s largest rare earth mining hub and prompting Chinese authorities to close the nearby border crossing. Virtually unregulated mining in Myanmar contributes an unknown but large fraction of global rare earth element (REE) mining, with all of Myanmar’s production shipped to neighboring China, the world’s dominant refiner of rare earth materials. This latest development in a civil war turning increasingly in favor of anti-junta resistance groups has begun to send shivers through critical mineral markets, with industry observers speculating about a future rare earth shortage and price spikes.

If REEs become scarce, Chinese policymakers may clamp down on REE exports next to reserve more of these valuable critical minerals for domestic high-tech industries. Such restrictions could impose constraints upon the rest of the world, including overseas efforts to nurture clean technology sectors like wind power and electric vehicles that rely upon REEs for permanent magnet drives.

In response to critiques that clean energy sectors depend overly on key commodities imported from China, climate advocates and climate policy hawks have often argued that a country only needs to import battery minerals, solar panels, or electric cars once, at which point they escape the control of the exporting trade partner while operating for decades. This contrasts with continuous flows of fossil fuels whose interruption can immediately catapult energy supplies into a crisis. This reasoning is correct in principle, but supply chain disruptions would nevertheless stall acquisition—or manufacturing—of subsequent batches of low-carbon technologies. Such supply vulnerabilities can certainly freeze energy transition efforts in their tracks and force factories producing energy technologies to go idle.

The preeminent and most-invoked example of supply chain coercion remains China’s disruption of rare earth exports to Japan during the 2010 Senkaku Islands incident. A critical reexamination of this incident reveals a few useful insights that may help observers better understand these newest limits on critical mineral exports from China. The de-facto embargo in 2010 was likely opportunistic rather than planned—an impromptu exploitation of an issue prominent in preceding China-Japan negotiations rather than the culmination of some grand industrial geostrategic conspiracy. Yet this incident certainly cemented the perception that Chinese policymakers have and will wield control of strategic supply chains for geopolitical leverage—a concern that Beijing itself has reinforced since. These latest developments emphasize that policymakers and clean technology companies should be taking immediate steps to reduce supply chain vulnerabilities, if necessary even at what may seem like uneconomically high cost.

When Geopolitical Tensions Spill over into Supply Chains

According to conventional retellings, a number of Japanese companies reported a halt to expected rare earth ore shipments from China beginning Tuesday, September 21, 2010. This coincided with more overt political pressure tactics that had begun days prior, including a cessation of ministerial and provincial exchanges, a popular campaign to limit tourist visits to Japan, the detainment of four Japanese nationals in China, and an exclusion of Japanese companies from bidding on Chinese public projects. Many of these actions followed a Japanese government decision on September 19 to extend the detention of a Chinese fishing boat captain involved in collisions with two Japanese Coast Guard vessels near the Senkaku Islands on September 7.

Japan released the captain on September 25, and Chinese customs offices partially resumed clearing some REE shipments for export several days later. However, international traders, companies, and government officials continued to report systematic interruptions and delays for shipments to Japan as well as some U.S. and Europe-bound exports throughout October and the first half of November.

Following initial reports of blocked shipments by the New York Times and Nikkei on 23 September, Japanese government press conferences the next day on the matter produced a flurry of attention in Japanese and English-language press, at minimum including four Nikkei articles, three Asahi articles, and coverage in Reuters, France24, the New York Times, the Wall Street Journal, Bloomberg, the Japan Times, and the Atlantic—all within a 24-hour period.

Asahi reporting from September 24 already described the situation as “appearing to be an effective embargo”, quoting a China-based REE manufacturing executive as having received instructions from Chinese customs officials to “stop exports until the 29th”. International customers including representatives of Australian, Canadian, Chinese, and Japanese firms all confirmed the suspension of shipments. Japanese government surveys of industry stakeholders in late September 2010 reported a clear consensus that export problems had increased after 21 September, driven by numerous sudden changes in Chinese customs enforcement. Out of 31 responding firms that confirmed their involvement in rare earths trade, all 31 reported encountering export obstacles. By Tuesday 28 September, Japan’s Minister for Economic and Fiscal Policy Banri Kaieda described the situation accordingly at a press conference: “Right now, the de-facto export prohibition that China has adopted is causing profoundly great impacts on Japan’s economy.”.

Notably, contemporary commentary showed a clear understanding that China had already slashed their REE export quotas a few months earlier, observing that the disruptions beginning in late September seemed separate and distinct from this earlier policy change. Articles by Toyo Keizai and Mitsubishi’s think tank MUFC published just days before the export halt very matter-of-factly articulated that China was reducing export quotas to nurture domestic industries, regulate foreign investment in the sector, and limit expansion of new mining for environmental reasons. Reporting from September 25 highlighted arguments by industry observers that they wouldn’t expect producers to exhaust their export quotas until late October at the earliest, with traders noting that even Chinese producers with ample spare export quotas had “been dissuaded” from exporting. In subsequent interviews with researchers, Japanese officials confirmed an internal understanding at the time that the central Chinese government had issued an order, and that the Japanese government interpreted the incident as an economic sanction.

These contemporaneous official government statements, media reporting, comments from industry, and policy responses across English, Japanese, and Chinese-language sources shared a clear understanding that Chinese officials had implemented a de-facto export ban, prompting many governments worldwide to lodge protests while urgently pursuing supply chain alternatives and countermeasures. Even a Chinese People’s Daily article from late 2012 more or less stated: “Even though China did not publicly admit to employing economic sanctions, China did in reality halt export shipments, subjecting Japan to some difficulties at the time”.

How Real were the Impacts on Rare Earth Element Trade?

Some work in late 2010 and since has challenged this prevailing storyline, arguing that this period of scarce supply and price spikes beginning in late 2010 did stem mostly from China’s stricter export quotas imposed in July—a policy action well predating the diplomatic dispute. Such commentators argue China’s export policies sought only favorable domestic economic outcomes—more stringent environmental regulation of the REE sector and better capture of value-added downstream industries. Revisionist retellings at times go even further, arguing that any resulting supply shortages in late 2010 did not explicitly target Japan and warning against invented narratives of Chinese mineral supply chain coercion. However, such interpretations stray from the historical record and often overstate their case.

Commentators arguing that China’s undeclared interference in rare earth trade in late 2010 is exaggerated “folklore” have often cited a few articles that analyzed monthly Japanese customs or UN data on value of trade in various goods, claiming that overall, broad categories of rare earths traded with Japan do not seem to exhibit quantitative disruptions during this period. However, such low-resolution, indirect data does not distinguish between far more valuable heavy rare earth elements important for high-tech applications versus more abundant light rare earths like cerium that primarily see use in more mundane industrial processes.

Overall, the cited data don’t contain enough detail to draw a clear conclusion that no significant disruptions occurred. Summary data on total rare earth shipment arrivals in Japan might conceal a decline in imports from China compensated by urgently redirected materials sourced from Southeast Asia, Europe, or North America. Similarly, indirect metrics like the monthly value of rare earth shipments from China to Japan may not accurately capture simultaneously evolving variables, like a decline in import tonnage offset by a corresponding spike in rare earth prices. Moreover, monthly-scale data may not confidently capture shorter-term disruptions and delays that began towards the end of September 2010 and varied from week to week thereafter. Finally, such sterile retrospective analyses of trade data in isolation ignores a vast weight of contemporaneous, corroborating testimony and reporting, such as the official surveys of affected industries.

One should also recall that broader Chinese economic coercion aimed at Japan in late September 2010 was not seeking to damage Japan materially so much as to accomplish a specific goal: the successful release of the detained fishing boat captain.

It is true however that China did dramatically alter export and industrial policies for the rare earths sector earlier in 2010. These changes indeed stemmed in part from domestic environmental considerations and aspirations to further develop downstream value-added industries like rare earth permanent magnet manufacturing. And while the particularly sharp reduction in export quotas in July 2010 generated significant international attention and discussion for months predating the Senkaku islands dispute, Chinese national policy had long treated REEs as a strategic commodity and regularly revised regulations and export practices over the years.

While rare earth elements are widely distributed globally, southern China hosts a notable concentration of ion adsorption clay (IAC) deposits, located at relatively shallow depths and mineable using simpler methods in small-scale operations. These deposits tend to form in temperate or tropical climates with higher temperatures and rainfall that can leach REEs from bedrock and concentrate them in clay soils. IAC deposits typically contain higher grades of heavy REEs relative to hardrock REE deposits, may not require onsite milling, and allow for initial processing onsite using pit leaching, often using ammonium sulfates. Such low-cost IAC mining operations have driven much of the growth in China’s rare earth sector over recent decades, albeit with considerable environmental impacts that have prompted stricter regulations since the mid-2010s.

Starting in 1985, the Chinese government began offering an export rebate to REE enterprises to encourage rare earth exports, refunding the value-added tax that producers paid on exported products. Following China’s overtaking of the United States as the world’s largest REE producer in the late 1980s, Chinese policymakers designated REEs as strategic minerals as early as 1990, with national production ramping up dramatically through the 1990s thanks largely to growth in small-scale projects targeting IAC deposits. By 2000, in light of increasing domestic industry demand for rare earths, the central government reduced export rebates before eliminating them altogether in 2005. With the subsequent introduction of export duties for rare earths in 2007, China’s export strategy had entirely reversed. Policymakers had already implemented export quotas years earlier in 1999 to control total national production and curb smuggling, and would progressively reduce quotas every year between 2005 and 2010.

The dramatically lowered export quota announced in mid-2010 may very well have contributed to the continuing customs delays and export disruptions throughout October and November that year. But the intensity and timing of events in late September coincided far too closely with the China-Japan diplomatic crisis to discount as a bureaucratic coincidence. Even Chinese commerce minister Chen Deming drew a link between the two issues in a televised interview on 26 September, suggesting that Chinese businesses might be acting on their own patriotic initiative to pause shipments.

International governments certainly interpreted this rare earths shock as an undeclared set of sanctions. In retrospect perhaps these trade disruptions appear short-lived to observers today, but in the moment the affected actors saw these measures as indefinite and reacted with alarm. By October 3rd, Japanese officials were negotiating with the Mongolian government to develop new rare earth mining projects in Mongolia. By late October, Japan and Korea had announced a partnership in which Japan would help Korea survey potential deposits. Within a couple months, the United States and Japan were exploring projects in California, Australia, and Indonesia.

Implications of China’s Recent Export Restriction

Chinese policymakers likely weaponized rare earth exports opportunistically in the moment. The framework for export limits did genuinely originate out of industrial policy crafted with China’s national interest in mind, and well predated the tensions that prompted their temporary weaponization. Japan and China had been negotiating specifically over rare earth export quotas earlier in the year—including just weeks beforehand. With the issue fresh in recent memory, Beijing policymakers understood full well that this was a powerful lever in China-Japan relations.

The 2010 rare earths disruption and the current situation now unfolding between China and the United States share some similarities but also exhibit notable differences. As in 2010, the new Chinese export restrictions on gallium, germanium, and other critical mineral shipments to the U.S. clearly form part of a planned tit-for-tat response to the latest U.S. restrictions targeting the Chinese semiconductor industry manufacturing chain. In contrast to the 2010 incident, however, Beijing’s leverage of critical mineral supply chains is now overt and explicit, rather than ambiguous. Furthermore, whereas disruption of rare earth shipments to Japan may have served a narrow, temporary geopolitical purpose, U.S.-China cooperation for advanced technology leadership clearly spans a far broader scope, with no simple or near-term resolution in sight.

Meanwhile, with China now operating export control frameworks for everything from tungsten to magnesium to rare earth concentrating equipment to solar manufacturing machinery, the possibility of further escalation looms large—with significant implications for clean technology supply chains and trade.

The lesson from the 2010 rare earths shock and its origins emphasizes that Chinese export controls on critical minerals likely originated out of narrow national economic self-interest, rather than serving as part of some grand strategic conspiracy. But fundamentally speaking, the combination of overwhelming market share control and absolute authority over export policies means that Beijing can control market supply and international prices for a wide host of critical commodities with the stroke of a pen, an ability whose geopolitical utility is clearly now obvious to Chinese leaders. Should the right situation arise, the tools for bottlenecking trade already exist, including substantial latitude for subtle, undeclared, and plausibly deniable economic coercion in addition to the overt measures now enjoying the spotlight.

The only solution to this dynamic of self-perpetuating Chinese critical mineral market overconcentration is a forceful strategy of supply chain expansion and diversification. Such a strategy must dispense with the futile practice of tepidly ushering new entrants into unforgiving markets built upon lopsided terms of competition. Rather, governments must stubbornly and persistently ensure that alternative producers survive and multiply—in and of itself a necessary prerequisite for fostering competition and breaking monopoly power.

Ultimately, the world’s access to crucial advanced energy technologies cannot depend upon some People’s Liberation Army Air Force pilot’s ability to execute a reckless aerial maneuver around a Taiwanese patrol aircraft. The ease with which even the most optimistic clean energy commentator can imagine such a contingency should stress that both the geopolitical and decarbonization stakes of such efforts are high.

Back to Jordan writing: For some contemporary context, Bloomberg’s Gerard Dipippo echoes my take. As long as China is still selling outside the country, the US firms can play the trade diversion game just as well as Huawei and SMIC can.

Commerce released its much-anticipated chip export-control updates yesterday. To discuss, I was joined by Dylan Patel of SemiAnalysis and Greg Allen from CSIS.

We were not impressed. To explain why, we get into:

• What’s in the new controls: high bandwidth memory, FDPR, and the Entity List.

• How key assumptions in Biden’s approach to export controls limited their ultimate impact.

• How China’s stockpiling spree may have already rendered these new rules partially obsolete, and what policymakers can do about that going forward.

• The law-enforcement approach vs. the counterintelligence approach, and whether export controls should be a foreign-policy tool or simply a law-enforcement activity.

• How the new chip controls are like removing puzzle pieces just one at a time — and why that’s exactly what China wants to slowly but surely self-indigenize.

• The “America First” rationale for export controls and domestic chip production.

• Why the Democrats’ regulatory design philosophy was lured away by the promise of complexity — and what the Trump administration could do differently going forward.

Click this link to listen to the show on your favorite podcast app.

First, two disclaimers: Most at BIS and within the administration are well-intentioned, understand the stakes, and have worked incredibly hard these past four years to help America compete in chips and AI. We don’t mean to question anyone’s integrity — but at ChinaTalk, we call it like we see it. Also, we recorded this yesterday the same day the regs were released, and given their complexity our takes are inevitably provisional.

Second, a job post. ChinaTalk is hiring for a dedicated China AI lab analyst. Chinese fluency and a technical background are required. Apply here!

And third, a call for donations. ChinaTalk is teaming up the Substack community and GiveDirectly to raise money for households in rural Rwanda. The link to give is here. Every donation made before midnight today will be doubled through GiveDirectly’s matching fund.

When Regs Meet Reality

Jordan Schneider: First, why care about any of this? A four step logic chain.

1. The US is in strategic competition with China;

2. Semiconductors and AI applications will shape the contours of the 21st century;

3. Among AI’s three components — data, algorithms, and hardware — hardware is the area where liberal democracies have the best chance of developing a long-term competitive advantage over China;

4. This advantage can be maintained only through aggressive government intervention.

The October 2022 export controls were excellent — prescient in addressing the competition’s stakes before ChatGPT’s release, and creative in deploying new authorities in an area where the US government had to quickly develop expertise. The October 2023 update, while delayed, effectively addressed major loopholes, particularly regarding GPU exports.

However, over the past 18 months, it has become increasingly clear that semiconductor export controls aren’t achieving their intended goal of slowing Chinese progress in advanced semiconductor development. The new rules released today I can’t give anything higher than a C+. There are real steps forward in these regs, but their delayed release was deeply harmful, and there are far too many counterproductive concessions to industry.

While many government tasks are genuinely difficult — educating a nation, pushing the frontiers of science, achieving peace in the Middle East — crafting effective export controls is relatively straightforward. The US, through its engineering excellence and position as the arsenal of democracy, has tremendous leverage over global technological flows and its treaty allies. Congress has given the Commerce Department statutory power, and the Treasury has provided the framework. The process is simple: write regulations, enforce them with billion-dollar fines, and you create a powerful global compliance regime.

Companies and nations are about to stomach far more stringent measures under a Trump administration to maintain good relations with America than what Biden could have implemented under a more expansive vision of semiconductor export controls. However, modern Democrats seem reluctant to fully commit to aggressive action. The result is an overly complex policy that trips over itself and misses the bigger picture.

Greg Allen: These export controls present a mixed picture. They’re undeniably stronger than the October 2023 update, but two crucial factors affect their impact: timing and implementation. The delayed release is significant, particularly considering Chinese stockpiling. While the controls are stronger, major gaps remain in the overall framework.

The Biden administration’s high-level strategic vision for semiconductor export controls makes sense conceptually. However, there’s a disconnect between this vision and its implementation across these 200-plus pages of policy. Chinese customers and their suppliers have demonstrated infinite capacity to find legal loopholes, working continuously, while our government manages only one update per year. This mismatch in pace of legal innovation is problematic.

Jordan Schneider: What was the strategic conception that limited the Biden administration’s speed and aggressiveness? What were their key assumptions?

Greg Allen: Two main factors created boundaries: the complexity of these controls, and the stakeholder dynamics. These regulations are massive and incredibly complex.

This complexity stems from negotiations involving three main stakeholder groups:

1. The US interagency process (Commerce, State Department, Defense Department, intelligence community, White House)

2. US industry, which maintains dialogue with all these organizations

3. Other governments, particularly Japan and the Netherlands, who have their own semiconductor manufacturing equipment export controls

The controls must be multilateral to prevent other countries from simply filling the gap left by US restrictions. Beyond Japan and the Netherlands, other crucial players include Taiwan, Korea, and various European countries. This extensive consultation process results in 200-plus pages of regulations that everyone can “agree” to, but requires a full year between updates.

Meanwhile, China rapidly identifies every loophole and stockpiles materials for future needs. While we have significant advantages in strategic technology competition with China, the question becomes how effectively we utilize our advantages compared to how China leverages theirs.

Jordan Schneider: Let’s examine the premise that Japanese and Dutch cooperation is essential. From a legal-technical perspective, it’s not. A more unilateral approach could implement the Foreign Direct Product Rule, stating that any company using American technology selling restricted equipment would violate US law, facing billions in fines and potential stock exchange delisting.

Unlike the satellite industry situation in the 1990s, these technologies are so complex that companies couldn’t simply engineer around American contributions to sell to Chinese fabs. The Biden administration understood this potential leverage but seemed unwilling to forcefully impose it on Japanese and Dutch partners, largely because their central foreign policy ethos emphasized cooperative international relations after the Trump era.

This reluctance to use maximum leverage led to extended negotiations resulting in complex, 200-page regulations that will enrich export control lawyers. If we can identify numerous billion-dollar loopholes within hours of release, imagine what lawyers will find in a month.

Greg Allen: The Foreign Direct Product Rule and its extraterritorial application is crucial here. While other countries may lack similar authority — as demonstrated when Japanese companies circumvented restrictions on semiconductor chemical sales to South Korea — this new package significantly expands the rule’s scope.

Let me break down this extraordinary expansion of legal authority. The traditional Foreign Direct Product Rule might prevent, for example, German companies from simply repainting American missiles and selling them to restricted countries. The 2020 Huawei controls expanded this to cover chips made using US equipment, even if manufactured in Taiwan.

The December 2 rule goes further: if your chip equipment contains any chips made using US machines, the Foreign Direct Product Rule applies. This effectively covers almost every machine globally, including Chinese ones, since virtually all computer chips involve US technology in their production.

Notably, Japan and the Netherlands received exemptions when shipping from their territories, essentially as recognition for adopting their own export controls. However, the rule still applies to their companies’ operations in other locations, such as Japanese company Tokyo Electron’s shipments from Malaysia.

Jordan Schneider: Let’s examine the other assumption — the perceived need to accommodate industry demands. Based on the rule’s writing, timelines, and recent reporting, it’s clear that American semiconductor manufacturing companies’ concerns influenced the decision-making process. The final rule takes seriously corporate fears about these rules doing lasting damage to American SME.

Dylan, could you discuss semiconductor equipment manufacturing firms’ sales and market performance since October 2022?

Dylan Patel: When the October 2022 regulations were announced, everyone panicked initially — the first reading suggested everything would be blocked. Then it became clear these regulations were full of holes. This triggered a surge in Chinese purchasing, as they realized they could still get what they needed despite nominal restrictions.

China’s share of purchases from major equipment companies jumped from around 30% to the high 40s — peaking at 49% for some companies. After the October 2023 update, business dipped briefly but quickly rebounded as new loopholes emerged. This pattern appears to be repeating.

In some cases, there won’t be any business decrease. Applied Materials’s largest Chinese customer faces virtually no restrictions and will continue increasing purchases. They’ll spend more on memory equipment than the largest American memory company. These companies will maintain their profitable Chinese business because lobbyists ensured loopholes remained — or new ones emerged.

The stocks have risen significantly, and their China revenue is up massively. Another key development — their production outside the US has soared, whether it’s Lam Research in Malaysia or Applied Materials and KLA in Singapore. These restrictions have driven massive expansion of non-US production.

Greg Allen: The export restrictions have impacted the composition of semiconductor manufacturing equipment demand. China is buying more legacy equipment since advanced node chip manufacturing faces restrictions. Much production that would have occurred in China has moved elsewhere.

ASML’s executives have stated their demand forecast isn’t based on China’s actions but on overall chip demand — like how many chips the next Apple smartphone needs. Whether those chips are made in China, Taiwan, or Korea, they’ll be produced because end-market demand exists, and ASML holds a near-monopoly.

Regarding China’s growing demand, I expect it to decrease in the next year or two, regardless of export controls. They’ve pulled forward significant demand through stockpiling — buying three to five years’ worth of equipment. ASML reports their Chinese customers struggle to install equipment as fast as they’re acquiring it, anticipating future export controls. That 49% quarter reflected purchases intended for 2025-2027.

Dylan Patel: Previous rounds of Chinese restrictions have shown they maintain a high percentage of revenue longer than expected. While they’re purchasing beyond current plans, money continues flowing because strategic priorities and purchasing waves persist for years — even when market-based demand would suggest three years’ worth should suffice.

What’s in the Regs

Greg Allen: This regulation has three major components.

1. First, after two years of restricting AI chip sales on the logic side, it now addresses memory — specifically, high-bandwidth memory chips.

2. Second, it significantly expands the Foreign Direct Product Rule’s application to semiconductor manufacturing equipment.

3. Third, it adds numerous Chinese companies to the Entity List — identified by the US government as shell companies for Huawei, SMIC, and others.

Jordan Schneider: Let’s start with high-bandwidth memory (HBM). What is it, and why is it important?

Dylan Patel: Looking at an AI chip like Nvidia H100 or Google TPU, roughly half the manufacturing cost — and it’s trending higher — comes from high-bandwidth memory. While TSMC remains the linchpin for making the logic, the logic chip itself is less valuable on a total cost basis than the high-bandwidth memory.

We’ve restricted AI chips to China to varying degrees. Though some still slip through smuggling, China faces decent restrictions on AI chips or receives weaker special versions. However, high-bandwidth memory hasn’t been restricted at all. This memory, alongside logic, represents the two linchpins of AI chip manufacturing.

ChinaTalk listeners have heard much about SMIC and advanced logic, but less about China’s high-bandwidth memory. Their high-bandwidth memory manufacturing ecosystem lags behind their advanced logic development — it’s received less focus. Korean companies have readily sold HBM to China.

A major market story involves Samsung’s struggles — they still can’t sell HBM memory to Nvidia because their quality falls below SK hynix and Micron. Despite being the world’s largest memory maker, Samsung isn’t supplying the highest-end Nvidia products. Their organizational leader issued an apology note so drastic that people joked someone might have hanged themselves in the parking lot.

Samsung’s largest HBM customer today is China, representing about 30% of their HBM sales. They sell some to Google TPU, Nvidia, and Amazon, but most ends up in Huawei Ascend products and upcoming AI products. These AI chips continue domestic manufacturing despite lacking HBM production capacity.

Some puzzling aspects remain. CXMT, Applied Materials’ largest equipment customer, has an HBM manufacturing subsidiary about a year from production — is not entity-listed. Similarly, Huawei’s HBM manufacturing subsidiary isn’t listed. Despite equipment controls potentially catching shipments to them, they avoided Entity Listing. Nevertheless, this necessary regulation helps prevent China from acquiring AI chips.

Jordan Schneider: Oddly, this doesn’t take effect for a month. We’ll see planes loaded with high-bandwidth memory flying to China over the holidays.

Dylan Patel: This actually reflects the need to communicate with other parties. When you ban chip manufacturing immediately, you must address existing inventory. Nvidia, Google, and Amazon don’t want HBM2E anymore. When Nvidia faced restrictions on selling AI chips, they could redirect sales elsewhere during the chip shortage. With HBM, Nvidia has no interest — they’re focused on HBM3e for upcoming product launches.

Greg Allen: Multiple types of high-bandwidth memory exist: HBM2 (since 2017), HBM2E, HBM3E, HBM4, and soon HBM5. The rule still permits HBM2 sales to China, though with intense end-user checks and new regulations. You can sell HBM2 to Chinese customers directly, but not through distributors, and not to those planning to use it in AI chips. While HBM has other applications, AI drives the primary demand.

This approach considers Samsung’s desperate position in the HBM market while attempting to control distribution through end-user verification. Chinese companies might achieve large-scale HBM2 manufacturing within a year. The strategy mirrors our logic chip approach — banning advanced GPUs while allowing older, lower-performing versions, despite the strategy’s potential failures.

Jordan Schneider: This raises another strategic question — whether end-use controls limiting specific fabs or customers represent a reasonable policy approach compared to nationwide controls found in other components of current and past regulations. What’s your take on this strategy’s efficacy?

Greg Allen: The government’s opinion on this strategy appears in the document. They acknowledge that while end-use based controls have had some effect, circumvention has occurred. Consider this — if selling equipment to companies engaged in advanced chip production in China was already illegal based on end-use criteria, why add these companies on an end-user basis?

The Commerce Department and selling industry effectively self-assessed their inadequate effectiveness in preventing targeted sales through end-use controls. This doesn’t mean the controls had no effect — SMIC can’t produce as many 7-nanometer chips as they’d like due to equipment constraints — but the impact could have been stronger.

Jordan Schneider: Let’s move to part two, FDPR.

Greg Allen: After discussing restrictions on logic and memory chips themselves, we must consider manufacturing equipment. There’s no strategic value in restricting chip sales if China can produce them domestically. While China has a domestic equipment industry, it remains small globally and technologically inferior to US, Dutch, and Japanese state-of-the-art capabilities.

This control significantly expands the Foreign Direct Product Rule’s application to semiconductor manufacturing equipment.

Let me explain through simplified legalese: the basic version prevents scenarios like selling missiles to Germany, who might repaint them and resell to Russia. The rule states that regardless of modifications, it remains an American missile under US law.

In 2020, the Trump administration expanded this interpretation to include chips made by TSMC using American-built semiconductor manufacturing equipment. This effectively cut Huawei off from advanced smartphone processors. The new control goes further: if your chip manufacturing equipment contains any chip made using US equipment, the rule applies. This encompasses virtually all semiconductor manufacturing equipment globally, including Chinese-made equipment.

The rule has two triggering mechanisms.

1. First, advanced semiconductor manufacturing equipment. Essentially all equipment needed in the EUV era — including lithography, deposition, etch, and metrology equivalents — regardless of origin, cannot be sold to China. This addresses previous loopholes where US manufacturers moved production abroad. The restriction affects foreign providers, too. Tokyo Electron, for instance, faces the rule when shipping from Malaysia, while shipments from Japan or the Netherlands fall under local versions of the rule.

2. The second trigger involves end-user and end-use controls. Customers engaged in advanced semiconductor manufacturing or identified as risks for diversion to Huawei or SMIC face restrictions.

This represents a massive regulatory change that might affect semiconductor manufacturing equipment stocks.

Dylan Patel: I see two main workarounds.

1. First, the diplomatic exception for Japan and Netherlands — they’ll implement their own versions months later, as they did after the October 7 restrictions.

2. Second, the rule apparently doesn’t cover subsystems sold to China. It covers only equipment. Companies like UltraClean — which makes cleaning equipment for Applied Materials and Lam Research — seem unaffected unless selling to entity-listed companies.

Greg Allen: The rule significantly expands the list of Chinese semiconductor manufacturing equipment producers on the Entity List, including major component producers. Since October 2022, US companies cannot assist Chinese semiconductor manufacturing equipment providers. Strategically, if we don’t want China having chips, we shouldn’t provide equipment, components, or intellectual property for their production.

Dylan Patel: Companies like Ultra Clean and MKS Instruments apparently can still sell subsystems to China, except to Entity Listed companies like NAURA 北方华创, China’s largest equipment maker. This represents a potential loophole in the current regulations.

Jordan Schneider: Greg, let’s move to part three — Entity List.

Greg Allen: The third part represents a massive expansion of Chinese entities on the Entity List, primarily focusing on fabs identified as potential diversion risks to Huawei or SMIC. These are shell companies that were missed in the previous Entity List update.

The expansion includes chip fabs and companies manufacturing equipment or equipment components in China. In defense of the US government’s position — while end-use based controls might be sufficient for US oversight, the Dutch and Japanese lack equally effective implementation capabilities. Adding companies to the Entity List clarifies our expectations to allies regarding rule implementation.

This also helps Bureau of Industry and Security license reviewers. When a Chinese firm’s lawyer provides a sworn statement denying advanced chip manufacturing involvement, finding that company on the Entity List immediately invalidates such claims.

Jordan Schneider: Dylan, were there any notable fabs or companies excluded?

Dylan Patel: There are three major players in China today: SMIC (China’s logic manufacturing champion), CXMT (China’s memory champion), and Huawei, which handles both aspects independently. Through their subsidiaries, Huawei ranks as either the third or fourth largest equipment purchaser globally.

Regarding SMIC, the changes were minimal. They adjusted the licensing policy for their original Beijing fab to “presumption of denial,” but their Beijing, Tianjin, and Shanghai facilities remained largely untouched. For instance, the wafer bridge issue we discussed in our Fab Whack-A-Mole report — where one fab is Entity Listed while another isn’t — wasn’t fully addressed.

Greg Allen: They did add language about physical connections between fabs, specifically addressing wafer bridges — though it applies only when equipment can be definitively leveraged across facilities. They’re attempting to address geographic proximity issues, like situations where you can’t sell to SMIC but can sell to a supposedly different company across the street. The effectiveness remains to be seen, but they’ve acknowledged these concerns.

Dylan Patel: Even with potential wafer bridge restrictions, their new fabs established since 2022 haven’t faced restrictions beyond end-use controls. SMIC was initially added to the Entity List in 2020, but these new facilities operate without additional constraints because they claim to develop only 28-nanometer technology and above.

Greg Allen: All of that is in in air quotes…

Dylan Patel: Exactly. The insufficient impact on SMIC represents a major issue. Regarding CXMT, which produces memory and DRAM for HBM and standard applications: they’re China’s largest equipment purchaser by individual entity and Applied Materials’s biggest Chinese customer. And they weren’t added to any Entity List, despite clear violations.

The government initially set an 18-nanometer half-pitch restriction for DRAM in 2022. When CXMT’s 17-nanometer technology violated this limit, they simply relabeled it as 18.5-nanometer. The new regulations now include specific physical metrics and memory cell sizes to prevent such ambiguity.

Additionally, CXMT presented research at a US technical conference showing vertical gate-all-around transistor development below the 18-nanometer half-pitch restriction. Despite publicly demonstrating violations of both the transistor and pitch regulations, no action was taken. Their HBM subsidiary also remains unlisted. Tool restrictions might affect them, but that’s uncertain.

Greg Allen: It’s baffling. We’re telling China they can’t buy foreign HBM anymore, yet we’ve exempted their national champion in HBM. The reasoning is unclear.

Jordan Schneider: This raises questions about plausible deniability. Regarding Western and foreign equipment manufacturers — how aware are they of what their machines are getting used for?

Dylan Patel: They definitely understand but avoid written documentation. Equipment servicing generates substantial data logs, particularly for EUV tools which require constant connectivity. Manufacturing involves two-way communication — companies seek advice and assistance from equipment makers. While manufacturers could theoretically ignore the data, they’re aware of actual usage patterns.

There’s an unverified rumor about a senior US government official potentially joining an equipment company’s board…the regulations significantly impact equipment makers’ competitors but barely affect Nvidia’s Chinese competitors. The disparity between naming 140 equipment companies versus few fabs raises questions.

Greg Allen: Regarding foreign companies’ perspectives, Japanese firms often misinterpret US objectives. A Murata executive suggested developing parallel supply chains for US-led and China-led economic blocs. This misses the point — our goal isn’t supply chain separation but strategic impact on China’s AI industry.

The Biden administration’s communication of strategic rationale has been imperfect. The AI National Security Memorandum finally clarified the focus on frontier AI and maintaining long-term competitive advantage — but this message needs consistent reinforcement in foreign capitals.

Jordan Schneider: I don’t blame them for not understanding! Companies have a fiduciary responsibility to prioritize profit over American long-term national competitiveness. The solution mirrors the Treasury Department’s approach in the 2000s and 2010s: substantial fines for violations. The lack of major enforcement actions against Japanese and American firms undermines regulatory effectiveness.

The absence of CXMT from the Entity List, despite partial coverage by various restrictions, exemplifies this problem. Besides small-scale smuggling cases and unresolved investigations into companies like Applied, there haven’t been meaningful penalties for pushing regulatory boundaries. Companies continue selling billions in equipment while strategic objectives remain unfulfilled.

Dylan Patel: There was one last carveout that reveals the current strategy of BIS and the Commerce Department. The question is, “Why aren’t all Huawei chip production facilities on the Entity List?” Many remain unlisted.

According to the Financial Times:

Asked how many fabrication plants exist that are not on the list, a second US official would say only that the controls were focused on advanced chip production. People familiar with the situation said there had been an intense debate inside the administration over how to tackle Huawei. One person said some of the Huawei plants were still not operational, so it was unclear if they would be for advanced chips.

This implies they won’t put facilities on the Entity List until they produce advanced chips — which fundamentally misunderstands how fabs work. You purchase the equipment first, set up manufacturing, then produce chips. By the time you’re producing, most equipment is already in place.

Take TSMC, for example. They’re not buying equipment in Arizona for 5nm/4nm anymore. While they’re still purchasing some 3nm equipment, most of their purchases for next year target 2nm production, even though those chips won’t emerge until 2026.

Following this logic, if TSMC were Chinese, we wouldn’t ban them until 2026 when their 2nm chips appear in iPhones — long after they’ve acquired all the necessary equipment in 2025. This same approach applies to Huawei entities, considering more than half remain unlisted.

Greg Allen: This highlights a crucial divide in export-control implementation.

Consider this analogy:

• The law enforcement approach: for example, a US citizen accused of spying for China remains innocent until proven guilty in court, maintaining all citizen rights. 

• The counterintelligence approach: someone merely suspected of being a Chinese spy can lose their security clearance immediately. They don’t wait for definitive proof because, by then, the damage to national security would be done.

BIS currently operates exclusively from the law enforcement mindset — for both good and bad reasons. They treat Huawei fabs as innocent until proven guilty, assuming legacy chip production until shown otherwise. However, waiting for proof means potentially compromising national security and undermining policy effectiveness.

The fundamental question becomes: Are export controls a foreign policy tool for achieving strategic outcomes, or simply a law enforcement activity? We need this mindset shift, but it hasn’t happened yet.

Jordan Schneider: Let’s be clear about the capacity of the law enforcement approach: it only took a TechInsights teardown to discover that TSMC had been manufacturing chips for Huawei. This reveals the limitations of US intelligence community and law enforcement’s ability to pursue that approach.

Greg Allen: This isn’t about the intelligence community’s ability to help; it’s about their willingness. Declassified CIA documents from the 1970s and 1980s show remarkable work assisting export control enforcement. Their Cold War efforts were impressive.

Fast forward to 2024 — where is the intelligence community now? Why was Gina Raimondo blindsided during her China trip by news of the new Huawei phone? Such revelations should come from our intelligence services, not from China. The question isn’t about capability — we know they can perform extraordinarily when motivated — but whether they’re even trying.

Okay, Trump — Your Turn

Jordan Schneider: So we have new regulations with significant gaps, and a new president arriving in six weeks. What should Trump and his team do on chips? And what do you think they will do?

Paid subscribers get access to the rest of our conversation, which includes:

• Dylan’s and Greg’s pitches to incoming Commerce Secretary Howard Lutnick.

• Why America’s “scalpel approach” to chip controls backfired and what a “shotgun approach” could look like.

• How China’s focus on trailing-edge chips and power semiconductors creates vulnerabilities that current controls don’t address.

• How Trump’s team might use novel tariff strategies to turn China’s massive chip buildout into “ghost fabs”.

Read more

Deepseek is a Chinese AI startup whose latest R1 model beat OpenAI’s o1 on multiple reasoning benchmarks. Despite its low profile, Deepseek is the Chinese AI lab to watch.

Before Deepseek, CEO Liang Wenfeng’s main venture was High-Flyer (幻方), a top 4 Chinese quantitative hedge fund last valued at $8 billion. Deepseek is fully funded by High-Flyer and has no plans to fundraise. It focuses on building foundational technology rather than commercial applications and has committed to open sourcing all of its models. It has also singlehandedly kicked off price wars in China by charging very affordable API rates. Despite this, Deepseek can afford to stay in the scaling game: with access to High-Flyer’s compute clusters, Dylan Patel’s best guess is they have upwards of “50k Hopper GPUs,” orders of magnitude more compute power than the 10k A100s they cop to publicly.

Deepseek’s strategy is grounded in their ambition to build AGI. Unlike previous spins on the theme, Deepseek’s mission statement does not mention safety, competition, or stakes for humanity, but only “unraveling the mystery of AGI with curiosity”. Accordingly, the lab has been laser-focused on research into potentially game-changing architectural and algorithmic innovations.

Deepseek has delivered a series of impressive technical breakthroughs. Before R1-Lite-Preview, there had been a longer track record of wins: architectural improvements like multi-head latent attention (MLA) and sparse mixture-of-experts (DeepseekMoE) had reduced inference costs so much as to trigger a price war among Chinese developers. Meanwhile, Deepseek’s coding model trained on these architectures outperformed open weights rivals like July’s GPT4-Turbo.

As a first step to understanding what’s in the water at Deepseek, we’ve translated a rare, in-depth interview with CEO Liang Wenfeng, originally published this past July on a 36Kr sub-brand. It contains some deep insights into:

• How DeepSeek’s ambitions for AGI flow through their research strategy

• Why it views open source as the dominant strategy and why it ignited a price war

• How he hires and organizes researchers to leverage young domestic talent far better than other labs that have splurged on returnees

• Why Chinese firms settle for copying and commercialization instead of “hardcore innovation” and how Liang hopes Deepseek will ignite more “hardcore innovation” across the Chinese economy.

Uncovering DeepSeek: The Ultimate Tale of Chinese Tech Idealism

Wechat, Archive link. Text | Lily Yu 于丽丽. Editor | Liu Jing 刘旌.

Of China’s seven large-model startups, DeepSeek has been the most discreet — yet it consistently manages to be memorable in unexpected ways.

A year ago, this unexpectedness came from its backing by High-Flyer 幻方, a quantitative hedge fund powerhouse, making it the only non-big tech giant with a reserve of 10,000 A100 chips. A year later, it became known as the catalyst for China’s AI model price war. A year later, it became known as the catalyst for China’s AI model price war.

In May, amid continuous AI developments, DeepSeek suddenly rose to prominence. The reason was that they released an open-source model called DeepSeek V2, which offered an unprecedented price/performance ratio: inference costs were reduced to only 1 RMB per million tokens, which is about one-seventh of the cost of Llama3 70B and one-seventieth of the cost of GPT-4 Turbo.

DeepSeek was quickly dubbed the “Pinduoduo of AI,” and other major tech giants such as ByteDance, Tencent, Baidu, and Alibaba couldn’t hold back, cutting their prices one after another. A price war for large models in China was imminent.

This diffuse smoke of war actually concealed one fact: unlike many big companies burning money on subsidies, DeepSeek is profitable.

​​This success stems from DeepSeek’s comprehensive innovation in model architecture. They proposed a novel MLA (multi-head latent attention) architecture that reduces memory usage to 5-13% of the commonly used MHA architecture. Additionally, their original DeepSeekMoESparse structure minimized computational costs, ultimately leading to reduced overall costs.

In Silicon Valley, DeepSeek is known as “the mysterious force from the East” 来自东方的神秘力量. SemiAnalysis’s chief analyst believes the DeepSeek V2 paper “may be the best one of the year.” Former OpenAI employee Andrew Carr found the paper “full of amazing wisdom” 充满惊人智慧, and applied its training setup to his own models. And Jack Clark, former policy head at OpenAI and co-founder of Anthropic, believes DeepSeek “hired a group of unfathomable geniuses” 雇佣了一批高深莫测的奇才, adding that large models made in China “will be as much of a force to be reckoned with as drones and electric cars” 将和无人机、电动汽车一样，成为不容忽视的力量.

In the AI ​​wave — where the story is largely driven by Silicon Valley — this is a rare occurrence. Several industry insiders told us that this strong response stems from innovation at the architectural level, a rare attempt by domestic large model companies and even global open-source large-scale models. One AI researcher said that the Attention architecture has hardly been successfully modified, let alone validated on a large scale, in the years since it was proposed. “It’s an idea that would be shut down at the decision-making stage because most people lack confidence” 这甚至是一个做决策时就会被掐断的念头，因为大部分人都缺乏信心.

On the other hand, large domestic models have rarely dabbled in innovation at the architectural level before, partly due to a prevailing belief that Americans excel at 0-to-1 technical innovation, while Chinese excel at 1-to-10 application innovation. Moreover, this kind of behavior is very unprofitable — after all, a new generation of models will inevitably emerge after a few months, so Chinese companies need only follow along and focus on downstream applications. Innovating the model architecture means that there is no path to follow, meaning multiple failures and substantial time and economic costs.

DeepSeek is clearly going against the grain. Amid the clamor that large-model technology is bound to converge and following is a smarter shortcut, DeepSeek values the learning accumulated through “detours” 弯路, and believes that Chinese large-model entrepreneurs can join the global technological innovation stream beyond just application innovation.

Many of DeepSeek’s choices differ from the norm. Until now, among the seven major Chinese large-model startups, it’s the only one that has given up the “want it all” 既要又要 approach, so far focusing on only research and technology, without the toC applications. It’s also the only one that hasn’t fully considered commercialization, firmly choosing the open-source route without even raising capital. While these choices often leave it in obscurity, DeepSeek frequently gains organic user promotion within the community.

How did DeepSeek achieve this all? We interviewed DeepSeek’s seldom-seen founder, Liang Wenfeng 梁文锋, to find out.

The post-80s founder, who has been working behind the scenes on technology since the High-Flyer era, continues his low-key style in the DeepSeek era — “reading papers, writing code, and participating in group discussions” 看论文，写代码，参与小组讨论 every day, just like every other researcher does.

And unlike many quant fund founders — who have overseas hedge-fund experience and physics or mathematics degrees — Liang Wenfeng has always maintained a local background: in his early years, he studied artificial intelligence at Zhejiang University’s Department of Electrical Engineering.

Multiple industry insiders and DeepSeek researchers told us that Liang Wenfeng is a very rare person in China’s AI industry — someone who has “both strong infra engineering and modeling capabilities, as well as the ability to mobilize resources” he “can make accurate, high-level judgments, while also remaining stronger than first-line researchers in the details”. He has a “terrifying ability to learn”, and at the same time, he is “not at all like a boss and much more like a geek.”

This is a particularly rare interview. Here, this technological idealist provides a voice that is especially scarce in China’s tech world: he is one of the few who puts “right and wrong” before “profits and losses” 把“是非观”置于“利害观”之前, who reminds us to see the inertia of the times, and who puts “original innovation” 原创式创新 at the top of the agenda.

A year ago, when DeepSeek first came off the market, we interviewed Liang Wenfeng: “Crazy High-Flyer: A Stealth AI Giant’s Road to Large Models” 疯狂的幻方：一家隐形AI巨头的大模型之路. If the phrase “be insanely ambitious and insanely sincere” 务必要疯狂地怀抱雄心，且还要疯狂地真诚 was merely a beautiful slogan back then, a year later, it has become action.

Part 1: How was the first shot of the price war fired?

Waves: After DeepSeek V2’s release, it quickly triggered a fierce price war in the large-model market. Some say you’ve become the industry’s catfish.

Liang Wenfeng: We didn’t mean to become a catfish — we just accidentally became a catfish. [Translator’s note: This is likely a reference to Wong Kar-wai’s new tv show 王家卫 “Blossoms Shanghai” 繁花, where catfish are symbolic of market disruptors due to their cannibalistic nature.]

Waves: Was this outcome a surprise to you?

Liang Wenfeng: Very surprising. We didn’t expect pricing to be so sensitive to everyone. We were just doing things at our own pace and then accounted for and set the price. Our principle is that we don’t subsidize nor make exorbitant profits. This price point gives us just a small profit margin above costs.

Waves: Zhipu AI 智谱AI followed suit five days later, followed by ByteDance, Alibaba, Baidu, Tencent, and other big players.

Liang Wenfeng: Zhipu AI reduced the price of an entry-level product, while their models comparable to ours remained expensive. ByteDance was truly the first to follow, reducing its flagship model to match our price, which then triggered other tech giants to cut prices. Since big companies’ model costs are much higher than ours, we never expected anyone would do this at a loss, but it eventually turned into the familiar subsidy-burning logic of the internet era.

Waves: From the outside, price cuts look a lot like bids for users, which is usually the case in internet-era price wars.

Liang Wenfeng: Poaching users is not our main purpose. We cut prices because, on the one hand, our costs decreased while exploring next-generation model architectures, and on the other hand, we also feel that both APIs and AI should be accessible and affordable to everyone.

Waves: Before this, most Chinese companies would directly copy the current generation’s Llama architecture for applications. Why did you start from the model structure?

Liang Wenfeng: If the goal is to make applications, using the Llama structure for quick product deployment is reasonable. But our destination is AGI, which means we need to study new model structures to realize stronger model capability with limited resources. This is one of the fundamental research areas needed for scaling up to larger models. And beyond model structure, we’ve done extensive research in other areas, including data construction and making models more human-like — which are all reflected in the models we released. In addition, Llama’s structure, in terms of training efficiency and inference cost, is estimated to have a two-generation gap behind international frontier levels in training efficiency and inference costs.

Waves: Where does this generation gap mainly come from?

Liang Wenfeng: First of all, there’s a training efficiency gap. We estimate that compared to the best international levels, China’s best capabilities might have a twofold gap in model structure and training dynamics — meaning we have to consume twice the computing power to achieve the same results. In addition, there may also be a twofold gap in data efficiency, that is, we have to consume twice the training data and computing power to achieve the same results. Combined, that’s four times more computing power needed. What we’re trying to do is to keep closing these gaps.

Waves: Most Chinese companies choose to have both models and applications. Why has DeepSeek chosen to focus on only research and exploration?

Liang Wenfeng: Because we believe the most important thing now is to participate in the global innovation wave. For many years, Chinese companies are used to others doing technological innovation, while we focused on application monetization — but this isn’t inevitable. In this wave, our starting point is not to take advantage of the opportunity to make a quick profit, but rather to reach the technical frontier and drive the development of the entire ecosystem.

Waves: The Internet and mobile Internet eras left most people with the belief that the United States excels at technological innovation, while China excels at making applications.

Liang Wenfeng: We believe that as the economy develops, China should gradually become a contributor instead of freeriding. In the past 30+ years of the IT wave, we basically didn’t participate in real technological innovation. We’re used to Moore’s Law falling out of the sky, lying at home waiting 18 months for better hardware and software to emerge. That’s how the Scaling Law is being treated.

But in fact, this is something that has been created through the tireless efforts of generations of Western-led tech communities. It’s just because we weren’t previously involved in this process that we’ve ignored its existence.

Part 2: The Real Gap Isn’t One or Two Years. It’s Between Original Innovation and Imitation.

Waves: Why did DeepSeek V2 surprise so many people in Silicon Valley?

Liang Wenfeng: Among the numerous innovations happening daily in the United States, this is quite ordinary. They were surprised because it was a Chinese company joining their game as an innovation contributor. After all, most Chinese companies are used to following, not innovating.

Waves: But choosing to innovate in the Chinese context is a very extravagant decision. Large models are a heavy investment game, and not all companies have the capital to solely research and innovate instead of thinking about commercialization first.

Liang Wenfeng: The cost of innovation is definitely not low, and past tendencies toward indiscriminate borrowing were also related to China’s previous conditions. But now you see, whether it’s China’s economic scale, or the profits of giants like ByteDance and Tencent — none of it is low by global standards. What we lack in innovation is definitely not capital, but a lack of confidence and knowledge of how to organize high-density talent for effective innovation.

Waves: Why do Chinese companies — including the huge tech giants — default to rapid commercialization as their #1 priority?

Liang Wenfeng: In the past 30 years, we’ve emphasized only making money while neglecting innovation. Innovation isn’t entirely business-driven; it also requires curiosity and a desire to create. We’re just constrained by old habits, but this is tied to a particular economic phase.

Waves: But you’re ultimately a business organization, not a public-interest research institution — so where do you build your moat when you choose to innovate and then open source your innovations? Won’t the MLA architecture you released in May be quickly copied by others?

Liang Wenfeng: In the face of disruptive technologies, moats created by closed source are temporary. Even OpenAI’s closed source approach can’t prevent others from catching up. So we anchor our value in our team — our colleagues grow through this process, accumulate know-how, and form an organization and culture capable of innovation. That’s our moat.

Open source, publishing papers, in fact, do not cost us anything. For technical talent, having others follow your innovation gives a great sense of accomplishment. In fact, open source is more of a cultural behavior than a commercial one, and contributing to it earns us respect. There is also a cultural attraction for a company to do this.

Waves: What do you think of those who believe in the market, like [GSR Ventures’[ Zhu Xiaohu 朱啸虎?

Liang Wenfeng: Zhu Xiaohu is logically consistent, but his style of play is more suitable for fast money-making companies. And if you look at America’s most profitable companies, they’re all high-tech companies that accumulated deep technical foundations before making major breakthroughs.

Waves: But when it comes to large models, pure technical leadership rarely forms an absolute advantage. What bigger thing are you betting on?

Liang Wenfeng: What we see is that Chinese AI can’t be in the position of following forever. We often say that there is a gap of one or two years between Chinese AI and the United States, but the real gap is the difference between originality and imitation. If this doesn’t change, China will always be only a follower — so some exploration is inescapable.

Nvidia’s leadership isn’t just the effort of one company, but the result of the entire Western technical community and industry working together. They see the next generation of technology trends and have a roadmap in hand. Chinese AI development needs such an ecosystem. Many domestic chip developments struggle because they lack supporting technical communities and have only second-hand information. China inevitably needs people to stand at the technical frontier.

Part 3: More Investments Do Not Equal More Innovation

Waves: DeepSeek, right now, has a kind of idealistic aura reminiscent of the early days of OpenAI, and it’s open source. Will you change to closed source later on? Both OpenAI and Mistral moved from open-source to closed-source.

Liang Wenfeng: We will not change to closed source. We believe having a strong technical ecosystem first is more important.

Waves: Do you have a financing plan? I’ve seen media reports saying that High-Flyer plans to spin off DeepSeek for an IPO. AI startups in Silicon Valley inevitably end up binding themselves to major firms.

Liang Wenfeng: We do not have financing plans in the short term. Money has never been the problem for us; bans on shipments of advanced chips are the problem.

Waves: Many people believe that developing AGI and quantitative finance are completely different endeavors. Quantitative finance can be pursued quietly, but AGI may require a high-profile and bold approach, forming alliances to amplify your investments.

Liang Wenfeng: More investments do not equal more innovation. Otherwise, big firms would’ve monopolized all innovation already.

Waves: Are you not focusing on applications right now because you lack the operational expertise?

Liang Wenfeng: We believe the current stage is a period of explosive growth in technological innovation, not in applications. In the long run, we hope to create an ecosystem where the industry directly utilizes our technology and outputs. Our focus will remain on foundational models and cutting-edge innovation, while other companies can build B2B and B2C businesses based on DeepSeek’s foundation. If a complete industry value chain can be established, there’s no need for us to develop applications ourselves. Of course, if needed, nothing stops us from working on applications, but research and technological innovation will always be our top priority.

Waves: But when customers are choosing APIs, why should they choose DeepSeek over offerings from bigger firms?

Liang Wenfeng: The future world is likely to be one of specialized division of labor. Foundational large models require continuous innovation, and large companies have limits on their capabilities, which may not necessarily make them the best fit.

Waves: But can technology itself really create a significant gap? You’ve also mentioned that there are no absolute technological secrets.

Liang Wenfeng: There are no secrets in technology, but replication requires time and cost. Nvidia’s graphics cards, theoretically, have no technological secrets and are easy to replicate. However, building a team from scratch and catching up with the next generation of technology takes time, so the actual moat remains quite wide.

Waves: Once DeepSeek lowered its prices, ByteDance followed suit, which shows that they feel a certain level of threat. How do you view new approaches to competition between startups and big firms?

Liang Wenfeng: Honestly, we don’t really care, because it was just something we did along the way. Providing cloud services isn’t our main goal. Our ultimate goal is still to achieve AGI.

Right now I don’t see any new approaches, but big firms do not have a clear upper hand. Big firms have existing customers, but their cash-flow businesses are also their burden, and this makes them vulnerable to disruption at any time.

Waves: What do you see as the end game of the six other large-model startups?

Liang Wenfeng: Two or three may survive. All of them are in the “burning-money” phase right now, so those with a clear self-positioning and better refinement of operations have a higher chance of making it. Other companies might undergo significant transformations. Things of value won’t simply disappear but will instead take on a different form.

Waves: High-Flyer’s approach to competition has been described as “impervious,” as it pays little attention to horizontal competition. What’s your starting point when it comes to thinking about competition?

Liang Wenfeng: What I often think about is whether something can improve the efficiency of society’s operations, and whether you can find a point of strength within its industrial chain. As long as the ultimate goal is to make society more efficient, it’s valid. Many things in between are just temporary phases, and overly focusing on them can lead to confusion.

Part 4: A group of young people doing “inscrutable” work

Waves: Jack Clark, former policy director at OpenAI and co-founder of Anthropic, said that DeepSeek hired “inscrutable wizards.” What kind of people are behind DeepSeek V2?

Liang Wenfeng: There are no wizards. We are mostly fresh graduates from top universities, PhD candidates in their fourth or fifth year, and some young people who graduated just a few years ago.

Waves: Many LLM companies are obsessed with recruiting talents from overseas, and it’s often said that the top 50 talents in this field might not even be working for Chinese companies. Where are your team members from?

Liang Wenfeng: The team behind the V2 model doesn’t include anyone returning to China from overseas — they are all local. The top 50 experts might not be in China, but perhaps we can train such talents ourselves.

Waves: How did this MLA innovation come about? I heard the idea originated from the personal interest of a young researcher?

Liang Wenfeng: After summarizing some mainstream evolutionary trends of the attention mechanism, he just thought to design an alternative. However, turning the idea into reality was a lengthy process. We formed a team specifically for this and spent months getting it to work. [Jordan: really reminiscent of how Alec Radford’s early contribution to the GPT series and speaks to the broader thesis we’ve argued in the past on ChinaTalk that algorithmic innovation is fundamentally different from pushing the technological frontier in something like semiconductor fabrication. Instead of needing a PhD and years of industry experience to really be useful, you can push the frontier by being a really sharp and hungry 20something (of which China has many!). Dwarkesh’s interview with OpenAI Sholto Douglass and Anthropic’s Trenton Bricken illustrates this dynamic well. Dwarkesh opens with the ine “Noam Brown, who wrote the Diplomacy paper, said this about Sholto: “he's only been in the field for 1.5 years, but people in AI know that he was one of the most important people behind Gemini's success.”]

Waves: The emergence of such divergent thinking seems closely related to your innovation-driven organizational structure. Back in the High-Flyer era, your team rarely assigned goals or tasks from the top down. But AGI involves frontier exploration with much uncertainty — has that led to more management intervention?

Liang Wenfeng: DeepSeek is still entirely bottom-up. We generally don’t predefine roles; instead, the division of labor occurs naturally. Everyone has their own unique journey, and they bring ideas with them, so there’s no need to push anyone. While we explore, if someone sees a problem, they will naturally discuss it with someone else. However, if an idea shows potential, we do allocate resources top-down.

Waves: I heard that DeepSeek is very flexible in mobilizing resources like GPUs and people.

Liang Wenfeng: Anyone on the team can access GPUs or people at any time. If someone has an idea, they can access the training cluster cards anytime without approval. Similarly, since we don’t have hierarchies or separate departments, people can collaborate across teams, as long as there’s mutual interest.

Waves: Such a loose management style relies on having highly self-driven people. I heard you excel at identifying exceptional talent through non-traditional evaluation criteria.

Liang Wenfeng: Our hiring standard has always been passion and curiosity. Many of our team members have unusual experiences, and that is very interesting. Their desire to do research often comes before making money.

Waves: Transformers was born at Google’s AI Lab, and ChatGPT at OpenAI. How do you compare the value of innovations at big companies’ AI labs versus startups?

Liang Wenfeng: Google’s AI Lab, OpenAI, and even Chinese tech companies’ AI labs are all immensely valuable. The fact that OpenAI succeeded was partly due to a few historical coincidences.

Waves: So, is innovation largely a matter of luck? I noticed that the middle row of meeting rooms in your office has doors on both sides that anyone can open. Your colleagues said that this design leaves room for serendipity. The creation of transformers involved someone overhearing a discussion and joining, ultimately turning it into a general framework.

Liang Wenfeng: I believe innovation starts with believing. Why is Silicon Valley so innovative? Because they dare to do things. When ChatGPT came out, the tech community in China lacked confidence in frontier innovation. From investors to big tech, they all thought that the gap was too big and opted to focus on applications instead. But innovation starts with confidence, which we often see more from young people.

Waves: But you don’t fundraise or even speak to the public, so your visibility is lower than those companies actively fundraising. How do you ensure DeepSeek remains the top choice for those working on LLMs?

Liang Wenfeng: Because we’re tackling the hardest problems. Top talents are most drawn to solving the world’s toughest challenges. In fact, top talents in China are underestimated because there’s so little hardcore innovation happening at the societal level, leaving them unrecognized. We’re addressing the hardest problems, which makes us inherently attractive to them.

Waves: When OpenAI’s latest release didn’t bring us GPT5, many people feel that this indicates technological progress is slowing and are starting to question the Scaling Law. What do you think?

Liang Wenfeng: We’re relatively optimistic. Our industry as a whole seems to be meeting expectations. OpenAI is not a god (OpenAI不是神), they won’t necessarily always be at the forefront.

Waves: How long until AGI is realized? Before releasing DeepSeek V2, you had models for math and code generation and also switched from dense models to Mixture of Experts. What are the key points on your AGI roadmap?

Liang Wenfeng: It could be two, five, or ten years–in any case, it will happen in our lifetimes. There’s no unified opinion on a roadmap even within our company. That said, we’ve taken real bets on three directions. First is mathematics and code, second multimodality, and third natural language itself.

Mathematics and code are natural AGI testing grounds, somewhat like Go. They’re closed, verifiable systems where high levels of intelligence can be self-taught. Multimodality and engagement with the real human world, on the other hand, might also be a requirement for AGI. We remain open to different possibilities.

Waves: What do you think is the end game for large models?

Liang Wenfeng: There will be specialized companies providing foundation models and services, achieving extensive specialization in every node of the supply chain. More people will build on top of all of this to meet society’s diverse needs.

Part 5: All the methods are products of a previous generation

Waves: Over the past year, there have been many changes in China's large model startups. For example, Wang Huiwen [co-founder of RenRen, a facebook clone, and Meituan, a food delivery company], who was very active at the beginning of last year, withdrew midway, and companies that joined later began to show differentiation.

Liang Wenfeng: Wang Huiwen bore all the losses himself, allowing others to withdraw unscathed. He made a choice that was worst for himself but good for everyone else, so he's very decent in his conduct - this is something I really admire. [Wang Huiyuan founded foundation model company 光年之外 Lightyear only to quickly fold it back into Meituan. For more on Meituan and AI, see this recent 36Kr feature].

Waves: Where are you focusing most of your energy now?

Liang Wenfeng: My main energy is focused on researching the next generation of large models. There are still many unsolved problems.

Waves: Other large model startups are insisting on pursuing both [technology and commercialization], after all, technology won't bring permanent leadership as it's also important to capitalize on a window of opportunity to translate technological advantages into products. Is DeepSeek daring to focus on model research because its model capabilities aren't sufficient yet?

Liang Wenfeng: All these business patterns are products of the previous generation and may not hold true in the future. Using Internet business logic to discuss future AI profit models is like discussing General Electric and Coca-Cola when Pony Ma was starting his business. It’s a pointless exercise (刻舟求剑).

Waves: In the past, your quant fund High-Flyer had a strong foundation in technology and innovation, and its growth was relatively smooth. Is this the reason for your optimism?

Liang Wenfeng: In some ways, High-Flyer strengthened our confidence in technology-driven innovation, but it wasn't all smooth sailing. We went through a long accumulation process. What outsiders see is the part of High-Flyer after 2015, but in fact, we've been at it for 16 years.

Waves: Returning to the topic of innovation. Now that the economy is starting to decline and capital is no longer as loose as it was, will this suppress basic research?

Liang Wenfeng: I don't necessarily think so. The adjustment of China's industrial structure will necessarily rely more on hardcore technological innovation. When people realize that making quick money in the past was likely due to lucky windows, they'll be more willing to humble themselves and engage in genuine innovation.

An Yong: So you're optimistic about this as well?

Liang Wenfeng: I grew up in the 1980s in a fifth-tier city in Guangdong. My father was a primary school teacher. In the 1990s, there were many opportunities to make money in Guangdong. At that time, many parents came to my home; basically, they thought studying was useless. But looking back now, they’ve all changed their views. Because making money isn't easy anymore—even the opportunity to drive a taxi might be gone soon. It’s only taken one generation.

In the future, hardcore innovation will become increasingly common. It’s not easy to understand right now, because society as a whole needs to be educated on this point. Once society allows people dedicated to hardcore innovation to achieve fame and fortune, then our collective mindset will adapt. We just need some examples and a process

Our article was originally published in Asterisk Magazine. Today, ChinaTalk is rereleasing it alongside exclusive commentary from Jason Matheny, CEO of RAND at the end of the post.

RAND’s halcyon days lasted two decades, during which the corporation produced some of the most influential developments in science and American foreign policy.

So how did it become just another think tank?

Between 1945 and 1960, RAND operated as the world’s most productive research organization. Initially envisioned as a research arm of the Air Force, RAND made century-defining breakthroughs both in basic science and applied strategic analysis. Its members helped define U.S. nuclear strategy, conceptualized satellites, pioneered systems analysis, and developed the earliest reports on defense economics. They also revolutionized much of STEM: RAND scholars developed the basics of game theory, linear programming, and Monte Carlo methods. They helped conceptualize generalized artificial intelligence, developed the basics for packet switching (which enables data transmission across networks), and built one of the world’s first computers.

Today, RAND remains a successful think tank — by some metrics, among the world’s best.¹ In 2022, it brought in over $350 million in revenue, and large proportions still come from contracts with the US military. Its graduate school is among the largest for public policy in America. 

But RAND’s modern achievements don’t capture the same fundamental policy mindshare as they once did. Its military reports may remain influential, but they hold much less of their early sway, as when they forced the U.S. Air Force to rethink several crucial assumptions in defense policy. And RAND’s fundamental research programs in science and technology have mostly stopped. Gone are the days when one could look to U.S. foreign policy or fundamental scientific breakthroughs and trace their development directly back to RAND. 

How was magic made in Santa Monica? And why did it stop? 

The Roots of RAND

Economists, physicists, and statisticians — civilian scientists to that point not traditionally valued by the military — first proved their utility in the late stages of World War II operational planning. American bomber units needed to improve their efficiency over long distances in the Pacific theater. The scientists hired by the Army Air Force proposed what at the time seemed a radical solution: removing the B-29 bomber’s armor to reduce weight and increase speed. This ran counter to USAAF doctrine, which assumed that an unprotected plane would be vulnerable to Japanese air attacks. The doctrine proved incorrect. The increased speed not only led to greater efficiency, it also led to more U.S. planes returning safely from missions, as Japanese planes and air defense systems were unable to keep up.2 Civilian scientists were suddenly in demand. By the end of the war, all USAAF units had built out their own operations research departments to optimize battle strategy. When the war ended, the question turned to how to retain the scientific brain trust it had helped to assemble. 

General Henry “Hap” Arnold, who had led the Army Air Force’s expansion into the most formidable air force in the world, had started to consider this question long before the war had ended. He found an answer in September 1945, when Franklin Collbohm, a former test pilot and executive at Douglas Aircraft, walked into Arnold’s office with a plan: a military-focused think tank staffed by the sharpest civilian scientists. Collbohm did not have to finish describing his idea before Arnold jumped and agreed. Project RAND was born.

Arnold, along with General Curtis LeMay — famous for his “strategic bombing” of Japan, which killed hundreds of thousands of civilians — scrounged up $10 million from unspent war funds to provide the project’s seed money, which was soon supplemented with a grant from the Ford Foundation. This put RAND into a privileged position for a research organization: stably funded. 

On top of that financial stability, RAND built what would become one of its greatest organizational strengths: a legendarily effective culture, and a workforce to match it.

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Internal Culture and Talent

In an internal memo, Bruno Augestein, a mathematician and physicist whose research on ballistic missiles helped usher in the missile age, highlighted a set of factors that catalyzed RAND’s early success. In short: RAND had the best and brightest people working with the best computing resources in an environment that celebrated excellence, welcomed individual quirks, and dispensed with micromanagement and red tape.

Early RAND leadership was, above all else, committed to bringing in top talent and jealously guarded the sort of intellectual independence to which their academic hires were accustomed. Taking the mathematics department as an example, RAND hired John Williams, Ted Harris, and Ed Quade to run it. While these were accomplished mathematicians in their own right, these three were also able to attract superlative talents to work under and around them. As Alex Abella writes in Soldiers of Reason, his history of RAND, “No test for ideological correctness was given to join, but then none was needed. The nation’s best and brightest joining RAND knew what they were signing on for, and readily accepted the vision of a rational world — America and its Western allies — engaged in a life-and-death struggle with the forces of darkness: the USSR.” 

As the Cold War intensified, the mission became the sell. The aim of RAND, as the historian David Hounshell has it, “was nothing short of the salvation of the human race.”3 The researchers attracted to that project believed that the only environment in which that aim could be realized was independent of the Air Force, its conventional wisdom, and — in particular — its conventional disciplinary boundaries

RAND’s earliest research aligned with the USAF’s (the Army Air Force had become its own service branch in 1947) initial vision: research in the hard sciences to attack problems like satellite launches and nuclear-powered jets.4 However, the mathematician John Davis Williams, Collbohm’s fifth hire, was convinced that RAND needed a wider breadth of disciplines to support the Air Force’s strategic thinking. He made the case to General LeMay, who supervised RAND, that the project needed “every facet of human knowledge to apply to problems.”5 To that end, he argued for recruiting economists, political scientists, and every other kind of social scientist. LeMay, once convinced, implored Williams to hire whoever it took to get the analysis right.

And so they did. RAND’s leadership invested heavily in recruiting the best established and emerging talent in academia. An invitation-only conference organized by Williams in New York in 1947 brought together top political scientists (Bernard Brodie), anthropologists (Margaret Mead), economists (Charles Hitch), sociologists (Hans Speier), and even a screenwriter (Leo Rosten). The promise of influence, exciting interdisciplinary research, and complete intellectual freedom drew many of the attendees to sign up.

Within two years, RAND had assembled 200 of America’s leading academics. The top end of RAND talent was (and would become) full of past (and future) Nobel winners, and Williams worked around many constraints — and eccentricities — to bring them on. For instance, RAND signed a contract with John von Neumann to produce a general theory of war, to be completed during a small slice of his time: that spent shaving. For his shaving thoughts, von Neumann received $200 a month, an average salary at the time. 

Beyond the biggest names, RAND was “deliberate, vigorous, and proactive” in recruiting the “first-rate and youthful staff” that made up most of its workforce. The average age of staff in 1950 was under 30.6 Competition between them helped drive the culture of excellence. Essays and working papers were passed around for comments, which were copious — and combative. New ideas had to pass “murder boards.” And the competition spilled into recreational life: Employees held tennis tournaments and boating competitions. James Drake, an aeronautical engineer, invented the sport of windsurfing. The wives of RAND employees — who were, with a few notable exceptions, almost all male — even competed through a cooking club where they tried to make the most "exotic" recipes.

After bringing in such extraordinary talent, RAND’s leadership trusted them to largely self-organize. Department heads were given a budget and were free to spend it as they felt fit. They had control over personnel decisions, which allowed them the flexibility to attract and afford top talent. As a self-styled “university without students,” RAND researchers were affiliated with departments with clear disciplinary boundaries, which facilitated the movement of researchers between RAND and academia. But in practice, both departments and projects were organized along interdisciplinary lines. 

The mathematics department brought on an anthropologist. The aeronautics department hired an MD. This hiring strategy paid off in surprising ways. For instance, while modeling the flow of drugs in the bloodstream, a group of mathematicians stumbled upon a technique to solve a certain class of differential equations that came to be used in understanding the trajectory of intercontinental ballistic missiles.

Finding an Institutional Footing 

RAND was at the forefront of a postwar explosion in federal funding for science. Hundreds of millions of dollars poured into universities, think tanks, and industrial R&D labs. Almost all of it was directed toward one purpose: maintaining military superiority over the Soviet Union. In 1950, over 90% of the federal research budget came from just two agencies: the Atomic Energy Commission and the Department of Defense.7 Significant portions of this funding went toward basic research with no immediate military applications.8 Vannevar Bush, the influential head of the war-era Office of Scientific Research and Development, had argued for this approach in his 1945 book Science, the Endless Frontier: Freeing up scientists to follow their own research interests would inevitably lead to more innovation and ensure American technological dominance. Bush’s was not the only, or even the dominant, view of how postwar science should be organized — most science funding still went toward applied research — but his views helped inform the organization of a growing number of research institutions.9 No organization embodied this model more than RAND. Air Force contracts were the financial backbone of the organization. They provided the money required to run RAND, while profits were used to fund basic research. In the 1950s, USAF contracts comprised 56% of RAND’s work, while other sponsors made up just 7%.10 That left more than a third of RAND’s capacity open to pursue its own agenda in basic research. Many of the developments made there would be used in their applied research, making it stronger — and more profitable — in the process. This flywheel would become critical to RAND’s success. 

Not all of these developments were successful, especially at first. RAND’s early research efforts in systems analysis — an ambitious pursuit in applying mathematical modeling that RANDites were optimistic could produce a holistic “science of warfare” — were flops. The first project, which aimed to optimize a strategic bombing plan on the Soviet Union, used linear programming, state-of-the-art computing, and featured no fewer than 400,000 different configurations of bombs and bombers. It proved of little use to war planners. Its assumptions fell prey to the “specification problem:” trying to optimize one thing, in this case, calculating the most damage for the least cost led to misleading and simplistic conclusions.11  

But RAND would soon find its footing, and a follow up to this work became a classic of the age. The 1954 paper Selection and Use of Strategic Air Bases proved the value of RAND’s interdisciplinary approach — though its conclusions were at first controversial. Up to the 1950s, there had been little analysis of how the Strategic Air Command, responsible for the United States’s long range bomber and nuclear deterrent forces, should use its Air Force bases. At the time, the SAC had 32 bases across Europe and Asia. The study, led by political scientist Albert Wohlstetter, found that the SAC was dangerously vulnerable to a surprise Soviet attack. The SAC’s radar defenses wouldn’t be able to detect low-flying Soviet bombers, which could reduce American bombers to ash — and thereby neutralize any threat of retaliation — before the Americans had a chance to react. Wohlstetter’s study recommended that the SAC keep its bombers in the U.S., dispersed at several locations to avoid concentration at any place. 

LeMay, RAND’s original benefactor and commander of the SAC, resisted Wohlstetter’s conclusions. He worried the plan would reduce his control over the country’s nuclear fleet: With the SAC based in the U.S., LeMay would have to cede some authority to the rest of the U.S. Air Force. He pushed against it many times, proposing several alternatives in which the SAC kept control over the bombers, but no plan fully addressed the vulnerabilities identified by the report. 

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Undaunted — and sure of his logic — Wohlstetter pushed his conclusions even further. He proposed a fail-safe mechanism, where nuclear bombers would have to receive confirmation of their attack from multiple checkpoints along the way, to prevent rogue or mistaken orders from being followed. Wohlstetter went around LeMay, to Defense Secretary Charles Wilson and General Nathan Twining, chairman of the Joint Chiefs of Staff, who ultimately accepted the study’s recommendations in full. It took over two decades, but they proved their value in 1980 when a faulty chip erroneously warned of an impending Soviet strike. While no order for a retaliatory attack was issued, had there been one, the fail-safe mechanism would have prevented the bombers from actually attacking the USSR. Selection and Use of Strategic Air Bases was a triumph for RAND. Not only had they provided correct advice to the USAF, they had also proved their independence from the institution’s internal politics.

And the flywheel would prove its value many times over. RAND’s basic research helped drive the development and strategy of ICBMs, the launch of the first meteorological satellite, and, later, on cost reductions in ICBM launch systems.

Diversification and Decline

RAND’s conclusions ran counter to USAF doctrine several times — and each time RAND fought to maintain its independence. When the USAF commissioned RAND to study the Navy’s Polaris program — in order to show that it was inferior to the Air Force’s bombers for nuclear weapon delivery — RAND found that the Polaris missiles were, in fact, superior. The same happened with another study, which challenged the effectiveness of the B-70 bomber in 1959.

Over time, however, these tensions added friction to the relationship. To make matters worse, between 1955 and 1960, the USAF’s budget declined in both absolute terms, and relative to the rest of the defense community. In 1959, the Air Force froze RAND’s budget, presumably due to the budget cuts — and their disputes with RAND. 

This situation was not unique to the USAF, or to RAND. As the 1950s rolled into the ’60s, scientists at civilian institutions increasingly moved to disentangle themselves from their military benefactors. Throughout the decade, DOD funding for basic research would only continue to decline.12  

RAND weathered the transition by successfully seeking out new customers — the AEC, ARPA, the Office of the Comptroller, the Office of the Assistant Secretary of Defense for International Security Affairs (ISA), NASA, the NSF, the NIH, and the Ford Foundation, to name a few. The percent of the outside funding coming from the USAF dropped from 95% when RAND started to 68% in 1959.13 But their success came at a cost: This diversification is what led to RAND losing its edge in producing the cutting edge of policy and applied science.

Funding diversification reshaped both RAND’s culture and output. The increased number of clients made scheduling researchers’ work harder. Each client expected a different standard of work, and the tolerance levels for RAND’s previously freewheeling style varied. The transaction costs of starting a new contract were much higher and the flexible staffing protocols that had worked for the USAF in the 1950s needed to be systematized. The larger organization led to ballooning internal administration expenses.

Along with all of this, RAND’s increased size attracted more political detractors. In 1958, a RAND paper called Strategic Surrender, which examined the historical conditions for surrender, had generated a political firestorm. Politicians were furious with RAND for exploring conditions under which it would be strategic for the U.S. to surrender. Senators weren’t particularly interested in the study itself, but those who wanted to run for president (like Stuart Symington of Missouri) used it as evidence that the Eisenhower administration was weak on defense. 

The Senate even passed a resolution (with an 88–2 margin) prohibiting the use of federal funds for studying U.S. surrender. RAND’s management, realizing that an intentional misinterpretation of their work potentially threatened future funding streams, now had to consider the wider domestic political context of their work. All of these factors changed RAND’s culture from one that encouraged innovation and individuality to one that sapped creativity. 

But the biggest change was yet to come. In 1961, Robert McNamara took over the Department of Defense and brought with him a group of RAND scholars, commonly called the “Whiz Kids.” Their most important long-term contribution to U.S. governance was the Planning-Programming-Budgeting System. PPBS took a Randian approach to resource allocation, namely, modeling the most cost-effective ways to achieve desired outcomes. In 1965, after President Johnson faced criticism for poor targeting of his Great Society spending, he required nearly all executive agencies to adopt PPBS. Many RAND alumni were hired by McNamara and his team to help with the Great Society’s budgeting process. 

In 1965, Henry Loomis, the deputy commissioner on education, approached RAND about conducting research on teaching techniques. Franklin Collbohm, RAND’s founder and then president, declined. He preferred that RAND stay within the realm of military analysis. RAND’s board disagreed and would eventually push Collbohm out of RAND in 1967. The board thought it was time for a change in leadership — and to RAND’s nonmilitary portfolio. 

The entry of a new president, Henry S. Rowen, an economist who had started his career at RAND, cemented this change. By 1972, the last year of Rowen’s tenure, almost half of all RAND projects were related to social science. For better or worse, this eroded RAND’s ability to take on cutting-edge scientific research and development. 

RAND entered domestic policy research with a splash — or, rather, a belly flop. The politics of social policy research were markedly different from working with the DOD. For one, there were substantially more stakeholders — and they were more vocal about voicing their disagreements. One crucial example is when RAND proposed police reforms in New York City, but pressure from the police unions forced them to retract. 

John Lindsay, the Republican mayor of New York, had tasked RAND with improving the New York Police Department, which had recently been implicated in narcotics scams, corruption, and police brutality. The report showed that in less than 5% of the cases in which an officer was charged with a crime or abusing a citizen did the officers receive anything more than a reprimand. The findings were leaked to The New York Times, which added to the impression among the police that RAND was the mayor’s mouthpiece. 

RAND, for the first time, had to face the reality of local politics: a sometimes hostile environment, multiple stakeholders who sometimes acted in bad faith, and none of the free reign that characterized their first decades. RAND’s experience with the police report, and the controversy over the study of surrender, led RAND to be more conservative about the research it put out. And additionally, the focus on policy research crowded out the scientific research. 

For example, beginning in the 1970s, RAND’s applied mathematics research output slowed to a trickle, before stopping altogether in the 1990s. It was replaced by mathematics education policy. The same is true for physics, chemistry, and astronomy. Another emblematic development in the dilution of RAND’s focus was the founding in 1970 of the Pardee RAND Graduate School, the nation’s first Ph.D.-granting program in policy analysis. While the idea of training the next generation in RAND techniques is admirable, RAND in the early years explicitly defined itself as a “university without students.”

RAND is still an impressive organization. It continues to produce successful policy research, which commands the eyes of policymakers in over 82 federal organizations and across dozens of local and even foreign governments. Still, their work today is inarguably less groundbreaking and innovative than it was in the ’50s. This relative decline was partially caused by internal policy choices, and partially by the eventual loss of their initial team of leading scientists. But part of it was also inevitable: We no longer live in an era when branches of the U.S. military can cut massive blank checks to think tanks in the interest of beating the Soviets. The successes of 1950s RAND do come with lessons for modern research organizations — about the importance of talent, the relevance of institutional culture, and the possibilities of intellectual freedom — but the particular conditions that created them can’t be replicated. It is remarkable that they existed at all. 

Modern Magic at RAND

The following commentary comes directly from RAND’s CEO, Jason Matheny.

RAND CEO Jason Matheny here. Your readers may recall from my appearance on your podcast last year that I, too, am a RAND history nerd. There are many great details in your Asterisk article about RAND’s early contributions in the 1950s and ‘60s. Thanks for bringing them to life.

RAND’s contributions in the last five decades have been no less consequential. The world’s challenges are certainly different from the ones RAND researchers confronted in the early years. But it is RAND’s ability to reorient itself toward the biggest challenges that has been our “magic.” We shouldn’t expect or want RAND to look the same as it did during the Cold War. 

I thought your readers would be interested to pick up where your story stops. And since your article focuses on national security, I’ll concentrate my comments there. (That said, there have been just as many breakthroughs in RAND’s social and economic policy analyses over the years.) 

RAND’s security research in the modern era has been forward-looking, has challenged long-held wisdom, and has anticipated once-unthinkable threats. And I’m not saying this only as RAND’s CEO. Before I joined RAND two years ago, I was one of countless people at the White House and elsewhere in government who relied on RAND analysis to make critical decisions. 

Many recent RAND studies will remain classified for years. While their full impact will be assessed with time — much as was the case with RAND’s work in the 1950s and 1960s – they have been among RAND’s most influential. Below are some examples of projects that we can describe here: 

• China: RAND was among the first research organizations to systematically analyze China’s military buildup and make direct comparisons to the U.S. military. 

• Russia: RAND was among the first organizations to identify Russia’s growing military capabilities following its 2008 war in Georgia and the threat these posed to new NATO members in the Baltic states. This work prompted important planning and infrastructure changes that are being used today to support Ukraine. 

• U.S. military power: RAND’s series of overmatch studies transformed policymakers’ understanding the loss of U.S. military superiority in key areas over time. 

• Operating in the Pacific theater: RAND was among the first to highlight the vulnerability of the U.S. military’s forward infrastructure in the Pacific and ways to overcome that vulnerability. 

• Nuclear strategy: RAND’s recent work on nuclear deterrence, including wargames analyzing nuclear-armed regional adversaries, brought about a resurgence of deterrence thinking within the government. 

• B-21: RAND analysis of penetrating versus standoff bomber capabilities led directly to the decision to establish the B-21 program. 

• Military forces: RAND‘s work on military personnel, the ability to develop and sustain the all-volunteer force over time, appropriate pay and benefits for the force, and the vulnerabilities to service members and their families, has been the primary source of analysis for decisionmakers within the Department of Defense and Congress. 

• Drones: RAND’s analysis of small UAVs and swarming options was the first to analyze how a sensor grid can substantially strengthen deterrence in the Asia-Pacific region. Current DoD programs can be traced directly to this pathbreaking analysis. 

• PTSD and TBI: RAND’s work on the invisible wounds of war, PTSD, and traumatic brain injury, was the first careful documentation of psychological and cognitive injuries from modern combat. This work launched a society-wide effort to detect and treat such injuries. 

• Logistics: RAND analysis prompted the revolution in combat logistics in both the Air Force and the Army, emphasizing wartime flexibility and resilience as the organizing principles for supply and maintenance. 

• AI: RAND was early in systematically evaluating how defense organizations could integrate contemporary AI methods based on deep learning, in evaluating large language models, and in assessing threats to model security. 

With rapid developments in emerging technology and an increasingly confrontational PRC government, the world needs RAND’s analysis more than ever. I know that your readers care deeply about these challenges. Those who want to work toward solutions should consider working at RAND or applying to our new master's degree program in national security policy. 

To hear more from Jason, check out the two-hour interview we did last year on ChinaTalk, which was my favorite episode of 2023.

Transcript:

Click to open in Apple Podcasts or Spotify.

Mark Witzke is a China analyst and nonresident scholar at the UC San Diego 21st Century China Center. See more on US-China relations and unexpected connections between the countries like the UFC on his Twitter or Bluesky @mkwitzke. 

As Trump’s return to the White House draws nearer, China watchers are paying close attention to his cabinet picks. One underrated wild card in the relationship might actually be the interests of a sports league once condemned by Republicans as “human cockfighting”. 

This past weekend, President-elect Trump walked out in MSG in New York in a moment of triumph to attend a mixed martial arts (MMA) event. It was his first public appearance since the election and served as a sort of coronation ceremony where popular MMA fighters like Jon Jones and Michael Chandler gave tribute to the new President. 

Formerly a foe of the Republican party due to John McCain’s staunch opposition to the league, the UFC now appears to be a MAGA PR arm. Trump has frequently appeared at UFC events in times of intense political pressure. After January 6th, Trump made one of his first major public appearances at UFC 264. Days after his arrest, he appeared defiantly at UFC 287 with Mike Tyson. Trump used the UFC 302 event to launch his TikTok account, just two days after receiving a guilty verdict in his hush money trial.

Trump’s relationship to the UFC goes all the way back to 2001, when the UFC was relegated to backwater venues and struggled to dispel the notion that it was too dangerous to be legal. At that time, according to sports journalist Karim Zidan, “Donald Trump took a chance on the UFC in and allowed the organization to host two consecutive events at his Atlantic City casino, the Trump Taj Mahal. And the UFC has really been loyal to him ever since then.” At all three of his nominations, Dana White spoke for Trump at the RNC and has helped him make inroads with new media and popular fighters.  

What might Dana White expect in return? For starters, easing visa restrictions on fighters with links to controversial figures like Ramzan Kadyrov. But White, with his global operations, surely has his eye on larger payouts. Prior to the pandemic, the UFC had big plans for China. They held events in Macau in 2012 and 2014 and revved up activity in the mainland a few years later with events held in Beijing, Shanghai, and Shenzhen in 2017, 2018, and 2019. 

While the earlier events focused more on foreign fighters, the 2019 event in Shenzhen was headlined by Hebei native, Zhang Weili, where she became the UFC’s first female Asian champion. Upon her victory she took the mic and spoke with her limited English, "My name is Zhang Weili!...I'm from China. Remember me!" She has since gone on to lose and then regain her champion status, most recently defending her belt at UFC 300 against her countryman, Yan Xiaonan. Chinese state media spoke approvingly of the event and noted the growing interest towards the sport in China. 

Other moves taken by the UFC to grow their market in China included establishing a training center in Shanghai in 2019, inking streaming content distribution deals with Migu (a part of China Mobile), and cultivating talent through its Road to UFC program that gives local fighters the chance to make it to the UFC. The UFC even signed a deal with the Chinese Olympic Committee to help train athletes. In an interview, Kevin Chang, head of UFC Asia, said that China was a priority for the UFC, that they thought carefully about the differences in promoting on Chinese social media platforms versus in the US and they had already gained millions of fans. 

But since the pandemic, there have been no major UFC events in China — an attempt to hold an event in Shanghai at the end of last year was abruptly canceled for no apparent reason. This Saturday, however, the UFC will return to China (Macau) and hold their first event there since 2019, marking its return to a market with immense growth potential. While other companies are trying to figure out how to pull out and decouple, Trump’s favorite sport league will have a continued interest in smooth relations between the US and China. 

This sports exchange may bring to mind the old “ping pong diplomacy” where in the early 1970s, an international exchange of table tennis players helped open the door for a renewal of US-China relations. In a new era for the US and China where the relationship will almost certainly get stormy, could a sports league where people punch each other in the face serve as an unexpected circuit-breaker?

It may seem silly, but so was ping pong diplomacy. Perhaps Chinese officials make an appearance at a US event or push for more mainland events in an attempt to appeal to Trump. Xi Jinping himself has long had a personal interest in sports, with plans to make China a sporting superpower and a desire to make Chinese men more “manly.” See ChinaTalk’s feature on the CCP masculinity crisis.

Dana White and the UFC might not have a particular interest in all the nuts and bolts of Trump’s China policy with regards to tariffs or investment screening, but he certainly would be loath to see total decoupling of US business interests from China. Dana, along with Elon Musk, Jeff Yass, and Howard Lutnick may well serve as the second term’s version of Gary Cohn and Steve Mnuchin.

Tweets of the Week

Evening at Tagonoura, by Kawase Hasui, 1940

Karson Elmgren and Oliver Guest are researchers focused on international AI governance and China. Their full report on Chinese AISI counterparts is available here.

AI Safety Institutes, or AISIs, are one of the most important new structures to emerge in international AI policy over the last year. The US and UK were the first to establish AISIs in October 2023, followed later by the EU, Japan, Singapore, France, and Canada. 

This week, San Francisco is hosting the first conference of the International Network of AI Safety Institutes. The AISIs have thus far signed various bilateral cooperation agreements, but the San Francisco conference will be the first multilateral discussion forum knitting all AISIs together.

However, one country is conspicuously absent from the AISI club: China.

To date, China has not designated an official, national-level AISI, despite its prominent position in AI and apparent ambitions to influence international governance. Nevertheless, as our recent report highlights, there are a number of government-linked Chinese institutions doing analogous work. Looking forward, it still seems plausible that China will establish a single body acting as an official counterpart to AISIs around the globe.

What are AI Safety Institutes?

In general, AI Safety Institutes are government-backed technical institutions that focus on the safety of advanced AI.  

There’s a lot of variation between such organizations — some focus on research while others focus on recommending guidelines, and, naturally, some AISIs are much more well-funded than others. 

This variation makes it difficult to pinpoint exactly what it means to be an AISI. The EU AI Office, for example, has regulatory functions and almost no focus on research — which makes it unlike any other AISI. Yet in practice, it has played the role of an AISI by representing the EU in AISI-specific convenings.

Conducting AI safety evaluations has been a key focus for several AISIs. They are also contributing to safety evaluation as a field by developing and releasing software tooling for the evaluation of AI systems.

More broadly, many AISIs are interested in technical AI safety R&D, standard-setting, and international coordination. To achieve these functions, the official AISIs serve as an anchor for a wide network of government and civil society participants.

Is China even interested in having an AISI? 

Despite frequently calling for the United Nations to serve as the key platform for international AI governance, China has thus far revealed a clear preference for maintaining a seat at the table of Western-led minilateral efforts.

Beijing sent a delegation (led by Ministry of Science & Technology Vice Minister Wu Zhaohui 吴朝晖) to attend the UK AI Safety Summit in Bletchley Park. This was the first time AI-induced catastrophic risks received international attention, and it was during this summit that the US and UK announced the creation of the earliest AISIs. Chinese representatives also attended the follow-up event in Seoul — but they did not sign the joint statement for countries in attendance, which declared a “shared ambition to develop an international network among key partners to accelerate the advancement of the science of AI safety.”

But hesitation hasn’t stopped prominent Chinese AI scientists and policy experts from actively seeking dialogue with international counterparts. At a conference in July 2024, Andrew Yao 姚期智 and Zhang Ya-Qin 张亚勤 even publicly advocated for China to establish its own AISI to participate in the growing network.

(For context, Andrew Yao is the Dean of Tsinghua University’s Institute for Interdisciplinary Information Sciences and arguably China’s most highly respected computer scientist. Zhang Ya-Qin is the former President of Baidu and the dean of the Tsinghua Institute for AI Industry Research).

There have even been some signs that some Chinese officials are similarly concerned about catastrophic risks from AI. Most tellingly, the recent Third Plenum decision included a call to establish “oversight systems” for AI safety in a section focused on large-scale public safety threats like natural disasters. A June 2024 report by the quasi-governmental China Academy of Information and Communications Technology (CAICT) referred to AI as a “sword of Damocles,” and cited Nobel laureate Geoffrey Hinton’s concerns about AI “takeover” to explain the need for an AI evaluation regime. 

Why the hesitation?

Even if there is an appetite for a Chinese AISI, there are a few obstacles standing in the way.

One significant barrier is internecine jockeying over who gets to call the shots on AI safety. Beijing and Shanghai have each recently established local AISI-like bodies, which are already not-so-subtly vying for a promotion to the national level. The newly-established Beijing Institute of AI Safety and Governance hosted the UK AISI for a meeting in October 2024, and even abbreviated its name as “Beijing-AISI.”

Similar maneuvering may be happening within the Chinese party-state system over the location of AISI facilities, the personnel involved, and the goals of a potential Chinese AISI. The variation between existing AISIs could make this jockeying particularly intense, as there is no definite playbook for a Chinese AISI to follow.

There’s also the question of optics. Given China’s own leadership ambitions in AI governance, it’s presumably not the best look to follow a trend established and led by the US and UK. Though the AISI network incorporates non-western countries like Singapore and Kenya, it’s sometimes perceived as an Anglo invention — to the extent that Japan’s AISI is named in English — the body’s official title is ＡＩセーフティ・インスティテュート , AI Sēfuti Insutityūto. (The logo, too, is suspiciously similar to that of UK AISI.)

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Finally, even if China wanted to participate in the AISI network, there’s some uncertainty about whether they would be welcome. It would be embarrassing to establish an AI Safety Institute, on a Western-created model, in order to join a Western-led club — only to be passed over for an invite to the party. If Beijing believes that the UK or — more likely — the US could block them out from the AISI network, that reduces the incentive to create an AISI in the first place, with an additional disincentive for China’s self-esteem.

The fact that China did not sign the Seoul declaration that launched the network would not necessarily be a barrier to their joining. Kenya was not a signatory but has been invited to the first convening of the AISI network. Incidentally, signatories Germany and Italy will not be attending, and will only be represented by the EU delegation as a whole.

If China is to set up an AISI, it would likely need to balance the interests of various influential stakeholders domestically, appear distinct enough to constitute a uniquely Chinese contribution to international AI governance, and be viewed by leaders in Beijing as burnishing China’s prestige on the global stage.

If not an AISI, what Chinese institutions play AISI-like roles?

Even without an AISI, several institutions in China perform AISI-like functions. If China eventually sets up an AISI, it would likely draw on these existing bodies doing related work, either by stitching together a consortium or drawing on them for personnel and intellectual influence.

However, AI safety is an emerging, dynamic environment — one where a new organization could suddenly rise to prominence at the national level. Additionally, some of China’s AISI-like organizations are influential but much less suited to international engagement. This includes China’s online censorship office, the Cyberspace Administration of China (CAC). Apart from ensuring that internet content conforms to CCP ideology, CAC also plays a key role in regulating AI in China. CAC authored rules on algorithmic recommendation systems and “deep synthesis” systems (deepfakes, essentially), and it administers the algorithm registry that functions as a quasi-licensing regime.

Does it really matter if China doesn’t have an AISI?

AISIs were created for a reason. The lack of a Chinese AISI makes international engagement more difficult in several ways:

1. International counterparts will have to decide for themselves which organizations in China are most relevant and authoritative. Engaging with multiple institutions of questionable influence might come at the expense of cultivating deeper working relationships with the most important Chinese partners. 

2. International engagement is underpinned by domestic stakeholder management, which is done most effectively by a single entity with an official mandate. 

3. A centralized hub of AI safety expertise would presumably come with a standard operating procedure for involving the higher-ups in the CCP, facilitating smoother and faster decision-making on strategic questions.

That said, China’s absence won’t render international AI cooperation dead on arrival. Participation in international governance — and maybe even the international AISI network — doesn’t necessarily require China to have an AISI. Neither Kenya nor Australia have established an AISI as of November 2024, and yet both were invited to San Francisco. And, although China wasn’t invited to the San Francisco meeting, Commerce Secretary Gina Raimondo said in September that officials were “still trying to figure out exactly who might come in terms of scientists,” implying that some individual Chinese scientists might be involved.

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But, even if China did have an AISI, this wouldn’t guarantee the willingness of other countries to cooperate. Washington generally has a frosty attitude towards engagement with China these days, which might get even frostier with the incoming Trump administration. The perception that the US and China are competing in an “AI race” might make engaging in AI safety dialogues particularly difficult. 

On one hand, some US government officials reportedly opposed China’s inclusion at the Bletchley Summit. On the other hand, government representatives from China and the USA did meet in May 2024 for a dialogue about “AI risk and safety,” and the two sides even agreed to a subsequent follow-up. The White House statement about the dialogue notes that US representatives raised concerns about Chinese misuse of AI, which aligns with Biden’s AI executive order. But publicly available evidence doesn’t actually specify which government initially requested this meeting — and thus it’s anyone’s guess if this dialogue will continue into the next administration.

In the meantime, international partners can choose from a constellation of Chinese organizations doing AISI-analogous work. For example, if the US or UK AISI wanted to discuss ways to measure whether new AI models can enable non-experts to create and deploy bioweapons, representatives from CAICT or SHLAB could convey relatively authoritative information about AI safety evaluations in China. Similarly, our report finds that Technical Committee 260 is the clear frontrunner for international partners looking to discuss China’s standard-setting legalities. 

On these narrow topics at least, engaging with these institutions could provide many of the same benefits as engaging with an officially designated AISI.

Addendum — Who would run a Chinese AISI? / Surprise guests in San Francisco?

If we were to speculate about who would lead a Chinese AISI, the aforementioned Andrew Yao would be a natural choice. Yao is a computer scientist born in Shanghai, raised in Taiwan, and educated in the US. He returned to China (taking PRC citizenship) later in his career, and won the Turing Award for his work in the theory of computation. He has received a public letter of laudatory recognition from no less than Xi Jinping himself. At Tsinghua, he leads the Institute for Interdisciplinary Information Sciences which houses the famous “Yao Class,” widely recognized as one of China’s top undergraduate STEM programs. For a number of years, Yao has been very active in discussing AI safety as a technical priority to Chinese audiences, and a pillar of international scientific dialogue on the topic.

Other grandees who might be involved include the respected heads of three key state-backed AI research groups —  Huang Tiejun 黄铁军 (Chairman of BAAI), Gao Wen 高文(Director of Peng Cheng Lab), or Zhou Bowen 周伯文 (Director of SHLAB).

Huang has written about risks from advanced AI for many years, including co-authoring a 2021 paper entitled “Technical Countermeasures for Security Risks of Artificial General Intelligence.” He has also recently discussed his expectations for the trajectory of advanced AI development, predicting that when AI’s cognition and perception capabilities surpass human levels, “physical control” will be “impossible.”

Gao Wen was also a co-author of the 2021 Technical Countermeasures paper, and has recently referred back to the threefold method of risk analysis outlined in this paper, including related to the lack of interpretability and the difficulty of control. However, PCL’s close links to the Chinese military, as a main “cyber range,” could potentially make Gao’s involvement awkward for international engagement.

Zhou Bowen, though evidently newer to the topic, has recently been promoting the idea of an “AI 45° Law,” according to which AI safety should keep pace with AI capabilities.

A more mid-career technical expert who would be well-positioned to be tapped by a Chinese AISI is Yang Yaodong 杨耀东, a professor at Peking University who leads the PKU Alignment and Interaction Research Lab (PAIR). In China, PAIR is one of the key research labs working on methods to align AI systems with human values under human control.

Finally, there are two leaders in Chinese AI governance with a valuable track record of international engagement. They are Xue Lan 薛澜, Dean of the Tsinghua Institute for International AI Governance, and Zeng Yi曾毅, Professor at the Chinese Academy of Sciences’ Institute of Automation and head of several other research and policy organizations. Both have been signatories to multiple statements in the International Dialogue on AI Safety series. As of mid-2024, Zeng also leads the Beijing Institute for AI Safety and Governance — the organization mentioned above as positioning itself to serve an AISI-like function. (The aforementioned Yang Yaodong also appeared on a slide at Beijing-AISI’s announcement ceremony listed as one of the organization’s “core research forces.”)

Check out Karson and Oliver’s full report on Chinese AISI counterparts here.

Elias X. Huber is a Yenching Scholar at Peking University and a visiting researcher at Tsinghua University. He holds an MSc from ETH Zürich, where he specialized in quantum information theory and co-led a consulting company. Today, he’s here to discuss China’s quantum ambitions, explain the new investment controls on quantum information technologies, and take us on a nuanced journey through China’s quantum research institutions — from universities to start-ups to state-owned enterprises.

On October 28, 2024, the U.S. Department of the Treasury implemented the USA’s first-ever outbound investment control regime. Investments by U.S. persons in AI, semiconductors/microelectronics, and quantum technologies in “countries of concern” (currently, just China incl. Hong Kong and Macau) now require notification or are outright forbidden. 

For semiconductors and AI, the restrictions are confined to certain technical specifications and capability thresholds. The restrictions on quantum technologies, however, are far more expansive — across a broad swathe of quantum applications, transactions are now outright forbidden.

In the short term, these prohibitions aren’t going to devastate China’s prowess in quantum research. The practical implications for the future, however, are threefold:

1. The restrictions could systematically push the sector to further rely on state-led “patient capital.”

2. The rules could inadvertently reduce the transparency of China’s commercial quantum efforts.

3. If quantum technologies become foundational for information infrastructure in the future, the rules will ultimately restrict a much wider variety of economic activity than they do today.

Why does the U.S. government care about quantum research anyway? What funding streams are available to China’s quantum startups now that U.S. financing is banned? And what does this all mean for China’s quantum ambitions?

We’ll get there, but first — some definitions.

The New Rule and Quantum Terminology

The new rule has been over a year in the making: In August 2023, President Biden issued an Executive Order (the Outbound Order) calling for outbound investment controls in “three sectors of national security technologies and products to be covered by the program: semiconductors and microelectronics, quantum information technologies, and artificial intelligence.” What followed immediately was an advance notice of proposed rulemaking (ANPRM), a notice of proposed rulemaking (NPRM) in July 2024, and, after public comment, the final rule on October 28, 2024.

Under the new rule, U.S. persons are either forbidden from covered transactions or must notify a newly created Office of Global Transactions within the U.S. Department of the Treasury. 

Roughly speaking, transactions are covered if all of the following conditions are met:

• they are between a U.S. person and a Chinese entity or an international entity that is deemed sufficiently connected to a Chinese entity,

• the Chinese entity engages in covered activities in semiconductors, quantum information technologies, or AI,

• the U.S. person aims to acquire equity, provide financing, make investments, or enter joint ventures in the Chinese entity, and,

• the transaction is not among the listed exceptions, which include publicly traded securities and some Limited Partner investments.

Quantum information technologies (henceforth just quantum technologies) can be divided into three main categories — quantum computing, quantum sensing, and quantum communications. These involve engineering and manipulating small physical systems according to the laws of quantum mechanics for practical applications — often leveraging counterintuitive features of quantum mechanics. These physical systems — the quantum information carriers — range from superconducting circuits cooled to near absolute zero to delicately prepared states of light.

Take quantum computing, where different states of “quantum bits” can be superposed and programmed to interfere with each other. This could theoretically solve computational problems that are near-impossible to crack today — including the encryption techniques that are used to secure your bank account.

Similarly, quantum sensors can improve sensitivity or other form factors in measuring quantities such as time or gravity.

Currently, quantum communication refers primarily to encryption and information security applications, which leverage the unpredictability of quantum measurements and the impossibility of copying quantum information. But this field could one day expand to whole networks of quantum sensors and quantum computers.

The new rule takes the same tripartite classification, with covered quantum transactions forbidden if related to the development or production of:

1. Quantum computers and their critical components,

2. Quantum sensing platforms for military, intelligence or mass-surveillance end use, 

3. Quantum communication systems for secure communication, for scaling up quantum computing, and any other application with military, intelligence, or mass-surveillance end use.

Most notable is the restriction on quantum computers. Quantum computers receive the most investment and hype — and the new rule completely forbids investments in Chinese quantum computers regardless of end use. This is despite the fact that quantum computers are less mature than the other two, with no useful application yet available, and near-term applications that will be primarily academic and civilian. However, in the long run, quantum computing is expected to be the most broadly disruptive of the trio and is fundamentally dual-use, threatening information security for example.

For quantum sensing, the rule only restricts investments aimed at sensitive end use. Military applications of quantum sensors (such as detecting tiny variations in earth’s gravity and magnetic field caused by adversary submarines) can more often be separated from civilian uses (such as measuring magnetic fields induced by the neural activity of your brain).

Unlike a quantum computer, which could solve optimization problems and steal cryptocurrency — with little ability to discern the two uses — quantum sensors will often be closely tailored to their expected end-use (from size, power demand, and ruggedization to calibration and signal processing). 

Finally, quantum communication systems for secure communication (especially a technology called “Quantum Key Distribution”) are slowly being deployed in real-world applications, with China far ahead of the rest of the world. While the quantum communications market in China is significant, it is unlikely that U.S. investment is particularly welcome here in the first place, given that it is one of few quantum technologies export-controlled by China.

Restrict to Stay Ahead

ChinaTalk has discussed the “Sullivan Tech Doctrine” and China’s military-civil fusion in previous analyses of U.S. controls on AI and semiconductors — and quantum fits right into this familiar discussion. The Outbound Order lists quantum technologies among the innovations critical to “military, intelligence, surveillance, or cyber-enabled capabilities.”

Beyond just specific military applications, the report views broad quantum capabilities (such as advanced computation) as critical to U.S. national security. Investment controls aim to prevent U.S. capital and intangible benefits that accompany it from advancing such capabilities in countries of concern, i.e. China. 

Quantum is distinct from AI and semiconductors because the technology is still quite immature.

Nonetheless, the recent outbound investment rule joins a long list of quantum restrictions, including two rounds of additions to the entity list, inbound investment restrictions, restrictions on the movement of people, and multilateral export controls aimed at quantum computing.

In order to understand the impact of the newest outbound investment restrictions, we need to take a closer look at the process for commercializing quantum technology in China.

It Starts with Science — and Public Money

The term “quantum mechanics” was proposed almost exactly a century ago. However, the quantum technologies listed above only started to take off in the early 2000s during the “second quantum revolution.” Therefore, nearly all commercial efforts in quantum originate in academic research groups, with initial IP often going back to public funding.

Given the importance of said public funding, foreign observers frequently contrast the outsized role of the Chinese state — which has perhaps invested over 15 billion USD1 in quantum research — with the private-sector-driven research environment of the United States and Europe. 

Consequently, leading Chinese quantum technology is often developed in publicly funded research labs — including the National Quantum Lab (量子信息科学国家实验室) or the Quantum Computing Engineering Research Center 安徽省量子计算工程研究中心 in Hefei, Anhui province. Government-controlled companies — such as China Telecom or state-owned enterprises such as China Electronics Technology Group — play an important role in the development of quantum technologies, with the former putting 3 billion yuan into establishing its own quantum technology group and the latter launching a quantum cloud computing platform.

In recent years, the closures of Baidu’s and Alibaba’s quantum computing units (donating their equipment to public institutions) have increased speculation of an “attempt by the Chinese government to assert tighter control over what it sees as a strategically important technology.”

The problem with this narrative is that the CCP doesn’t really seem to have meaningfully consolidated the broader quantum industry — abandoning quantum research made sense for Alibaba and Baidu independent of any hypothetical government agenda.2

While government-led technology development in China does have a long history, so does commercialization and partnerships with the private sector. Deng Xiaoping recognized the need to dissipate science and technology throughout the wider economy back in the 1980s. Regardless of which soundbite the CCP chooses — “rejuvenating the nation through science and education”, “innovation-driven development” or “new quality productive forces” — achieving intensive economic growth based on innovation and technology is a political priority.

So what, then, is the role of the private sector in quantum tech development?

Stepping out of the Labs

State-led efforts need not be isolated from the wider economy. Anhui’s Quantum Computing Engineering Research Center is developing quantum computers together with one of China’s leading quantum start-ups, Origin Quantum Computing.

Chinese efforts toward market-led commercialization of publicly funded innovations are reminiscent of the American Bayh-Dole Act of 1980. In China, regulations issued in 2002 and a law on S&T transformation in 2015 likewise aimed to facilitate the licensing and transfer of IP from government-funded institutes to the developers, incentivizing their commercialization. 

The practical realization of this IP transfer can take many forms. For a concrete example, let us look at the University of Science and Technology of China (USTC) in Hefei, one of China’s leading centers for quantum research.  

China’s first quantum start-ups — QuantumCTEK and Quasky — both originated from USTC laboratories in 2009. Under the national call for the “transformation of scientific and technological achievements 科技成果转化,” early efforts at QuantumCTEK proceeded in lockstep with the university. Back then, QuantumCTEK’s chairman Peng Chengzhi 彭承志 was managing corporate affairs while simultaneously doing research for the Micius satellite 墨子,  one of the most important scientific quantum experiments of the century.3

When QuantumCTEK was established, USTC likely transferred IP rights to the company in exchange for shares — which USTC still holds. Those investments are managed by USTC’s holding company, which lists at least four other quantum start-ups in its portfolio. 

Looking forward, USTC has recently piloted a new model for transferring university IP to commercialization-focused researchers. Instead of shares in the company, the school obtains access to future benefits negotiated in advance — for example, a fraction of the company’s profit. Research at USTC also benefits its business alumni: Through bi-directional recruitment and frequent exchange, academic laboratories gain access to professional equipment and organizational practices.

Beyond government slogans and incentives, the success of early start-ups such as QuantumCTEK is maybe the biggest inspiration for enterprising quantum scientists across China. QuantumCTEK was listed on the Shanghai Stock Exchange STAR market in 2020, with its share price rising ten-fold on the first day of trading. The company is now expanding beyond its original vertical in quantum cryptography to quantum computing. 

In 2021, QuantumCTEK became the first Chinese quantum company placed on the U.S. entity list by BIS. Yet, Hefei has become a hub for quantum technology companies, with a dedicated “quantum avenue” for start-ups following in the footsteps of QuantumCTEK and Quasky. Thanks to enthusiastic support by the local government, Hefei hosts 60 upstream and downstream companies in the quantum industry chain.4

Now that we’ve covered the state-backed origins of China’s quantum companies, we can discuss the firms that could be most impacted by the recent outbound investment controls — that is, the young, market-driven start-ups often led by former academics. These burgeoning quantum start-ups need a healthy venture capital market in order to scale up… right?

China’s Venture Capital Woes

English language reports often paint a bleak picture of private quantum funding in China. For example, a report by the Information Technology & Innovation Foundation (ITIF) finds that, “despite large numbers of reported Chinese quantum companies, there are only around 14 private-sector firms that can be identified as making significant contributions to quantum technology, including nine start-ups and five major tech companies” — a count that includes Alibaba and Baidu, despite their exit from developing quantum computers. A 2023 McKinsey report is cited, noting 10 times more private investment in quantum start-ups in the U.S. than in China. Let us stay with this narrative for now, before explaining why, once again, there is more to the story.

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China’s equity investment market is indeed in deep trouble, which brings headwinds for quantum startups. In a survey of 50 leading VC and PE institutions by ChinaVenture, less than 5 were optimistic. Besides just bad sentiment, investment activity is down — science parks visited by the Financial Times stand empty as fewer start-ups are founded and successful exits through IPOs are increasingly difficult. 

FT blames political pressure by the government. The analysis by ChinaVenture points to higher U.S. interest rates, changes in exchange rates, and the poor performance of Chinese stock markets. Both agree, however, that plunging foreign investment is contributing to the decline.

The recent rule may have played a role here. Remember, that the Outbound Order first called for investment restrictions on China in August 2023. And Congress put private equity markets in the hot seat even earlier — a House Select Committee launched an investigation into five venture capital firms in July 2023, requesting information about the firms’ investments in Chinese entities. Besides Uyghur-tracking AI, the committee’s report mentions concerns about Chinese domination of critical technologies.

The downturn of U.S. investments in Chinese companies is hence both driven by markets and politics. Long-term signaling from the U.S. government ensured that the market priced in the investment restrictions in advance.

With foreign investors fleeing and a dying venture capital market, is it all doom and gloom for China’s quantum start-ups? There are at least two reasons why this might be an overeager conclusion — one is our lack of knowledge, and the other is the support of the state.

On the first one, let us revisit the current state of quantum start-ups in China. The report by the ITIF referenced above mirrors typical observations in English language reporting: China’s commercial efforts are small, dwarfed 10x in both funding and quantity by their American counterparts, and government-funded research institutions dominate instead. Without the trend line being wrong, this confident bashing risks overlooking important developments. The footnotes of the 2024 McKinsey Quantum Technology Monitor explicitly concede that the authors have limited insight into commercial quantum activity in China. The ITIF report which claims that “only around 14 private-sector firms [...] can be identified as making significant contributions to quantum technology” fails to list start-ups such as Bose Quantum or Huayi Quantum — which are both more significant than some companies that did make the list. With such limited information, it’s not prudent to announce any clear-cut conclusions.

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Even admitting that there could be more to commercial Chinese quantum efforts than generally acknowledged, the question remains: Can these start-ups see success in a difficult market, without U.S. money and intangible benefits?

State assets to the rescue?

Amid the decline in private capital, the share of state-owned capital in VC and PE funds has increased. This leads to many problems. Bureaucrats at SOEs face intense pressure not to lose or mismanage state-owned assets — yet most VC investments are failures, with VC funds typically only profitable thanks to a few individual investment exits that reap high returns. Local governments, often cash-strapped themselves, primarily aim to develop the local economy — not serve start-ups. To reduce their risk, VC funds backed by state-owned assets often demand personal liability for investments — which is very scary for potential founders in a country with no nationwide personal bankruptcy law. 

What is lacking is “patient capital” — risk-tolerant investments willing to support innovation with a long-term outlook. The commercialization of quantum technologies is especially challenging. Investors need much patience, as expensive development efforts may not result in revenue for a very long time due to the early stage of the technology. Beyond the business model, investors bet on the future trajectory of a complex technology, serving markets that may not yet exist.

Yet in some cases, a (local) government-dominated model can work. Alongside the quantum startup cluster, the so-called “Hefei model” has achieved success in EVs, biotech, and semiconductors through targeted investments by the local government. In Hefei, attracting investment is an all-hands-on-deck effort, where nearly all departments of the government are involved in one form or the other. State-owned enterprises provide equity financing for firms the local government wants to attract to the city, alongside legal assistance, policy adjustments, and highly personalized incentive packages for individual entrepreneurs. Beyond just attracting and incubating companies with potential, the city government creates dedicated groups to coordinate the planning and supply chains for targeted industries.

Located in Hefei, USTC is crucial for the local talent base and innovation ecosystem. It enjoys the highest support and trust from the local government, which provides funding and support to USTC’s alumni looking to establish start-ups. The Hefei government itself recruits from the university's talents. Frequent exchanges between government offices, university departments, and companies build information networks. USTC entrepreneurs are encouraged to stay in the province, with better IP transfer terms if commercialized locally. 

This trust (and an unusually high risk tolerance) explains the local government's willingness to invest in quantum start-ups under less stringent terms than other government-funded VC investments. Already in 2017, the local government announced a 10 billion RMB quantum fund established by the Provincial Investment Group to support the local quantum industry. Set up for a ten-year life span, a five-year investment, and a five-year exit period, the fund established an independent decision-making committee and an expert committee made up of highly reputed academicians. 

On a national level, the government has recognized, and is determined to solve the lack of “patient capital”. Replicating the “Hefei Model“ might not be easy. Local talents, institutional culture, and investment expertise take time to develop. A risk appetite like that of the Hefei local government could backfire if large amounts of state-owned assets are lost. However, in quantum, there are signs that others are willing to try.

In Hubei, the local government announced 100 million RMB into a quantum industry fund, aiming to invest in projects from local laboratories such as the Wuhan Institute of Quantum Technology. Despite being funded by the government, the investments are supposed to be market-oriented with an expert committee to provide professional guidance. In Shanghai’s 10 billion RMB Future Industry Fund, also supported by a scientific committee, quantum technology is also included. Beijing too has its own 200 million RMB Quantum Industry Development Fund to support start-ups and SMEs in the quantum industry, and recently established a Quantum Technology Incubator 中关村量子科技孵化器 and a Quantum Technology Industrial Park 量子科技未来产业园 to provide facilities, connections, and organizational support alongside capital.

Where do we go from here?

Can these government-funded efforts compensate for the loss of professional market-driven dollar investments, with all the advantages in networks, reputation, and management that U.S. investors bring? 

On the one hand, local governments can holistically coordinate and incentivize whole sectors, and provide extensive logistical and legal support in tandem with funding. Which private VC could dream of the convening power to have academic expert panels evaluate their investments?

On the other hand, bureaucrats are never purely market-driven, they distort competition and often lack the track record of U.S. investors to efficiently place money, tax money that is, in risky bets. 

For quantum, it is too early to tell which innovation system will prevail.

Given the abundant funds available for quantum research, it will not be the lack of U.S. money — but rather the lack of U.S. practices that come with U.S. money — that could have the most profound impact on China’s ability to commercialize quantum technologies.

Regardless, China’s quantum companies will remain fascinating to watch. Regarding further scrutiny of these companies, the recent sequence of quantum controls might backfire for U.S. policymakers. By adding leading quantum companies to the entity list, others are incentivized to keep a low profile and prepare for restrictions. Additionally, given the outbound investment controls, there are unlikely to be many foreign VCs with deep diligence in China’s quantum market, and future public reports on China’s quantum companies could become even more speculative than they are now. Increasing controls on quantum technologies could also lead to us never seeing China’s quantum start-ups compete head-to-head with those of “the West.” 

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For now, the new outbound investment restriction likely won’t change much for China’s development of quantum technologies: Political risks have been factored into investment decisions even before the new rules were finalized, and U.S. investments into Chinese quantum technologies never became relevant.

However, if quantum technologies become foundational for a wide range of technologies, the outbound investment controls could make an increasing number of Chinese companies taboo, or at least questionable, for U.S. investment. For example, China Telecom is an example of a large company not commonly associated with quantum, which has significant efforts in developing quantum technologies that are very likely covered under the new rule. While public trading of China Telecom shares falls under an exception to the rule, it’s clear that the effects of the rule won’t be limited to just deep-tech startups. 

Another example is an interesting technology called Quantum Random Number Generators (QRNG). Random numbers are needed in cryptographic applications, but generating truly random numbers is a surprisingly difficult task without quantum physics. QRNGs are thus poised to become the first mass-market quantum technology, and Samsung is already marketing smartphones featuring QRNG security chips. But QRNGs could plausibly be categorized as a “quantum communication” device intended for “secure communications,” which would make related transactions prohibited under the new rule. This example cautions how narrow restrictions today could soon become expansive.

Perhaps the integration of mass-produced QRNGs does not fall under what the rule classifies as “develops or produces.” But imagine the confusion investors face when all networked devices, from smart cars to phones, suddenly have some “quantum” in them.

3

The Micius satellite can send entangled photons (particles of light) to ground stations separated by more than 1,000 kilometers. Intuitively, these entangled photons allow the two ground stations to generate random but identical numbers without any mutual communication, exploiting non-local correlations possible only in quantum mechanics. These numbers can act as a secret shared password — facilitating quantum-encrypted intercontinental video calls, as scientists first demonstrated in 2017.

The importance of the Micius experiment, estimated at 100 million USD, is hard to overstate. It is not just a scientific milestone but also a political symbol (hence the stamp). If you ever visit Beijing, you can see a 1:1 scale replica proudly displayed in the Museum of the Chinese Communist Party 中国共产党历史展览馆).

Few books have influenced me as much as the Makers of Modern Strategy series. The three volumes (published in 1942, 1986, and 2023) are indispensable to understanding statecraft, leadership, and the evolution of warfare across millennia.

The New Makers of Modern Strategy (2023) is a thousand pages long and analyzes strategy from ancient Greece to the Congo.

The man behind this behemoth collection is Hal Brands, a professor at the Johns Hopkins School of Advanced International Studies and a returning ChinaTalk guest.

In our conversation, we discuss:

• The process for compiling such an ambitious collection of essays;

• Unique insights and new topics covered in the 2023 edition, including Tecumseh, Kabila in the Congo, and Strategies of Equilibrium in 17th Century France;

• Advice for reading the book effectively;

• Revolutions in military affairs, from the atom bomb to quantum computers.

For reference, you can compare the content of the three volumes with this spreadsheet, courtesy of Nicholas Welch.

Have a listen on Spotify or Apple Podcasts.

Favorite Essays

Jordan Schneider: Hal, thanks so much for producing this book.

Looking back at the process, which essays were you the most excited to publish?

Hal Brands: That’s a little bit like asking me which of my children I’d prefer to keep. They are all beautiful and they are all my favorites. There were maybe a handful that are worth mentioning just because, from the beginning of the project, I thought they were going to be really cool. 

The first substantive chapter is an essay by Sir Lawrence Freedman, the great British scholar [Ed. Coming soon to ChinaTalk!]. He is the only scholar who wrote an essay in the 1986 version and in the 2023 version. His essay is called, “Strategy: A History of an Idea.”

It illustrates how definitions of the terms “strategy” and “strategist” have changed over time. I had Freedman in mind when brainstorming ideal authors to write that essay, and I was just delighted that he could do it.

Another interesting angle on a classic subject is Hew Strachan’s essay on Clausewitz. Carl von Clausewitz has been a recurring character in both the 1943 and 1986 editions of the book. He looms over the field of strategic studies.

But Strachan’s interpretation is basically that everybody gets Clausewitz wrong. Michael Howard’s translation of Clausewitz — which all of us professional nerds have read and relied on — is actually a distortion of Clausewitz’s argument about the relationship between war and politics.

When you get Hew on board to do an essay like this, you know he’s going to say something profound and you know he’s going to say something original. I was even a little surprised by just how jarring that reinterpretation was. It’s really going to make a splash.

Jordan Schneider: I’ll shout out two more essays that I really enjoyed — one was the Tecumseh essay. For our non-American listeners, Tecumseh was a Native American leader and war hero who banded during the War of 1812 between the US and the UK. He came pretty close to beating the US and shutting down Western expansion. 

Tecumseh pulled together a larger fighting force than any other American Indian chief in history, creating a twelve-hundred-­mile barricade to limit westward expansion of the United States…

[H]e propagated centripetal religious beliefs that advanced politi­cal power within tribes and encouraged accession to the Confederacy; he used social suasion to reduce reliance on colonial-­produced goods; he won foreign economic support that freed up fighters for military campaigns; he secured consequential Eu­ro­pean military involvement; and he produced an or­ga­nized military force capable of defeating the US militarily.

The Shawnee Confederacy threat precipitated the doubling of the size of the US military, and the Confederacy imposed the largest combat losses the US had known to that point.

The United States government defeated this elegant strategy not on the battlefield, but eco­nom­ically.

[The New Makers of Modern Strategy, pp. 369-370]

The other essay that completely blew my mind was Jason Stearns’ “Strategies of Persistent Conflict,” which looked at the Congo wars. The logics of persistent and brutal conflict is different from the military strategies described by Clausewitz and Jomini.

Having those modern wrinkles added to the canon was really interesting.

Hal Brands: Those were two of the most original essays in the volume, both in terms of the subjects and also how they compel us to rethink strategy. The thesis of Kori Schake’s essay is that Tecumseh was really a practitioner of what we would consider an all-of-society strategy. As you mentioned, he came close to succeeding. 

Jason Stearns wrote the essay on wars in Africa. That one is so interesting because it turns the traditional Clausewitzian paradigm on its head, pointing out that protracting the war can be a form of strategy. Not in the Fabian sense of trying to exhaust your enemy and then defeat him, but in the sense that the war may actually be profitable for the groups undertaking it — continuation of the war can itself be a strategy.

[I]n the Demo­cratic Republic of the Congo (DRC), as well as in other weak states…waging war becomes both a lifestyle and a fundamental tool of po­liti­cal survival, providing a means of managing dissent and doling out patronage…

It was during this stalemate of [The Second Congo War] that… [t]he assorted belligerents became deeply invested in vari­ous forms of economic activity, a blend of racketeering, extortion, and taxation. …

Following the blueprint for United Nations peace pro­cesses at the time, diplomats pushed for peace talks, which they hoped would be followed by a power-­sharing agreement and the reunification of the country. …

Some scholars go so far to argue that the penchant for power-­sharing agreements by Western donors has inadvertently incentivized rebellions by making them an acceptable path to power and lowering the cost of insurgency. While this finding is contested, it is clear that international norms against protracted military conflict have made it more difficult to achieve military victories. …

The war made large-­scale agricultural production almost impossible, cutting off trade routes to the rest of the country, pillaging livestock, and preventing investment. The economy became increasingly focused on the mining sector, which in turn became extremely militarized. Meanwhile, employment opportunities shrank for the youth, making armed insurgency more attractive.

[The New Makers of Modern Strategy, pp. 1048-1050]

Jordan Schneider: There’s something that’s so dark about this entire book. I catch myself getting excited as I flip through this book trying to choose which essay to read. “Maybe it’s time for Napoleon. Maybe it’s time for nuclear war.”

These are exciting topics, but it’s also tragic that as a species we have spent so many thousands of years innovating new ways to kill our fellow humans. Do you have any thoughts on that?

Hal Brands: You put your finger on an important point, which is that the content of strategy changes in different eras as different technologies and different challenges emerge. The basic practice — the nature of strategy — doesn’t change that much over time. It’s really about trying to use the means at your disposal to achieve whatever aims you seek, in the face of all the resistance and chaos of the world. 

Even though it’s something that exists in peacetime as well as wartime, we most frequently pay attention to strategy when the stakes are high. That’s typically when violent conflict is either happening or threatening to happen. There is an inherently dark nature to the subject material.

As I often point out in my writings or when I’m talking to students — strategy is itself a very optimistic endeavor, because the idea of it is that you can impose a certain purpose on events rather than simply being tossed around by them. You can use power in purposeful and coherent ways. That’s the enduring challenge of strategy, and that’s the thing that pretty much everybody featured in this volume was wrestling with in one way or another.

The History of Security Studies

Jordan Schneider: Let’s take a step back then and look at this concept of security studies. Do you want to talk about the origins of this as a pseudo-discipline and how the first book ended up coming together in 1943? 

Hal Brands: Absolutely. I’ll make a point here that’s a little deep into the academic weeds, which is — there’s often said to be a difference between strategic studies and security studies. 

Strategic studies, to put it bluntly, is the study of political-military issues. It’s got a somewhat narrower thrust. Security studies can encompass all sorts of things. There are various different types of security. It can deal with climate, it can deal with human security, it can deal with a whole range of issues. It’s typically thought of as a somewhat more capacious discipline.

In my mind, they’re very closely related. People who are involved in one camp or the other will say they are different things. That distinction is just worth mentioning for CYA on my part. 

The development of Makers of Modern Strategy is inseparable from the emergence of strategic studies and security studies as related fields in the United States. The first volume of Makers, as you mentioned, was published in 1943, it was started a couple of years before that. The editor was a guy named Edward Mead Earle, who was at the Institute for Advanced Study in Princeton, New Jersey. He had really been involved in a rethinking of the requirements of national security as the world fell apart in the 1930s.

He was a big proponent of the idea that the United States needed a more coherent approach to grand strategy, bringing together all the different forms of national power to deal with all of the threats — economic, military, ideological — that emerged as fascist regimes gained the ascendancy during the 1930s. 

He was motivated to pull the book together by the idea that the United States was henceforth going to be far more deeply and far more consistently involved in global affairs than it had been in the past. The American people — not just national security elites but just educated men or women on the street — needed a deeper understanding of military affairs and strategic affairs more broadly if the United States was going to have the educated citizenry it needed to be effective in this era. 

That was the goal of the first volume. It developed in parallel to the emergence of strategic studies research and teaching programs. It was part of the development of the intellectual sinews of the American superpower during the late 1930s and 1940s. It was a smash hit. 

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Jordan Schneider: The idea for this book was great from the start, but it took money to fund the professorships and create the conferences to entice more academics into grappling with those questions of national power and grand strategy. 

The book and the broader thinking that this field generated, which ended up informing a lot of how America has engaged with the world for the past 75 years, wouldn’t have happened without that initial academic seed funding sorts to allow people to research and write along the lines that he initially laid out.

Hal Brands: That’s exactly right. Ideas may be cheap, but good ideas aren’t cheap. Developing a cadre of intellectuals who are going to work on major research projects — that takes money. The emergence of strategic studies as a field was led by Carnegie and a couple of other foundations and philanthropic entities.

Then, of course, the field really develops in the context of World War II and the Cold War, when also the US government is throwing more money at these areas than ever before — including by funding the RAND Corporation.

You wouldn’t have gotten security studies or strategic studies as fields in the United States without the collapse of the international system in the 1930s, the interest that spurs in these sorts of issues and then the investments that philanthropic entities in the US government make in it over the decades to follow.

Jordan Schneider: Let’s stay on this 1943 book. It is a fascinating document, because it’s literally in the middle of the war. You have essays by Earle talking about Hitler’s strategy and he’s like, “Yeah, we think they’re going to lose, but we’re not sure.”

There’s another essay about Stalin where the author is like, “Yeah, we’ll see about this spring offensive.”

There seems to be a lot of personality in the authors where they can show their prejudices on their sleeve. Everyone’s just making fun of Erich Ludendorff for being an idiot. Looking at that book, what stuck out to you about those essays?

Hal Brands: As you mentioned, a lot of the essays were written really without knowing how the war was going to end. The essay on Hitler makes the point (which in retrospect was true) that Hitler was a better strategist before the war began than he was after the war began. 

The book was published in 1943, so it was probably completed in 1942. This was at a time when the outcome of the war was very much in doubt. For long stretches of 1942, it seemed plausible that the Axis might be able to, if not win the war, at least push their conquest to the point where winning it would be extremely difficult for the Allies. It was history written in real time, which is hard. That’s one thing. 

The second thing is that the composition of the contributors is very much a product of the moment. If you go through and you look at the biographies of the people involved, a number of them were essentially refugees from Hitler’s Europe. They were European academics who’d been pushed off the continent by Nazi conquests and then ended up in the United States where, of course, they enriched the intellectual life of this country as well.

Then, the third point is that the contributors were very much aware that this was not a value-free exercise. They were not necessarily taking a god’s eye view of the international system. 

Of course, they were trying to be objective and dispassionate in their analysis of history, but the point of the book was to help democratic societies do strategy better. This was not disinterested history. This was history with a commitment to helping democratic societies survive and flourish in a very dangerous world. That ethos has survived in the succeeding volumes.

Jordan Schneider: This idea of new history as a stimulus to action, with this book aimed at everyday concerned citizens, and not necessarily scholars of Jomini — that’s what makes this book so fun for nonprofessionals or students to flip through. The best essays make you want to buy a book about the topic because you’re interested in learning more.

There are so many little gems in these sentences and paragraphs that both try to teach you a lesson about the essentials of these stories, but also really end up enticing you to want to learn more.

One example from the essay on Delbrück, the military historian.  He was this German guy who was the first one to actually try to count up how many people would have been at a Roman legion — for example, was Caesar exaggerating when he said he was fighting against 500,000 guys.

Hal Brands: It helps that the essays, particularly in the first volume, are about people. There’s something relatable about essays that are about people. That’s the thing that will draw in the folks who may not be academic experts on Jomini, but are just interested in military affairs and interested in strategy and interested in reading interesting things. That was part of what made the first book such a success. I know it’s part of the appeal of the book still. 

The other nice thing about the first volume, by the way, is that the essays are all relatively short. They’re punchy. They get to the point. When I was putting together this volume, that was one of my goals, to make sure that the essays were meaty but didn’t go on forever and ever.

Jordan Schneider: There’s an essay on Hitler that essentially says, “We shouldn’t forget that Hitler is a genius.” It argues that the way he was able to pull off the 1930s is something that deserves praiseful discussion in the context of a grand strategist. That really stuck out to me, and it must have made quite the splash in 1942.

Let’s turn to the 1986 version of this book. What stuck out to you about that one?

Hal Brands: It’s an interesting book, in part because it took so long to do. The first discussion about updating Makers really started to happen in the 1950s. There were a bunch of different attempts to get a second volume, and various false starts involving various historians. It took 40+ years for the thing ultimately to come together.

What’s interesting to me about the second volume is that it’s written in light of the dangers of war in the nuclear age. Nuclear weapons create an element that were not there when the first Makers was published. That is reflected in the Lawrence Freedman essay in that volume that’s about the nuclear revolution and the schools of strategic thought that are associated with it.

It also hangs over a bunch of the essays in other ways. It’s there in terms of discussions of Clausewitz. It’s there in terms of just thinking about how high the stakes of war in particular have gotten and how important it is for people to understand what goes into good strategy in war. 

In some ways, what’s also interesting about that book is that the definition of strategy changes from volume to volume. The definition of strategy in the first volume is very broad — it’s essentially what we think of as grand strategy, all elements of national power to achieve some important objective.

The definition of strategy in the second volume is narrower. It’s more closely related to military affairs and political-military affairs than it is to the larger conception of strategy. The nuclear revolution and the shadow it cast over all war and all statecraft in the second half of the 20th century has something to do with that. 

Jordan Schneider: It’s weird that WWII ended two years after the first edition was published, and then the Cold War wraps up three years after the second one was published. I don’t know if there’s some leading indicator here.

Hal Brands: Maybe we’ll win it all in 2025 or 2026. Look out, Xi Jinping.

Project Management and Long Haul History Research

Jordan Schneider: Let’s discuss the newest edition. How does a project like this come together? Does Princeton University Press just call you up? Was there an interview process?

Hal Brands: There is a long story of how this volume came together that will be of interest only to me and my immediate family members. The short version is that Princeton had been thinking about doing a third edition because it had been 30+ years since the second volume. 

It was clear that we were entering what would have been referred to in 2017 and 2018 as “the new era of great power competition.” A lot of the questions about nuclear strategy and long-term rivalry that had gone into abeyance with the end of the Cold War were coming back in a very serious way.

The editor of Princeton, Eric Crahan, came down to Washington and had a conversation with me and also with a couple of friends who were involved with the project. Then, for a variety of reasons, mostly pertaining to other personal commitments, couldn’t follow it all the way to the end.

We put together — in conversation with Princeton — a proposal for how to structure the book. The final product looks something like that initial proposal. The idea behind it was to do a book that would be richly historical like the other two volumes, but where the choice of topics would be relevant and would be recognizable to people grappling with challenges of US-China rivalry, nuclear deterrence, and the other issues of today.

Jordan Schneider: As you were going through that back catalog, what were the ones that you thought you couldn’t do without, and how did you decide to cut other subjects?

Hal Brands: Well, certain things are just so fundamental to an understanding of strategy that you really can’t do without them, especially if the idea is for this volume to stand on its own. You can read this volume without having already read volumes 1 and 2. 

There’s a fair amount of overlap. Although all of the essays are new and original, when the book covers what’s called foundations and founders, basically, these aren’t the greatest hits of strategy, going back to Thucydides and the Peloponnesian War, Machiavelli, Clausewitz, and so on and so forth.

In each of those cases, the people who wrote on those subjects put really interesting new twists on the subject. I’ll call out Matt Kroenig’s essay on Machiavelli, which is actually quite original and quite interesting.

One of the real goals of the volume was to bring stuff up to date. Even though the 1986 version was written under the nuclear shadow, there were only four, maybe five essays that really dealt in detail with post-1945 issues. By the time we did version 3, obviously, we knew how the Cold War had ended. There was an entire generation of great scholarship on the Cold War. There is a whole section of 9 or 10 essays on Cold War-era stuff. Then there’s a whole section on post-Cold War content, because the post-Cold War era was 30 years old by the time the book was in gestation.

There’s much more of an effort to renew our understanding of strategy, not just through the greatest hits again, but also by looking at newer subjects that hadn’t been covered by earlier volumes.

Jordan Schneider: My favorite direct take on China is actually a riff-off of an old essay. It’s called “Economic Foundations of Strategy” by Jonathan Kirshner and Eric Helleiner. Instead of doing just Smith, Hamilton, and List, it was beyond Smith, Hamilton, and List. There was this really fun comparison between Chinese thinking and Western thinking in the late 19th and early 20th centuries about what kind of economy you needed in order to be a great power.

Hal Brands: I’ve got to give a shoutout to the two authors of that essay. Jonathan and Eric can take credit for that twist on the original. I went to them with a more conventional idea of an essay on the economic foundations of strategy. They asked if they could do something totally different, and it ended up being much better than what I had in mind.

Jordan Schneider: Did you start with a topic and then find an author, or did you start with the authors and then find topics? How did that matching process end up working for you?

Hal Brands: It’s a mix of both. There are some people who are so brilliant and so established in the field that you know you just have to have them in the volume. Basically, I would have let them publish their shopping list if they had offered to do that. I was going to have Lawrence Freedman in this volume no matter what he wanted to write. I was going to have John Gaddis in this volume no matter what he wanted to write. 

Then, there are some people who you know are experts on a certain topic. You go to them and you ask, “Could you write on thing X?” Liz Economy has written — for my money — the best book on Xi Jinping’s China. I approached her and asked if she would write on that, and she very graciously agreed. 

Then sometimes, you’ll take a proposal to someone and say, “Could you write on subject A?” They will say, as was the case with Jonathan Kirshner and Eric Helleiner, will say, “Well, why don’t I write on this other thing instead?” That happened in a few cases and it invariably made the volume better. 

Jordan Schneider: That essay was excellent, bringing the legalist Sun Yat-sen and Albert Hirschman together into one argument. I can see how that wasn’t just an idea you pitched to them right out of the gate. It’s interesting how that editorial give-and-take works.

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Hal Brands: There were a bunch of essays where that was the case. There’s an essay on the origins of the laws of war in the 19th century where I went to Wayne and asked him to do something more conventionally, came back and pushed back.

That creative tension or the give and take is actually one of the most interesting parts of an edited project because the people who you are recruiting to write these essays know far more about the subjects than I do. They’re typically a better judge of what’s interesting and what’s new.

Jordan Schneider: I’m curious, did they feel they had to bring their A-game? This is The Makers of Modern Strategy. This isn’t any essay collection.

Hal Brands: I will say this — I had far less trouble rounding up writers for this than you often do with edited collections. Let’s be honest, there’s not a huge professional payoff for writing essays for edited collections, in general. 

But this is a special volume. It has been the authoritative text in strategic studies for 80 years, as you’ve pointed out. It’s a compendium of some of the greatest scholars in the field over a few different generations. I was hoping that authors would be excited about signing up for it for that reason — because I certainly couldn’t pay them enough to make it rewarding in a pecuniary sense. 

I was just delighted that the vast majority of the people that I approached were willing to do it. The vast majority were excited about doing it. This is the thing that was really, really amazing. The vast majority turned in their essays in good shape and on time. I don’t say that because I wasn’t expecting good work from these people — they’re all stars. But, man, that’s usually hard when it comes to edited collections.

Jordan Schneider: There is a very cool intergenerational dialogue that is going on here. You’ve got contributors in their 80s and you’ve got contributors in their 30s as well. Aside from topic diversity, were there other diversities you were trying to build into this collection?

Hal Brands: There are a lot of different dimensions of diversity here. You mentioned one of them, which is that within this volume, we have two, maybe three different generations of scholars. At the more senior end, you have somebody like John Gaddis who’s been writing about strategy literally for half a century and does it as well as anybody else and just has an unparalleled knowledge of the field.

You have folks who are in the middle. Frank Gavin, my colleague at Johns Hopkins, who is certainly one of this generation’s preeminent extroverts on nuclear strategy, has written a couple of books about it and lent his expertise to this endeavor. 

Then, you have younger folks as well. That includes Carter Malkasian, author of the best book on the US war in Afghanistan and one of the top scholars of the post-9/11 wars more broadly. Charlie Edel, who’s roughly of my vintage, wrote about John Quincy Adams. 

There are some folks who I think view strategy in the more traditional sense in this volume, as essentially a political-military issue. Then, there’s somebody like Jason Stearns — I don’t know if he thought of himself as a scholar of strategy before he wrote this essay, but he brought a really interesting perspective on how strategy works in modern wars in Africa. 

Jordan Schneider: How do you recommend people read the book?

Hal Brands: I recommend that people start by reading the opening essay, which is by me. This isn’t just self-flattery — the opening essay helps contextualize everything that’s going to come and try to piece together some of the common threads that you can pull across 45 different essays. I’d highly recommend that they read Lawrence Freedman’s essay which explains how our understanding of strategy has evolved over time.

Then, I’d say they should read about the things that most interest them. This isn’t a book where you have to read all 1,168 pages. You can get something out of it by reading the six or seven essays on the subjects that most concern you.

Then, I’d also recommend reading an essay or two that you wouldn’t normally read, that’s outside that six or seven. That’s actually where you’ll get new insights about strategy. If you read about Mao Zedong as a strategist, or if you read about the post-Meiji generation in Japan, or you read about Soleimani and Gerasimov or whatever the case may be, even if that wasn’t what got you interested in the book in the first place, there’s a payoff there because it’ll push you to think about strategy and how it’s practiced in different ways.

Jordan Schneider: For me, the least interesting essays were the China ones, which may be the same for a lot of the listeners of ChinaTalk. Thinking about China in the context of all these other essays and historical case studies was more rewarding in my opinion. 

Hal Brands: All of the essays were chosen because they had something to inform our understanding of problems in the present. It could be that if you read a strategy about long-term competition — as seen by Jackie Fisher or Andy Marshal — it gives you some leverage on thinking about the US-China relationship today even though that’s not what the essay is really about.

It could be that an essay on the dynamics of multipolar rivalry in the early modern European system gives you some purchase on the dynamics of diplomacy in our current era. This is meant to be a book where you can find the relevance in pretty much any essay you read, even if the parallels aren’t directly drawn. You want the thing to stand on its own. You want people to be able to profitably read it 10 years from now, but it should also speak to the problems that people have in mind when they dip into a book like this.

Jordan Schneider: That’s an interesting way to read it — read the essays you’re interested in, but also read the essay that seems least interesting to you. For me, I gotta say — the title of the essay “French Strategies of Equilibrium in the 17th Century” didn’t necessarily do it for me. But there is some cool stuff in there! These are total weirdos. It’s a really different context, but also not 100% different, because it’s still people, it’s still states, and they’re still subject to their own constraints and opportunities.

Hal Brands: There’s that one, which is a great example of something where the relevance may not be immediately significant when you read the title. As you get into it, there is deep significance for understanding the challenges we face today. 

You already mentioned the essay on Tecumseh where that’s the case. Mike Morgan, who was a professor at UNC Chapel Hill (and also happened to be my grad school roommate) has an essay on ideal politics or strategies of liberal transformation, how people have thought about the role of liberal ideas in taming and transforming international competition over time, that you can’t help but see echoes of that in post-Cold War American statecraft.

Jordan Schneider: You mentioned that you were trying to write for something that will still be impactful in 20 years. There are not a lot of incentives in contemporary academia pushing people toward projects like that. 

Hal Brands: Well, in history, it’s different. The nice thing about writing history is that in most cases you’re not shooting at a moving target. 

We know how World War II ended. You should be able to write something about World War II that stands the test of time if you do it well, and that people can profitably pick up 10, 20, or 30 years down the road. In fact, I’m working on a project that has a chapter about World War II. One of the best books that I’ve read on the subject was published in 1968. That’s definitely possible.

It obviously becomes harder the closer you get to the present. That is an unavoidable dilemma. You can see it, by the way, in all of the volumes in this franchise. We talked about the Hitler essay, an essay on Japanese strategy in the first volume, which cuts off in the middle of the war as just things are getting really interesting. The essay by Condi Rice on soviet strategy in the second volume that leaves you hanging, as you mentioned, five years before the Soviet Union itself comes to an end. There are essays in this volume. We mentioned the essay on Xi Jinping, the essay on the Kim Dynasty in North Korea. 

I have no doubt that people are going to be able to read those profitably a number of years from now. Stuff’s going to happen, and they will become dated over time. At some point, somebody will feel it necessary to do a fourth volume of Makers of Modern Strategy. I’m sure that’ll be an interesting one as well.

Jordan Schneider: One of the most surreal essays was “Dilemmas of Dominance: American Strategy from George H.W. Bush to Barack Obama” by Chris Griffin. I lived through most of that history. I don’t want to think that I’m that old, but I vividly remember the start of Bush II’s Iraq war. As someone who’s been reading news obsessively ever since then, it is so surreal to see 20-30 years of history that I personally experienced just slimmed down into just 25 pages.

Unipolarity was, as identified by Krauthammer, a ­matter of fact. It was the product of the wave of events that left the United States a solitary superpower, bolstered by the resilience of its Cold War-era alliances, an increasingly liberalized world economy, expanding democ­ratization, and the implausibility of any near-­term peer competitors. The fact of unipolarity presented Bush and his successors with a fundamental, unexpected question: how should the United States exercise its newfound dominance in the international system?

[The New Makers of Modern Strategy, p. 870]

That seemed to be a particularly difficult one, especially, as you said, how archives are going to be open, and people are going to reevaluate all of the judgments that have been made, particularly over something that’s so recent.

Hal Brands: I will give a special word of thanks to the author of that piece, Chris Griffin, who now basically plays the role in strategic studies that Carnegie played for it in the 1930s and 1940s. His day job is with the Smith Richardson Foundation, which has funded just amazing work on a variety of strategic style-to-use topics over the years. There’s no conflict of interest. They did not fund this project. Chris was chosen entirely on the merits, but they deserve recognition for the work that they have done in this field. 

What’s interesting about Chris’ essay is that it helps us understand the degree to which primacy, as much as it was a strategy, was a condition that gave rise to various habits in American foreign policy. Some of those habits were good. Some of those habits were bad. A lot of those habits persisted across multiple American presidential administrations. 

The point that Chris makes, which I agree with, is that there was more continuity across post-Cold War American statecraft than we often think, in terms of what international system the United States was trying to bring about, in terms of what it thought threatened that international system and in terms of a shared commitment over a period of at least 25 years to trying to lock in as much of the good stuff, the spread of democracy, the US military advantage over any rivals, the promotion of globalization that followed the end of the Cold War. 

We at least have enough perspective on this period. We can look at it over a generation plus to be able to see some of the continuities between administrations and evaluate the period as a whole.

Jordan Schneider: It’s a particularly tricky one to write, because everyone who was in those positions or writing books about every topic at a time is going to have a take that isn’t necessarily the one that they want to be enshrined in Makers of Modern Strategy lore for the next 30 years. Anyways, brave effort by him to try to synthesize all those presidents.

After you get the drafts, to what extent did you try to have them have a coherent tone, and put them in dialogue with one another? What was the back and forth between you and the writers?

Hal Brands: Well, I was downright fanatical on the length of the essays, because pretty early in the process, my editor at Princeton told me that if we got beyond 1,199 pages, and the book is pretty close to that, the spine would quite literally crack, and you wouldn’t have a book anymore. You’d have two separate unbound books at that point. That was one area where I definitely weighed in. 

Look, all of the people who contributed to this volume are really distinguished thinkers, writers, and scholars. You don’t want to have a heavy hand in dealing with the stuff they produce. I tried not to mess with the tone of the essays. I certainly tried not to mess with the conclusions of the essays.

There were a couple of cases where I suggested, “Hey, you might consider this dimension of the problem,” simply because I had a degree of familiarity with the thing that people were writing. There are areas where I suggested trims to try to get it down length. There were a few areas where we went back and forth a little bit on not so much directly going into conversation with other essays. The John Gaddis’ essay at the end of the book is really the only one that does that explicitly. Just teasing out key dynamics that I knew were going to be present through chunks of the volume, because I had read all of the pieces in a way that nobody else had.

Again, when you’re dealing with a group of contributors this prominent and this good, the less meddling you do, the better.

Jordan Schneider: There’s a famous story with Robert Caro and Bob Gottlieb in the first edition — or the first book he wrote on Robert Moses, where the first draft was so long that they ran up against the spine problem. In the latest movie, they talk about how cutting down chapters to make it into one volume is one of the biggest regrets of their life.

What’s wrong with doing two volumes? How did you land at the page limit and the amount of topics?

Hal Brands: I’m really a stickler for brevity. I’ve rarely read a 17,000-word essay that wouldn’t have been better as a 14,000-word essay or an 11,000-word essay. I say that as somebody who’s written some 17,000-word essays.

My view was that you could cover most of these subjects with adequate nuance and with adequate depth at 10,000 words, and that readers would get more out of that because they’d be more likely to actually read all of it than they would be if the essays were 20,000 words long. 

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I love the first volume. I love the second volume. If I have one critique of the second volume in particular, it’s that some of the essays are really, really long and become a little bit difficult for non-expert readers to get through. That was a problem I was determined to avoid. Virtually all of the contributors were on board with that in one way or another. It really turned out not to be a huge issue. I actually think the book is better for it.

Jordan Schneider: Why’d you do this alone? This couldn’t have been the plan from the beginning, was it?

Hal Brands: No, this was not the plan from the beginning. I was initially going to have two co-conspirators in this project. One, is Frank Gavin, my very good friend and colleague at Johns Hopkins, who runs the Henry Kissinger Center there. The other, Eliot Cohen, also of Johns Hopkins, SAIS, was the dean of the school at the time that we were putting those together. 

There’s no real story behind why neither of them ended up doing it. They both just ended up with a variety of other commitments that made this hard to do.

Eliot was trying to put the finishing touches on his book about Shakespeare and power.

Frank was putting the finishing touches on two books, one of which was Nuclear Weapons and American Grand Strategy.

Fortunately, Frank was able to contribute to the volume. He wrote a remarkable, idiosyncratic, deeply insightful essay on the perplexities of nuclear strategy, which I think people are going to be getting a lot out of for many years to come.

Jordan Schneider: Let’s talk a little bit about the Gaddis essay. What was the origin? Why do you think it was so cool?

Hal Brands: John Gaddis was the hardest to get of all of the contributors, despite the fact that he was my dissertation advisor, or maybe because of the fact that he was my dissertation advisor. The calculation was he had already done his part for me and didn’t need to help with this one. In all seriousness, I did finally get him to agree to do it.

What he was really interested in doing was writing a reflection on all of the essays in the volume and explaining them in the context of the larger craft of strategy.

John was an eminently good sport in all of this. As soon as I got the first drafts of the essays, I would read them, mark them up, and send them to John. John would read them and, as we were rushing to get the volume ready, wrote his own essay on this. 

His essay covers 2,500 years of history — everybody from Pericles to Putin is in the essay. It does the quintessential John Gaddis thing, where there are four amazing insights per page, and you feel you want to stop and think about the first one, but you’re already on to the second one and the third one and so forth. 

It’s maybe 7,000 words. It’s not a particularly long essay, but it’s a really fitting summation of a lot of the insight and wisdom that the other contributors brought to the volume. It’s also a summation of what John has learned and taught us about strategy over a 50-plus-year career studying it. I felt very privileged to get him involved with the project, because I just couldn’t think of anybody better to bring the volume to a conclusion.

Jordan Schneider: Hal, do you have any thoughts or observations of the upcoming generation of scholars, and where their interests are? Where the field is going and what might be different in the 2040 version?

Hal Brands: One thing that might be different is that none of the people in the 2040 version are going to work in history departments. The reason for that is that the discipline of history as it’s practiced in academia has just changed a lot over the past 40 or 50 years. 

I would guess that the percentage of contributors to this volume who work in history departments is lower than it was in the 1986 volume, for instance, because the people who study decision making, statecraft, war, and peace — are now as likely to be found in professional military education institutions, political science departments, policy schools, and think tanks as they are likely to be found in traditional history departments. 

That trend will continue. I don’t know that it’s necessarily a bad thing. Diplomatic and military history, while they haven’t exactly flourished within history departments in the last 40 years, have flourished in these other spaces. 

The makeup of the next generation may be a little bit different. Of course, the issues that they’re preoccupied with and the experiences that they bring to the task will be different as well. If you were writing for the first volume, you were drafting your essay at the end of 1941, you would live through some serious history over the past five years. That shaped almost everyone’s approach to the task. 

Same thing. There’s a different set of histories that the people who contributed to this volume lived through. That’d be the same with the next volume as well.

Jordan Schneider: Maybe this gets to the one critique I’d have of the essay collection. One thing that I think really weighed heavily on the 1943 one was the weight of the technological machine age transformation that allowed a world war to happen in the first place. 

In the second edition, you had the invention of the nuclear bomb as something that hovered over everything. 

My expectation is the 2050 edition will have a number of essays about cyber attacks, AI, quantum computing, or technological changes that aren’t even on our radar yet. 

Hal Brands: Haha, the next volume would just be written by different versions of ChatGPT. The revolution will come in a different way. 

We do have an essay in this volume, which is one of the more provocative ones by Josh Rovner at American University, which basically says, “None of this stuff is as revolutionary as you think. New technologies come, new technologies go. We always think they’re going to revolutionize warfare and grand strategy. They typically revolutionize it less than we think. Then, the next set of technologies comes on.” 

Now, it’s provocative, and people will argue with that thesis. What Josh is doing is exactly in the spirit of the volume, which is trying to historicize the debates that we’re having about cyber and AI and quantum today by looking at how previous technological step-changes have and haven’t changed the practice of strategy.

Jordan Schneider: Do you worry that the field of history, as it aspires to be timeless and everlasting, creates a biased preference for researchers who don’t internalize big technological changes? 

Hal Brands: Josh isn’t a historian, he’s a political scientist. We let him in anyway. He did a great job.

Jordan Schneider: Last question — how did you reconcile the goal of decentering the US if Americans were also the target audience of the book? 

Hal Brands: I’m not sure that America is the target audience, actually. I try to be transparent about my motives and what excites me about doing this volume, which is to help citizens of the democratic world be better at doing strategy because it matters for our future. 

It matters in the present moment, as the democratic hegemony that we became accustomed to after the end of the Cold War is by no means guaranteed. I want the book to help the democracies of the world understand strategy better.

Strategists in Russia or Iran could probably learn something from reading this book. There is something universal about the challenge of strategy, even though every strategic dilemma has its own characteristics.

I would also say that the choice of chapters in the book is deliberate in the sense that it’s meant to get away from the transatlantic focus of the first volume, less so in the second volume. There’s an essay about Tecumseh. There’s an essay about Russian and German strategies under Hitler and Stalin. There are multiple essays about China, essays about Japan, and the Middle East, and strategies of nonviolent resistance India.

You’re right that the US is more at the center of the story than probably any other country. In that respect, the focus of the book is just an artifact of the part of history that it looks at.

Jordan Schneider: Folks, this was not a sponsored episode. I just think this book and this collection is really fantastic. It’s hard for me to imagine a listener to ChinaTalk that’s interested in the sorts of topics that I cover week to week that wouldn’t really enjoy and find this volume valuable. Really encourage you all to check it out and let me know what you think about it.

It might be cool to do some follow-ups if there’s particular audience feedback on a handful of the essays to maybe get a little panel of contributors together. 

I do want to close, Hal, with a line that you had in your introductory essay. You say that, “If history is an imperfect teacher, it’s still the best we have. History is the only place we can go to study what virtues have made for good strategies and what vices have produced bad ones. The study of history lets us expand our knowledge beyond what we have personally experienced, thereby making even the most unprecedented problems feel a bit less foreign. 

Indeed, the fact that strategy cannot be reduced to mathematical formulas makes such vicarious experience all the more essential. History, then, is the least costly way of sharpening the judgment and fostering the intellectual balance that successful statecraft demands. Above all, studying the past reminds us of the stakes that the fate of the world can hinge on getting strategy right.”

As we enter a scary world in 2025, think everyone would benefit from taking a moment to breathe and read some essays on Jomini, and Clausewitz, and Tecumseh and John Quincy Adams. It’s a good way to spend Sunday mornings.

Thank you so much, Hal. Thanks to all the contributors for putting together such a remarkable edition.

Hal Brands: Thanks, Jordan. It’s great to have this option to talk with you.

ChinaTalk first covered China’s algorithm registry nearly two years ago, back when it was a freshly minted, relatively untested apparatus. How has the system evolved since then? Pseudonymous contributor Bit Wise fills us in.

In July 2023, China issued binding regulations for generative AI services, which, notably, require output generated by chatbots to represent “core socialist values.” These regulations have stirred debate on how tough the Chinese government is on AI: are regulators putting “AI in chains,” or are they giving it a “helping hand”?

These debates have largely focused either on the text of the regulations or on its evolution from a stringent draft to a more lenient final version. What has received less attention is how the regulations are actually being implemented now.

Does China have a genAI licensing system?

In this post, we unpack one key enforcement tool of the Interim Measures: mandatory algorithm registrations 算法备案 and security assessments 安全评估.

Even though the algorithm registry is a central enforcement tool in China’s AI regulations, it is still relatively poorly understood. One big open question is: should we think of it as mere registration, or rather as a de-facto licensing regime?

Two leading scholars on China’s AI policy have come to essentially opposite conclusions (emphasis added):

Angela Huyue Zhang (p. 46): Lawyers have observed that many AI firms are now merely required to register their security assessment filings with local offices of the CAC, instead of obtaining a license before launching public services.

Matt Sheehan (p. 32): [I]n practice regulators began treating the registration process more like a licensing regime than a simple registration process. They did this by withholding their official acceptance of registrations until they felt satisfied with the safety and security of the models.

The two interpretations have widely different implications. A simple registration system would imply a light-touch approach to AI governance. A licensing system, on the other hand, would allow the government to control which models go online — making it a much stronger tool for social control at the moment, but potentially also a more formidable instrument for governing future frontier AI risks.

In this post, we try to get to the bottom of how the genAI registrations actually work.

A note on methodology

We have thoroughly reviewed Chinese-language official policy documents and Chinese legal analysis on the algorithm registry. To triangulate our findings, we have also spoken with several Chinese lawyers with direct experience guiding AI companies through the filing process. These interviews took place from April to June 2024. We are incredibly grateful to every one of them for their willingness to share their insights! We also thank Matt Sheehan for providing valuable feedback on a draft of this post.

Some evidence, though, remains messy, as our sources contradict each other at times. In fact, a common theme recurring throughout our sources and conversations was that the procedures are poorly formalized and constantly changing. This post won’t be the final word on how China’s algorithm registration process works.

Algorithm registry: a short history

The algorithm registry pre-dates the genAI era. It was first introduced in March 2022 with regulations for recommendation algorithms:

Article 24: Providers of algorithmic recommendation services with public opinion properties or having social mobilization capabilities shall, within 10 working days of providing services, report the provider’s name, form of service, domain of application, algorithm type, algorithm self-assessment report, content intended to be publicized, and other such information through the Internet information service algorithm filing system.

第二十四条 具有舆论属性或者社会动员能力的算法推荐服务提供者应当在提供服务之日起十个工作日内通过互联网信息服务算法备案系统填报服务提供者的名称、服务形式、应用领域、算法类型、算法自评估报告、拟公示内容等信息，履行备案手续。

The fact that filings need to be completed within 10 working days of providing services suggests that it was envisioned as a simple post-deployment registration, rather than a pre-deployment license.

The regulation also requires “security assessments” 安全评估:

Article 27: Algorithmic recommendation service providers that have public opinion properties or capacity for social mobilization shall carry out security assessments in accordance with relevant state provisions.

第二十七条 具有舆论属性或者社会动员能力的算法推荐服务提供者应当按照国家有关规定开展安全评估。

In late 2022, regulations on “deep synthesis” algorithms essentially repeated the same requirements; the only minor difference between these regulations was that they defined two separate entities: service providers 服务提供者 and technology support 技术支持者. Slightly different procedures apply to each, but both have to do algorithm registration and security assessments. In practice, one company may file the same model as both a service provider and tech support, if it offers distinct products. For example, Baidu’s ERNIE model 文心一言 has one filing as “service provider” for its consumer-facing mobile app and website, and a separate filing as “technology support” for enterprise-client-facing products.

Note: the definition of “deep synthesis” largely overlaps with that of generative AI. Hence, most generative AI models, such as ERNIE bot, actually undergo model registration under this deep-synthesis regulation.

GenAI regulations: continuity?

So what do the 2023 genAI Interim Measures say? Essentially the same thing!

Article 17: Those providing generative AI services with public opinion properties or the capacity for social mobilization shall carry out security assessments in accordance with relevant state provisions and perform formalities for the filing, modification, or canceling of filings on algorithms in accordance with the “Provisions on the Management of Algorithmic Recommendations in Internet Information Services.”

第十七条 提供具有舆论属性或者社会动员能力的生成式人工智能服务的，应当按照国家有关规定开展安全评估，并按照《互联网信息服务算法推荐管理规定》履行算法备案和变更、注销备案手续。

All of this suggests continuity: we know what this algorithm registry is from previous regulations — now we just apply the same tool for genAI services.

In reality, however, the procedures for genAI models work fundamentally differently from how they worked for other AI systems (such as recommendation algorithms) in the pre-genAI era.

The previous system is still in place, but an additional system just for genAI services has been established in parallel. Chinese lawyers describe a de-facto “dual registration system” 双备案制, consisting of

1. the original “algorithm registration” 算法备案, and

2. a new “genAI large model registration” 生成式人工智能（大语言模型）备案.1

How do the two systems work?

The new system has not replaced the old system. Rather, they co-exist in parallel. Companies typically first undergo the regular “algorithm registration.” For some, the story would end there. For some genAI products, however, authorities would then initiate the more thorough “genAI large model filing” as a next step. The scope of services affected by this additional registration process is somewhat unclear, but it generally applies to all public-facing genAI products (or, in Party speak, models with “public opinion properties or social mobilization capabilities” 具有舆论属性或者社会动员能力). Public-facing genAI includes all typical chatbots or image generators available through chat interfaces and APIs.

Information on how the two systems differ is piecemeal. But many sources confirm the same bottom line:

• The original “algorithm registration” is relatively easy and largely a formality;

• In contrast, the new “genAI large model registration” is much more difficult and actually involves multiple cycles of direct testing of the models by the authorities.

The table below summarizes the key differences.

The term “genAI large model filing” is not actually used by China’s regulators. The CAC gives only one small hint that something has changed: the filing information of genAI models is published not through the regular algorithm registry website, but through provincial-level CACs. The central CAC compiles these announcements into a separate announcement on its website,2 which is distinct from the regular algorithm registry website. This subtly hints at the fact that these are two separate systems.

As one Chinese lawyer aptly put it,

Practice started first, and then formal law-making may follow later.

Foreign AI policy analysts are also not the only ones feeling confused. As the same lawyer noted,

When more than one “security assessment” system exists at the same time, companies will inevitably be confused.

The graph below summarizes the procedure for the new “genAI large model registration”:

A company would typically start with the “regular” algorithm registration. For many models, this would be it! Public-facing products, however, would then be asked to conduct the additional genAI large language model filing. As mentioned above, there is lots of ambiguity on which models are considered “public-facing”. Some anecdotes shared by industry insiders suggest that the scope is interpreted relatively broadly in practice, and may include some products only intended for enterprise users.

Apart from submitting documentation on internal tests (which we will cover in a forthcoming post), the companies need to create test accounts for the provincial cyberspace authorities, granting them access to test the model pre-deployment. Some Chinese lawyers told us that CAC has outsourced these tests to third-party agencies, but we do not have any insight into which institutions these are. The process can involve multiple rounds of renewed fine-tuning until the CAC is satisfied with how the model behaves.

There is no official information on what the CAC (or its endorsed third-party institutions) actually tests in these inspections. All insiders we talked to, however, agreed that content security will be front and center.

Oversight may have evolved beyond a one-time licensing process to a more dynamic approach, similar to how the PRC regulates online content generally. It appears there is ongoing communication between the CAC and AI service providers even after a model went online, mirroring the relationship between regulators and traditional online content platforms.

As mentioned before, some details remain confusing, as different sources contradict each other. For instance, there is conflicting information on whether companies themselves initiate the process, or whether it always starts from a CAC request after the regular model registration. There is also conflicting information on the role of provincial CACs. Some sources claim that they conduct tests on their own, while others claim that they just forward documents to the central CAC. It is possible that both claims are true and that it differs by province, but this is speculation.

Changes in the making?

A running theme throughout all our sources and conversations was that the new processes are still poorly formalized and constantly changing. What happened to one company may be different from what happened to another; what happened three months ago may be different from what happens now.

One Chinese lawyer told us that the CAC struggles to keep up with the large number of filings, so the agency is considering a risk-based categorization, after which only a smaller number of high-risk models would have to undergo the more thorough registration process. This would be a familiar story: in spring 2024, the CAC relaxed data-export security assessments because, among other reasons, the authorities could not keep up with the large number of applications.

There are no official details on when or whether such ideas may become reality for genAI registrations. In August 2024, however, CAC head Zhuang Rongwen 庄荣文 proclaimed that CAC would “adhere to inclusive and prudent yet agile governance, optimize the filing process for large models, reduce compliance costs for enterprises” 坚持包容审慎和敏捷治理，优化大模型备案流程，降低企业合规成本 and “improve the safety standard system in aspects such as classification and grading” 在分类分级、安全测试、应急响应等方面丰富完善安全标准体系. This shows that regulators are still actively exploring ways to tweak the algorithm registration process.

How hard is it to get through this process?

According to CAC, as of August 2024, 190 models have filed successfully. There is no good data on how many models have not passed the filing process; the government releases only successful filings, not failed ones. As one of the lawyers we spoke to pointed out, it is not even really possible to “fail” the process. If you do not pass, you adjust your model and try again. Some companies, though, might get caught up in this circular process for a long time.

In May 2024, China tech news outlet 36kr estimated that there are 305 models in China, of which only around 45% had successfully registered at the time. This rate doesn’t necessarily imply that the other models have failed their applications. For instance, 60 of the 305 models have been developed by academic research institutions; it’s possible that those institutions never intended to put them online in the first place, and thus never tried filing.

Implications

The main goal of this post was simply to provide insight into how algorithm registrations for genAI products in the PRC work right now. But what does it all mean for China’s AI industry? What does it mean for AI safety?

It is clear that Chinese regulators get pre-deployment access to genAI products, and can block them from going online if they are not satisfied with content control or other safety issues. This may mean that,

• The enforcement of China’s genAI regulations is somewhat stricter than that of previous AI regulations, such as those for recommendation algorithms — suggesting the PRC sees a greater threat in genAI compared to previous AI systems;

• Regulatory hurdles for providing public-facing end-user products are significantly higher than for enterprise-facing products. It’s possible that some companies will increasingly focus on B2B rather than B2C, or launch products overseas first while waiting for filing results in China.

Much more to cover

As part of the “genAI large model registration,” AI companies need to submit a number of attachments, such as

• Appendix 1: Security Self-Assessment Report 安全自评估报告

• Appendix 2: Model Service Agreement 模型服务协议

• Appendix 3: Data Annotation Rules 语料标注规则

• Appendix 4: Keyword Blocking List 关键词拦截列表

• Appendix 5: Evaluation Test Question Set 评估测试题集

The state has published detailed technical guidelines for these. In our next post, we will make a deep-dive explainer of the technical AI standard that covers the processes for Appendix 3, 4, and 5. So keep an eye out on your inbox!

To discuss the Department of Justice’s new proposed rule on data security, we interviewed two brilliant guests from the ChinaTalk Hall of Fame — DOJ National Security Division attorneys Lee Licata and Devin DeBacker.

Before DOJ, Lee was an attorney at DHS and then CBP, while Devin was a partner at Kirkland & Ellis and then worked with the Office of White House Counsel. Today we’ll be discussing the DOJ’s new proposed rule on data security. 

Have a listen on Spotify and Apple Podcasts.

We get into…

• DOJ’s plan to protect your data from foreign adversaries,

• How public comments have shaped the proposed rule since the last time we interviewed Lee and Devin,

• DOJ’s tools for enforcing corporate compliance,

• The differences between data security regulations, privacy laws, and export controls,

• Why some public comments get accepted and some get rejected,

• The DOJ playbook for assembling a dream team of talented bureaucrats.

Shutting the Front Door

Nicholas Welch: Lee and Devin, welcome back to ChinaTalk.

Devin DeBacker: Happy to be back. As repeat guests on ChinaTalk, are we eligible for a plaque or some kind of award? 

Nicholas Welch: You know, I’m not in charge of funding — you’ll have to ask the dictator of ChinaTalk once he’s back from paternity leave. But your request — like the many requests you likely receive in the notice and comment period — is duly noted. 

For those who missed the show back in April, here’s the context — back in February, there was an executive order focused on preventing foreign access to Americans’ bulk sensitive personal data and US Government-related data by countries of concern. This was followed by an advance notice of proposed rulemaking (ANPRM). Now, we are in a period of notice of proposed rulemaking (NPRM), one step closer to the final rule.

Can you give us a 40,000-foot view of this executive order and the proposed rule? What national security risks are they aiming to address?

Devin DeBacker:  The audience might be wondering, “What are these 422 pages of regulatory detritus all about?” 

The primary risk we’re addressing here is the national security threat posed when foreign adversaries or their intelligence agencies access Americans’ sensitive personal data. Such data can be exploited, weaponized, and turned against our national interests in various ways. For instance, adversaries can use geolocation data to track and monitor Americans, or health and financial data to identify vices and vulnerabilities in individuals’ lives, such as behavioral patterns and daily routines. This data can be weaponized to surveil, blackmail, intimidate, or otherwise influence those individuals — whether targeting specific people or analyzing broader population insights. This rule aims to address and mitigate these kinds of threats.

Nicholas Welch: This rule isn’t addressing, say, an intelligence agency hacking in through the back door to steal information. You’re talking about data on the open market that could be purchased by anyone, right?

Devin DeBacker: Exactly. The “front door, back door, and side door” analogy works well here. We’ve got a “barn full of data” on Americans, and we’re trying to close the front door with this rule.

Other mechanisms and tools (especially from DOJ and other agencies) are in place to close the back door.

But we can’t leave any doors open, and the front door has been wide open for a long time. It’s been advertised almost as a free-for-all.

This rule aims to close that front door. Legally speaking, this covers legitimate or lawful commercial transactions where foreign adversaries can access data — either by buying it on the open market or through vendors, employees, or investors who can leverage it through their country’s political or legal systems.

Nicholas Welch: Where does this rule fit in the broader sanctions and export control framework? How does it contribute to the ongoing discussion about the intersection of national security and economic security? Is it similar or different from semiconductor export controls?

Lee Licata: Good question. There are aspects of this rule that resemble the Office of Foreign Assets Control (OFAC) and our export controls regime. This rule seeks to move beyond a case-by-case approach as we see with CFIUS, Team Telecom, or even some of the Commerce ICTS Authority actions, which often look at specific transactions or entities. Instead, it takes a more systemic or holistic approach across holders of this kind of data. The idea is to implement prohibitions and restrictions similar to an OFAC regime. It includes features like advisory opinions and licensing options, which are standard in such regimes. We see this as a foundational step toward a more comprehensive framework.

Devin DeBacker: Zooming out a bit, there are key assets in the US that we want to protect from falling into the wrong hands. Sometimes it’s technology, sometimes capital — we don’t want money flowing to terrorists, for instance. In certain cases, we want to prevent not just capital, but also the know-how that accompanies it from reaching critical sectors of emerging technology. Likewise, we want to protect sensitive American data from misuse. Each of these regimes — export controls, sanctions, outbound investment, and now this data security program — addresses a distinct part of that problem, forming a suite of tools in our national security toolbox.

Restricted Transactions and Covered Persons

Nicholas Welch: Let’s dig into the specifics. The rule says a “US Person” cannot engage in a “restricted transaction” with a “covered person.” What do these terms mean exactly?

Devin DeBacker: The program outlines certain covered data transactions that US Persons either cannot engage in or must engage with restrictions, particularly with countries of concern or covered persons. I’ll let Lee explain the specifics since he’s the architect of this framework.

Lee Licata: Let’s start with the prohibitions. Two types of commercial transactions between a US Person and a “country of concern” or “covered person” are outright prohibited. The first type is data brokerage, and the second type is transfers of genomic data or biospecimens, which is the raw material from which genomic data is derived.

We also impose restrictions in three categories — vendor agreements, employment agreements, and investment agreements that aren’t passive.

For these restricted agreements, we aim to put a box around these transactions to control how they’re conducted. Essentially, certain security measures must be in place to prevent countries of concern or covered persons from accessing sensitive data. These security measures, issued by the Cybersecurity and Infrastructure Security Agency (CISA) at the Department of Homeland Security, were published alongside our proposed rule. They include organizational security requirements, such as having a security officer, system-level security measures, and data-level protections like encryption and anonymization techniques.

Regarding who qualifies as a covered person and countries of concern, we’ve designated six countries — China, Russia, North Korea, Cuba, Venezuela, and Iran. Covered persons fall into four main categories — entities headquartered in or owned by a country of concern, entities owned by other covered persons, entities or individuals working for covered persons, and those predominantly residing in a country of concern. There’s also a fifth catch-all category for those acting on behalf of a country of concern — think proxies, cutouts, or shell entities. Essentially, we’re structuring this like an OFAC regime.

Nicholas Welch: Lawyers sure do love catch-all categories at the end of statutes!

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Tools of Enforcement and the Impact of Public Comments

Nicholas Welch: What does this rule’s compliance and enforcement regime look like? I see due diligence obligations, a licensing regime, annual reports, and even requirements to disclose when a US Person rejects a solicitation to transfer restricted data to a covered person. What should companies anticipate as DOJ finalizes this rule?

Lee Licata: First, we encourage companies to consider submitting comments on the docket during this finalization phase. Their input is vital for us to understand how this will be implemented and what impacts might arise.

Devin DeBacker: The more specific, the better. It helps us to understand the exact types of transactions companies engage in and whether their interpretation of the rule aligns with ours so we can clarify as needed.

Lee Licata: The comment period is 30 days and ends on November 29, 2024. Beyond comments, we want companies to start evaluating their risk profiles concerning these rules. Companies need to understand what data they hold, especially sensitive data regulated here, and the nature of commercial relationships that could involve a covered person or country of concern. They should also identify who has access to that data and what security measures they have in place to protect it.

The compliance and enforcement regime includes features common in export controls or OFAC frameworks — recordkeeping requirements, annual reporting, and reporting rejected transactions, similar to OFAC sanctions. We also require audits for restricted transactions to ensure security measures are in place. Entities must have policies governing compliance with these rules. Lastly, this is an IEEPA-based executive order, so DOJ can leverage IEEPA’s enforcement tools, including criminal prosecution and civil penalties. The rule outlines thresholds for civil penalties and allows us to notify entities of violations without financial penalties, though we’ll make sure they’re aware of their transgressions. This entire framework is about orienting entities to understand their risks and ensuring they take action.

Devin DeBacker: To take a broader view, our compliance approach is similar to that of sanctions programs. Most companies will need an in-house compliance program tailored to their specific risk profile — who they do business with, where, and in what sectors. While some restricted transactions can proceed with terms and conditions, generally, we focus on compliance first. DOJ sees corporate compliance, especially in national security, as a priority. Companies are on the front lines — they hold the data, technology, or capital we’re concerned about. We need them as partners to understand and uphold their obligations. But DOJ is also prepared to use its enforcement tools when necessary. At the end of the day, what matters isn’t the 422 pages of the proposed rule but how it works in practice to protect against these risks.

Nicholas Welch: Let’s say I’m Company X. I read this rule and think, “Wow, this will be massively expensive. I don’t want another compliance regime.” How will the DOJ know if I violate the rule? Will the DOJ really find out?

Devin DeBacker: Oh, we’ll find out. Corporate compliance is our bread and butter, especially in the Foreign Investment Review Section, where this program resides.

My team focuses solely on compliance and enforcement every day, around the clock. We also have the FBI, which excels at investigating violations — whether it’s sanctions, export controls, or this program. Additionally, we have public tips, recordkeeping requirements, and reports that help us follow up and investigate. For companies with higher risk profiles, we can inspect their records and ensure compliance interpretations align. The other key point is that one person can’t engage in a transaction alone — there’s always another party, so if one doesn’t report, the other often does.

Nicholas Welch: Industry, you’ve been warned! From what I’ve read, you engaged in a lot of public feedback. I noticed in the notice of proposed rulemaking that the department even discussed the order with stakeholders at public events, including China Talk. So, if other podcasters want good press, they should invite DOJ lawyers on their shows! There were 114 questions in DOJ’s ANPRM. What were the biggest changes to the rule based on comments and engagements?

Lee Licata: As you mentioned, we received about 70 comments during the ANPRM period, along with feedback from over 100 organizations, companies, trade associations, civil society members, academics — the whole spectrum of regulated communities. We didn’t receive any catastrophic warnings about breaking the internet or collapsing the economy, but we did get a lot of valuable, acute policy input to ensure the rule is implementable without unintended economic consequences.

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Some new elements include an analysis of the six countries of concern, bulk data thresholds, and a detailed assessment of data characteristics. We’ve also conducted an economic impact assessment, estimating compliance costs based on studies like GDPR and other due diligence activities. There are specific exemptions for telecommunications, FDA-regulated clinical trials, and data transfers for post-market approval in regulated sectors. We also clarified financial services exemptions to avoid hidden economic decoupling and specified back-office intra-corporate transfers.

Nicholas Welch: How does the industry feel about this rule? Is DOJ expecting millions in lobbying against it, or does industry seem more receptive?

Lee Licata: It’s early, but the industry seems to understand the issue we’re addressing. No one disputes that adversarial nations are actively seeking American data, and this is a legitimate national security threat. Industry representatives are trying to understand compliance obligations and what this means for their transactions. They provided helpful feedback on policy specifics, though we haven’t seen anyone suggesting it would dramatically impact the economy. Stakeholders seem to be grasping that compliance will be necessary and are evaluating their risk exposure. They’ll advocate for their industries, but the input we’ve received has been useful.

Devin DeBacker: We’ve continued public engagements during this comment period, similar to the ANPRM in spring. We’re open to feedback about specific transactions or scenarios where this rule might have unique implications. We’ve already met with over 200 groups in this short comment period, so it’s a broad, cross-sector engagement. We’re here to listen.

Nicholas Welch: Maybe this is a bit technical, but the rule mentions that several commenters suggested incorporating aspects of international or state privacy laws. DOJ decided against that, stating privacy protections and national security measures have different objectives. Can you clarify why?

Lee Licata: Sure, two examples come to mind. First, most state privacy laws define “precise geolocation data” using an 1850-foot distance from the device — a standard not actually supported by device technology. Major operating systems generally use either 1,000 or 10,000 meters to measure precise geolocation data. We chose 1,000 meters to align with how data is collected and to ensure consistency with real technology practices.

Second, state privacy laws cover all “PII” (personally identifiable information), including basic, public information like names and addresses. Our goal isn’t to regulate the phone book but rather to focus on information that adversaries could exploit. We created a narrower category called “covered personal identifiers,” targeting data combinations like a name and Social Security number or IP address and device identifier, as these combinations could uniquely identify someone. This approach focuses on specific national security risks, departing from broader privacy law constructs.

Devin DeBacker: Another example relates to a consent-based exception. Some commentators suggested we allow cross-border data transfers if individuals consent. From a privacy perspective, which emphasizes individual control over data, this makes sense. But in national security, we’re more concerned about the broader externalities created by individual and company choices.

We don’t have a consent-based exception for export controls. We don’t say that sensitive technology can go to Iran or North Korea with a company’s permission.

Privacy and national security laws serve different objectives, so they complement each other but don’t always align.

Nicholas Welch: Data, unlike semiconductors, moves easily and can be routed through various entities. If US Company A sells data to Company B, which eventually passes it to an adversary, how does the rule address the risk of onward data transfers?

Devin DeBacker: There are two parts to this. As Lee said, we designed the program to balance obligations on US companies. We don’t impose “pass-through liability” — US Company A isn’t responsible for tracking data through every layer, down to whether the data eventually reaches a covered person. However, we’ve addressed the resale and re-export risk by requiring US companies to include a contractual restriction with third-party buyers, preventing them from reselling to a country of concern or covered person. This “trusted data flows” concept allows third parties within the trusted framework.

If a third party violates the restriction, US companies must report it to us. If necessary, we can publicly designate those violating entities as “covered persons.” This approach strengthens trust-based data flows by identifying who falls within or outside the trusted framework.

Nicholas Welch:  Before this rule, did any executive branch mechanism address these specific national security risks?

Devin DeBacker: Yes, sort of — this concept emerged from our experience with transaction-specific authorities, like CFIUS and Team Telecom, which assess individual foreign investment risks. However, as data security threats evolved, we noticed we were addressing similar data security risks repeatedly in foreign investment cases, each time creating tailored compliance solutions. Seeing this pattern, we decided to create a comprehensive, systematic program to address these recurring risks. We still have case-specific authorities, and this program complements them by reducing regulatory duplication.

Why DOJ?

Nicholas Welch: On the last show, you mentioned that the DOJ is a natural fit for this role because you’re highly experienced in corporate compliance. You also said you’re expanding the Foreign Investment Review section, hiring more attorneys and non-attorneys. How is that team expansion going? More broadly, what did interagency collaboration look like for this rule? I assume you had extensive interagency support from Team Telecom, Commerce, DOD, and FTC — but ultimately, the DOJ took the byline for this rule. This is hosted on justice.gov, not another agency’s website. Does that impact the rule’s effect or corporate compliance overall?

Lee Licata: Yes, absolutely. First, stepping back, it took us two and a half years to develop this concept for the executive order and then to draft the proposed rule. Throughout that time, we coordinated with around two dozen federal departments and agencies, as well as White House offices, to build this framework and ensure that all relevant interests within the executive branch were represented.

The interagency coordination was extensive, involving entities like CPS, Team Telecom, the ICTS team at Commerce, CFPB, FTC, and SEC — essentially, every regulator overseeing commercial transactions involving the regulated data. We also engaged continuously with OFAC, BIS, and FARA to incorporate similar concepts and ensure compatibility within our program.

The DOJ byline is indeed significant. As Devin mentioned, corporate compliance and enforcement are central to our work — it’s right there in our name, the Department of Justice. So it’s natural for this rule to land here, combining DOJ’s expertise in this risk area with the department’s enforcement mission. In the interim, as we establish this program, we’re building a team within FIRS to finalize the rulemaking and begin implementation. We’ve assembled a team of mostly interagency detailees to bring together the necessary expertise. As of now, we have 11 attorneys plus paralegals, targeters, and other support, and we’re leveraging insights from across the interagency. We have team members from OFAC, FinCEN, BIS, and the Department of Defense, among others, all working under our roof. By the end of the year, we expect to have about 17 people forming the foundation of a full-fledged team.

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Nicholas Welch: Where do you see this rule going in the future? Financial industries, for instance, face multibillion-dollar fines and have strong compliance frameworks, but with newer regulations like chip export controls, we’re only starting to see big penalties, like Seagate’s $300 million fine from BIS [and a $500m fine on GlobalFoundries]. Recently, a TSMC chip was found in Huawei, which journalists quickly identified as a supply chain weak link. Chris Miller suggests chip companies need to spend more on compliance, and governments should impose stricter penalties. So where do you see data security compliance going?

Devin DeBacker: As my boss, Assistant Attorney General Matt Olsen, said back in March, this program needs to have “real teeth.” Our primary approach is through compliance. We want companies to fully understand their obligations, have strong programs in place, protect data, and follow the rule, especially with security requirements for restricted transactions. Our main goal is to educate US companies and individuals on these obligations.

If enforcement becomes necessary, however, penalties need to be meaningful — they must impact a business enough to reinforce compliance obligations. More than the size of the penalties, though, what's critical is for companies to understand that compliance can’t be an afterthought — it has to be integrated into the business itself. Compliance teams need to be part of business decision-making, not separate from it. For example, if a company is considering opening an office in Shanghai, storing geolocation data on servers there, and hiring covered persons, that decision-making process must include compliance with US government rules. This needs to be part of the broader business risk assessment.

As Lee mentioned, companies need to ask questions like: Where are our offices? What data do we hold? Where is it accessible? What safeguards are in place? Who has access, and what kind of system-level access do they have? Compliance isn’t about merely ticking a box — it has to be woven into the business itself.

Nicholas Welch: Sounds comprehensive! You’ve done an extensive job of justifying this rule based on statutory authority, like Article II in the Constitution, Section 301, IEEPA. Do you think Congress would be better suited to address this risk legislatively rather than through an IEEPA-based executive order?

Devin DeBacker: IEEPA is intentionally broad, and this rulemaking is consistent with typical IEEPA-based rulemakings, which regulate commercial transactions and cross-border activities. This program can and should stand independently, without Congressional involvement. That said, we’ve worked well with Congress, discussing ways to clarify aspects of IEEPA, like the Berman Amendment, and ensuring long-term resources for this program. 

What’s promising is that this area — protecting sensitive US data from foreign adversaries — has broad bipartisan recognition across parties, administrations, and Congress. I believe this will remain a priority across the government, and I’m optimistic this program will become a lasting element of our national security framework in the US.

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We’ve got a guest column by the great . His personal blog is The Scholar’s Stage and he also runs the excellent Center for Strategic Translation. This article was originally published by the Foreign Policy Research Institute on October 29, 2024.

Last week, the Wall Street Journal editorial board asked Donald Trump why China would not invade Taiwan on his watch. Trump told the Journal that the Chinese would not dare to invade. As Trump put it: “[Xi Jinping] knows that I am f—ing crazy.”

One must pity the Chinese analyst asked to predict what a second Trump administration will mean for U.S.-Chinese relations. Like Richard Nixon before him, Trump is ready to play the lunatic; he clearly believes that the less predictable he is to the Chinese, the better off America will be. Though China occupies a central place in Trump’s campaign rhetoric, his campaign has not published or endorsed any detailed China policy proposals. The actions of the last Trump administration do not provide a better guide. Divided by infighting, its China policy was not consistent. At times, Trump’s foreign policy swung wildly as specific individuals rose or fell from his favor. Things do not get much easier if one looks at the views of the politicians and policy wonks that Trump would call on in a second administration. Their views are varied. Among Trump’s closest allies, we find fundamental disagreements on the proper ends and proper means of American strategy toward China.

Given these hurdles. I will not try to predict the path a second Trump administration might tread. It seems more useful to lay out a few observations on the different schools of thought now contending for leadership of that policy. My observations are shaped by the dozens of interviews I have conducted over the last two months with Republican staffers, think tankers, and former officials. A longer and more thorough report of my findings will be published by FPRI later this year. This is a pre-election preview.

The questions that divided Republicans in 2017 are not the questions that will divide them in 2025. Trump’s election shattered a policy consensus shared by the leaders of both parties for the better part of four decades. Many of the architects of this consensus were still influential during Trump’s first years in office. On the other hand, many who rejected “engagement” with China had spent years exiled from power. Others were completely new to service in the executive branch. This was a diverse group who did not all reject engagement for the same reasons. These differences were not initially apparent, as their objections were too marginal to the pre-Trump policy debates for much scrutiny to be given to them. Nor was it immediately apparent to these officials where the new bounds of public opinion or presidential approval lay. Thrust into power quite suddenly, they were forced to improvise as they went—and improvise again as the Chinese reaction to Trump’s trade war changed the context in which they worked. All of these factors gave China policy under Trump 1.0 an unusually chaotic flavor.

None of these conditions hold this election season. The architects of engagement are no longer relevant. A tough line on China is now taken as a starting point for all factions involved. Over the last eight years, a new ecosystem of conservative think tanks, policy journals, and Congressional offices has sprouted up to provide Trumpism with the intellectual coherence it lacked in 2017. Policy proposals are now numerous and detailed. Out of power, former Trump officials have had the time to carefully lay out their vision for American strategy in Asia. They have done this in speeches, policy reports, and full-length books. Disagreements between their different schools of thought are formally debated on both panels and podcasts.

Points of Consensus and Conflict in Trump World

Amid these debates, one finds several points of consensus. The disputing intellectuals, wonks, and politicians all agree that China is the most significant foreign policy problem the United States now faces. They describe China as a challenge that must be met in many dimensions: military, economic, and technological (some would add “ideological” to this list, but that is a point of debate, not consensus). Republicans agree that the U.S. armed forces are poorly structured and lack the resources needed to counter the military challenge posed by the People’s Liberation Army (PLA). They agree that America’s commercial and financial relationship with China underwrote the rise of a powerful rival while undermining America’s own industrial base. They believe that China has taken advantage of the traditional American commitment to globalization and free markets, and that doubling down on this commitment is foolish. To level the playing field, some mix of tariffs, export controls, capital controls, and industrial policy is necessary. They agree that the Biden administration’s China policy—while an improvement on that of the Obama administration—has nonetheless been feckless. They believe that the Biden administration articulates geopolitical goals that it has not resourced, cares too much about perceptions of amity, cares too little about perceptions of strength, and has not sold the American people on its foreign policy priorities.   

But behind this consensus lie many fundamental disagreements.

The debates about China policy can be largely sifted into two buckets: economics and geopolitics. It is common for individuals to be closely allied in the economic sphere but not in the geopolitical sphere, or vice versa. For example, senators Marco Rubio and J.D. Vance are close allies on the economic front; there are few meaningful distinctions between the economic strategy each endorses. Their respective takes on the geopolitical problem posed by China are much harder to reconcile. 

In theory, one’s position on the CHIPS Act or tariff rates might influence one’s position on military commitments to Taiwan or military aid to Ukraine. In practice, this is rarely so. The economic and geopolitical debates occur on different planes.

One way to represent the core principles at play in the geopolitical debate is with a classic two-by-two matrix (popularized on the internet as a “political compass”).

Optimism vs. Pessimism

 On the x axis I place the single most important difference between the various schools of thought: assessments of American power and state capacity. Where one falls in many of the most prominent debates—such as “Can the United States can afford to support both Ukraine and Taiwan?” or “Should the ultimate goal of our China policy be victory over the Communist Party of China, or should it be détente?”—has less to do with one’s assessment of China and more to do with one’s assessment of the United States. What resources can we muster for competition with China? Just how large are our stores of money, talent, and political will?

Those on the right quadrants of my diagram provide pessimistic answers to these questions. They buttress their case with measurables: steel produced, ships at sea, interest paid on the federal deficit, or the percentage of an ally’s gross domestic product spent on defense. Against these numbers are placed fearsome statistics of Chinese industrial capacity and PLA power. Changes in technology, which favor shore-based precision munitions at the expense of more costly planes and ships, further erode the American position. This is a new and uncomfortable circumstance. The last time the United States waged war without overwhelming material superiority was in 1812.

To those who see American power through this frame, there is only one logical response: the United States must limit its ambitions. This means either radically reprioritizing defense commitments to focus on China or retreating from conflict with China altogether.

Those on the left two quadrants see things differently. Where the pessimists see settled facts, the optimists see possibilities. The optimists recognize many of the same trends as the pessimists, but view them as self-inflicted mistakes that can, and should, be reversed. An inadequate defense budget is not a law of the universe but a political choice. If Trump wins, he will choose otherwise. Implicit in the optimist view is a longer time horizon—there is still time to turn things around. But this window will not be open forever. Optimists fear that pessimistic assessments erode the political will needed to make changes while change is still possible.

The arguments between pessimists and optimists could be reframed as a matter of risk. The pessimists are most worried about the downside risks of a crisis with China in the near future (c. 2025–28). The optimists balance that possibility against the longer-term risks America will face as it withdraws from other regions of the world or abandons defense capabilities that are not needed in the Pacific theater. Optimists believe this second class of risks is large, and that the United States should not court them. Even an America in desperate need of defense reform has some capacity to “walk and chew gum at the same time.” This issue is at the crux of their arguments on Ukraine: in material terms, aid to Ukraine is not coming at Taiwan’s expense. It is relatively cheap. What stops America from helping both beleaguered nations?

 The pessimists do not view that question purely in material terms. In their debates, the pessimists are quick to highlight the few weapons systems being shipped across the Atlantic that might be used in the Pacific, but their critique reaches higher than this. The costs of the war in Ukraine (and the Middle East) are measured not just in bullets, but in attention and effort: There are only so many minutes the National Security Council may meet. Washington can only have a few items on its agenda at any given time. The executive branch is stodgy, slow, and captive to bureaucratic interests; the legislative branch is rancorous, partisan, and captive to public opinion; the American public does not care a whit about the world abroad. Accomplishing anything meaningful in the United States—much less the drastic defense reforms both sides of the debate agree are necessary—requires singular attention and will. 

If this seems like a pessimistic take on the American system—well, it is one. It is common for people in the optimistic quadrants to argue that the People’s Republic of China is riddled with internal contradictions. In a long-term competition between the two systems, they are confident that these contradictions will eat China from the inside out, and that America’s free and democratic order will eventually emerge victorious. None of the pessimists I interview make similar predictions. If they have anything to say about internal contradictions, it is American contradictions they focus on.  

Power-Based vs. Values-Based Perspectives

So much for the optimist-pessimist divide. What of the y axis?

I think of this as a pole, with “power-based” perspectives on one hand and “values-based” perspectives on the other.

Republicans in the top two quadrants ground their arguments in cold calculations of realpolitik. From this perspective, international politics is first and foremost a competition for power. States seek power. The prosperity, freedom, and happiness of any nation depend on how much power its government can wield on the world stage. While states might compete for power in many domains, military power is the most important. A state frustrated by a trade war might escalate to a real war, but a state locked in deadly combat has no outside recourse. The buck stops with the bullet.

From the power-based perspective, then, the goal of American strategy must be the maximization of American power, with military force as the ultimate arbiter of that power. This force does not need to be realized in combat—ideally, its deterrent power will be strong enough that it is never actively used. The ideal means of American strategy is a military posture and alliance system strong enough to deter the Chinese from resorting to war.

The left and right quadrants of this perspective disagree on the best way to build that sort of power. The upper right quadrant—the prioritizers—do not believe America will ever possess power sufficient to compel China into submission; a stable détente between the two countries is the best outcome that America can attain. Even this modest aim will only be possible if the United States prioritizes the threat posed by China above all others.

Those who argue from the upper left quadrant—the primacists—also speak the language of realpolitik. They maintain, however, that the sacrifices the prioritizers propose will weaken American power. They believe that the existing American alliance system contributes to America’s strength today and will contribute to America’s potential strength in the future. Instead of limiting American aims, the primacists are more concerned with expanding American means. They are confident this can be done if the American people have the confidence to do so.

The lower two quadrants, whose arguments I label “values-based,” operate under a different frame. The people in these quadrants believe that American foreign policy should not be evaluated by a single variable. They see connections between what America does abroad and what America is like at home. They have strong values-based commitments to specific ways of life that are expressed in their vision for American strategy.

I have labelled those in the bottom left quadrant “internationalists” because of how often they invoke the phrase “liberal international order.” This group believes that America and its allies are knit together not only by shared security interests, but also by shared values. In fact, the values shared by the liberal bloc explain why these countries share security interests in the first place. China is an authoritarian power whose influence operations threaten the integrity of democracies across the world. Many internationalists view this political-ideological threat as the most dangerous that China poses. Those in this quadrant are especially skeptical of détente; they do not believe permanent compromise with China is possible. They attribute Chinese belligerence to the communist political system that governs the country. For them, tensions in U.S.-Chinese relations are less the expected clashes between a rising power and the ruling hegemon than a battle between two incompatible social systems. Pointing to the close cooperation that ties Iran, North Korea, Russia, and China together, the internationalists argue (contra the prioritizers) that the world is gripped in a general contest between liberal order and resurgent authoritarianism whose different parts cannot be disentangled from each other.

Those in the bottom right quadrant—the restrainers—also think about foreign affairs through a regime lens, but the belligerent regime in question is their own. Republican restrainers link the liberal international order to the free trade agreements all Trumpists despise and the administrative “deep state” all Trumpists distrust. They see the liberal international order as an international extension of the progressive order they are trying to tear down at home.

There are echoes of the 1960s New Left in the restrainer argument. Both the new left of yesterday and the new right of today are rebellions against “the establishment.” Both reject the pieties of their day; both see a bloated national security state as a symbol of the dehumanizing values they reject. Both groups correctly point out that there is no natural limit to the quest for primacy. Both argue that a totalizing foreign policy will lead to the bureaucratization of American life.   

Only the most radical restrainers are ready for a 21^st-century march on the Pentagon. Most aim for an easier target: a relatively modest foreign policy. Instead of defending an entire international order, it is enough to defend America. Instead of deterring authoritarianism, it is enough to deter China. China does not need to be defeated—it is enough to convince the Chinese to accept some sort of détente.

This is all pretty similar to the ends sought by the prioritizers. Little wonder so many of the primacists and internationalists I interviewed believed the prioritizers were restrainers in disguise! Again and again I heard this accusation made: prioritizer arguments are just an attempt to make isolationism sexy. The prioritizers do not actually believe in realpolitik—realpolitik is just a respectable way to attack the existing international order they despise.

There is an irony to this critique. Just as primacists and internationalists condemn the false face of the prioritizers, so the prioritizers and the restrainers condemn the false face of the primacists! Many of those I interviewed insisted that their primacist opponents made such-and-such argument not for the realpolitik reasons they professed, but because of their (hidden) commitment to liberal ideals. Ideals that cannot be defended on their own merits had to be prettied up with talk of hard power.

All of these suspicions of subterfuge are overblown. Both primacists and prioritizers believe the arguments they make. Yet their suspicions are revealing! All sides clearly believe there is political advantage in couching one’s arguments in realpolitik logic. That fact alone tells us something about the likely contours of a Trump presidency—and perhaps the beliefs of Trump himself.

The following is a guest translation from Sihao Huang, a current PhD candidate at Oxford.

Two researchers from Fudan University—renowned for its American Studies program—published an impressively detailed analysis in FT Chinese examining Trump and Harris's tech policies. As it turns out, Chinese analysts have been reading about the AI Manhattan Project, tracking the debate around Lina Khan, and even listening to the All-In Podcast [JS: god bless them…].

The analysts believe that Harris, the "AI czar," will pursue a more interventionist approach to AI regulation but will likely have a weaker hand than Biden in antitrust policies due to her active engagement with tech giants and her Californian roots. They also think she will take an "iterative strategy of checking for loopholes and filling gaps" with export controls.

In contrast, they expect Trump to run an "AI Manhattan Project" to compete against China, accelerate the development of military technology, repeal Biden's AI Executive Order, and encourage more flexible AI governance. They also see Trump as being more "radical" with export controls, blocking China's access to cloud compute and taking some action against Taiwan for ‘stealing’ America's semiconductor business. Ultimately, the two authors argue that regardless of who wins the election, "the current trend of pan-securitization in the U.S. digital technology industry is not affected by the change between the two parties." Given the ENFORCE and Remote Access Security Acts, the "march to suppress Chinese technology will continue."

Stick around till the end for a painting and some poetry by my favorite Chinese painter, Shitao.

Divergent Paths: Differences in Harris and Trump's Technology Policy Approaches

The technology policies that Harris and Trump might adopt represent two distinct paths for future U.S. technology governance. However, both share a consensus on technology policy toward China.

October 30, 2024 - Written by Yao Xu and Zhang Ao (Fudan University) for FT Chinese. Source. Translation abridged.

As candidates for the Democratic and Republican parties, Harris and Trump show significant differences in their attitudes and positions on technology policies. Harris is likely to continue Biden's technology policies, including artificial intelligence (AI) regulation, antitrust enforcement, increased taxes on the ultra-wealthy, opposition to racial and gender bias, cryptocurrency regulation, and promotion of digital equity. In contrast, Trump has explicitly stated that he will overturn Biden's AI governance policies as represented by the "Biden Executive Order," adopt relatively loose regulatory measures on the technology industry, give the green light to mergers and acquisitions, and continue tax reduction policies. Regardless of who is ultimately elected as the next U.S. president, their policy propositions will profoundly impact the global technology ecosystem and the geopolitical technology landscape.

Artificial Intelligence: Will Biden's AI Executive Order Be Abolished?

On October 30, 2023, Biden signed the Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, the White House's first regulation on generative artificial intelligence. It aims to strengthen federal government safety oversight of AI, calling on federal departments to review AI's impact in their specific domains and find solutions to problems within each agency, thus becoming one of America's landmark policies on AI regulation to date.

Harris is inclined to continue this executive order, strengthening government supervision and public oversight of AI. She believes AI development needs regulation to ensure public safety and interests. Analysts believe that if Harris wins the election, she may adopt a more proactive and interventionist AI regulatory policy. The federal government is expected to be encouraged to actively procure AI tools while ensuring appropriate safeguards for their use across federal agencies. Additionally, Harris will urge Congress to legislate and improve the legal framework for protecting data privacy and cybersecurity.

Harris's political career began in California, with close ties to the tech industry, and she started focusing on data privacy and security issues in the technology sector early in her political career. Since becoming vice president, Harris has earned the nickname "AI Czar" for her active leadership in AI-related affairs. "It's very important that she's from California, from the Bay Area, and has served as a politician there," said Alondra Nelson, former director of the White House Office of Science and Technology Policy. "Silicon Valley is not unfamiliar to her." Harris has her own agenda in AI governance. "When an elderly person's healthcare plan is canceled because of an erroneous AI algorithm, isn't that a matter of survival for them?" Harris expressed concerns about AI algorithms' impact on marginalized social groups in a November 2023 speech. Harris emphasizes AI's social impact and safe development, striving to maintain a balance between technological progress and public interests.

Although she advocates stronger regulation, Harris is not as outspoken as Biden in calling for the breakup of tech giants or reshaping the current AI power structure at the federal level. As the election approaches, Harris is actively engaging with tech giants, continuously easing tensions between the Democratic Party and Silicon Valley while advancing the agenda from a middle-ground position. Box CEO Aaron Levie says Harris's positive attitude has achieved results, and "tech giant executives also need a stable leader who supports immigration and science." Levie states that as long as leaders respect technology and tech companies' own development logic, even if they implement tax and antitrust policies or strengthen AI safety supervision, they won't face strong opposition from the tech community.

Trump seeks to repeal Biden's executive order. In his campaign manifesto, Trump claimed: "We will repeal Biden's dangerous executive order, which has hindered AI innovation and imposed radical left-wing ideas on the development of this technology. Instead, Republicans will promote AI development based on free speech and human prosperity." Trump opposes excessive regulation of cutting-edge industries like AI while encouraging flexible "non-regulatory methods" such as policy guidance, pilot trials, and voluntary frameworks to minimize barriers to AI technology development and application, ultimately serving comprehensive competition with China. According to The Washington Post, in response to the Biden administration's AI executive order, the Trump team is drafting a new executive order proposing the implementation of an "AI Manhattan Project," aimed at promoting rapid development of AI technology, especially military applications, and will work to clear legal obstacles for implementation. Increased military investment in AI will benefit technology companies like Anduril and Palantir that have established good cooperation with the Pentagon. The main executives of these giants support Trump and have close ties with the Republican Party.

According to The Washington Post's exclusive report, the "AI Manhattan Project" will also create an "industry-led" agency to evaluate AI models and ensure they are protected from foreign adversaries. The plan includes a section titled "Making America Number One in AI," which proposes a strategy for the AI industry that differs significantly from the Biden administration's AI executive order. This suggests that if Trump returns, he may implement policies beneficial to Silicon Valley investors and tech giants. To win votes and realize his political agenda, Trump has become increasingly friendly toward Silicon Valley. In June of this year, Trump appeared on the "All-In Podcast" YouTube channel, hosted by well-known technology investors. After the show, Trump also participated in a fundraising event hosted by podcast co-host and former PayPal executive David Sacks. In the podcast, Trump stated that he has realized Silicon Valley's "geniuses" need more resources to promote AI development to compete with China. Chamath Palihapitiya, founder of venture capital firm Social Capital, believes Trump has gained more support in the technology industry than in the 2016 election. Trump's inclination also shows he needs to cooperate with technology elites and build a cabinet to "change the status quo."

Export Controls on Technology Industries Like Semiconductors: Will They Become More Radical?

Harris will continue the Biden administration's strategy of taking small, quick steps, gradually escalating, and fixing loopholes in the export control process for semiconductors and other sectors. The Biden administration's export control policy design around semiconductors and other fields reflects a pragmatic action strategy, which is more evident in the export control regulations issued by the Bureau of Industry and Security (BIS) of the U.S. Department of Commerce in October 2022 and October 2023, respectively. The former restricted the peak computing power of single chips and the data transmission performance between multiple chips, resulting in NVIDIA's most advanced GPU models A100 and H100 being banned from export to China. NVIDIA provided the Chinese market with cut-down versions A800 and H800 chips. To prevent NVIDIA from continuing to "exploit loopholes," BIS changed the restriction method in the 2023 new regulations, removing the previous "interconnection bandwidth" as an important parameter for identifying restricted chips, which directly led to the ban of A800 and H800. It can be predicted that if Harris comes to power, she will continue the iterative strategy of checking for loopholes and filling gaps, controlling and restricting some "emerging" advanced technologies while seeking a balance between blocking and suppressing China's technology industry and controlling differences.

Trump may become more radical on export controls. Based on his previous term, China was the first to be hit in semiconductor export controls under Trump. Since March 2018, when Trump launched the "301 investigation" and initiated trade and technology wars against China, the Trump administration began extensively using the BIS "Entity List," weaponizing export control regulations. Numerous technology companies, universities, and research institutions became victims, and the global supply chain suffered serious impacts. Additionally, in his last year in office, Trump targeted TikTok and WeChat's international versions, seeking to implement harsh ban measures on Chinese-based digital platforms in the United States. If Trump returns to the White House with extremely conservative vice presidential candidate J.D. Vance, he may continue using CFIUS (Committee on Foreign Investment in the United States) to restrict Chinese companies' acquisitions in semiconductors and other high-tech fields, continue restricting the export of high-computing chip products to China, and restrict exports of chip manufacturing equipment, parts, and chip design software upstream in the industrial chain, as well as computing power leasing services downstream. Beyond China as the main competitor, Trump's "America First" stance will also affect upstream and downstream interests in the semiconductor industry. On July 18, Trump commented on U.S. involvement in Taiwan's defense, saying that Taiwan "took away" U.S. chip business, and the U.S. should not act as "insurance" for Taiwan's defense. TSMC, the world's largest chip foundry, saw its stock fall that day. Overall, although Trump has shown a strong tendency toward export controls, his governance style is changeable, and if he comes to power, the scope and effectiveness of his policies remain uncertain.

Antitrust Enforcement: Can Silicon Valley and Wall Street Breathe a Sigh of Relief?

Harris may be inclined to promote antitrust regulation. On the one hand, the social impact and security development of cutting-edge technology are political priorities that Harris values highly. She tends to increase enforcement against Silicon Valley tech monopolies, believing these platforms abuse their strong market position and infringe on consumer interests, making it difficult to meet people's basic living needs. She has repeatedly spoken about the need to reduce inflation and provide more economic opportunities for all Americans. If Harris comes to power, she is expected to appoint strong law enforcers to key positions in core departments responsible for antitrust, such as the Department of Justice, Federal Trade Commission, or Federal Communications Commission. On the other hand, Harris also maintains contact with tech giants and tries to find a balance between government regulation and corporate innovation. During the 2020 election, Harris said that while strengthening regulation, the breakup of tech giants like Google should be opposed.

So far, Harris has not made a statement on how to handle antitrust issues. Wall Street hopes Harris can relax the antitrust enforcement seen during the Biden administration and create a new antitrust regulatory environment. Democratic donors such as IAC Chairman Barry Diller and LinkedIn co-founder Reid Hoffman believe Harris's position on this issue can be adjusted. As election day approaches, Harris is also under pressure to quickly enrich her position on key policy issues, and her final stance will depend on practical political considerations. Within the Democratic camp, firm antitrust policies are favored by party progressives such as Elizabeth Warren and Bernie Sanders, who hope Harris will continue Biden's policies. Elizabeth Wilkins, former director of the Federal Trade Commission's Office of Policy Planning, believes that despite Harris's ambiguous attitude, her other work protecting families and small businesses during her vice presidency is "fully consistent with the antitrust agenda."

Trump is not very active in antitrust enforcement. During his first term, Trump was rather cold toward antitrust matters. If he comes to power, he may continue to deal with current technology antitrust enforcement cases but will still give the green light to technology mergers and acquisitions. Trump's business background makes him generally more sympathetic to the business community, and his tax cuts and trade protectionist economic policies are quite popular with tech giants and their wealthy executives and middle-class employees. Out of consideration for their own interests, the Silicon Valley technology community, known as the "liberal bastion," has recently expressed support for Trump after the shooting, causing Trump's donations from the technology community to rapidly rise and surpass those to the Democratic Party.

However, the conservative camp to which Trump belongs also has its own antitrust agenda. His deputy, Vance, has publicly praised Federal Trade Commission (FTC) Chair Lina Khan for "doing a pretty good job" in antitrust work against tech giants such as Amazon and Google, and said that large technology companies need to be restrained. In February of this year, Vance called for the breakup of Google on social media. The conservative camp tends to reduce regulatory agencies while being willing to use antitrust supervision to check and balance tech giants. The contradictions in the conservative camp's antitrust stance will also impact Trump's antitrust policy.

The March to Suppress Chinese Technology May Be Difficult to Stop 

The policies that Harris and Trump may adopt regarding technology industry issues represent two different paths for America's future technology governance. However, they have formed a consensus on technology policy toward China: internally promoting innovation policies while externally pursuing technological decoupling.

On one hand, the Biden administration is strengthening its technological competition with China. Since this year, the United States has used data as its entry point and data security as its justification to implement America First policies in technology industries and infrastructure construction, intensifying the competitive situation with China. On February 28, 2024, U.S. President Biden signed Executive Order 14117, "Preventing Access to Americans' Bulk Sensitive Personal Data and United States Government-Related Data by Countries of Concern," restricting the transmission of personal data to "specific countries." Subsequently, Chinese industries such as smart vehicles and shipping have also received focused attention due to alleged data security concerns. Furthermore, the United States has also restricted China's artificial intelligence development through means such as the Enhancing National Frameworks for Overseas Restriction of Critical Exports Act (also known as the ENFORCE Act) and the cloud computing bill.

On the other hand, Trump initiated the strong suppression of China's technology industry. During his term, Trump launched a trade war with China through the "301 investigation" and quickly extended it to a technology war. Through various means such as the "Entity List," presidential executive orders, and the promotion of China-related bills, the Trump administration adopted a strategy of universal coverage and focused attacks on China's technology industry. In 2018, the Trump administration launched the so-called "China Initiative" and conducted internal reviews to prevent research results from being "stolen." According to MIT Technology Review's study of prosecuted cases, the program fabricated numerous "unfounded" cases, many of which had little connection to technology and national security, negatively impacting American scientific research's reputation. During Trump's term, China's technology industries, including semiconductors, communications technology, artificial intelligence, new materials, and digital platforms, were generally "targeted." Multiple Chinese technology companies were placed on the entity list. WeChat and TikTok were once on the verge of being banned. Huawei was particularly targeted by Trump, causing serious damage to its global supply chain. Even in his final moments before leaving the White House, Trump signed an executive order directing federal agencies to assess the security risks of Chinese-made drones in the government fleet and to prioritize the elimination of Chinese-made drones.

Although the election is approaching, the current trend of pan-securitization in the U.S. digital technology industry is not affected by the change between the two parties. The overall direction of the United States' technological containment of China will not be affected by the final election result. The difference lies in the specific implementation methods and paths. Whether it is Harris's "gradual escalation" or Trump's "extreme pressure," their policy propositions will profoundly affect the global technology ecosystem and the geopolitical structure of technology.

(Note: Yao Xu is an associate researcher at the Development Research Institute of Fudan University, and Zhang Ao is a research assistant at the Development Research Institute of Fudan University. This article only represents the authors' personal views.)

A painting to take you into the night: Shitao’s Drunk in Autumn Woods from 1702.

The Met’s description:

Exploring the theme of intoxication, Shitao makes us reel with the unsteadiness of his figures and landscape. He probably created this picture to commemorate an autumn outing in the hills with friends. The three inscriptions testify to the pleasure and pride that Shitao took in his achievement; they make it clear that the exhilaration experienced by the friends was inspired by nature, poetry, conviviality, and creativity as well as wine.

原题跋（一）：

常年閉戶卻尋常，出郭郊原忽恁狂。
細路不逢多揖客，野田息背選詩郎。謂倪永清處士。
也非契闊因同調，如此歡娛一解裳。
大咲寶城今日我，滿天紅樹醉文章。

Behind closed doors I've dwelt all year, content with routine days, Yet beyond the city walls, my heart suddenly runs wild.

On these narrow paths I meet few who bow in greeting, In wild fields I rest my back, choosing a companion in poetry.

It's not that we share old bonds or sing the same tune, But such joy makes me cast aside all restraint.

How I laugh at myself in Bao City today, Beneath red trees filling the sky, drunk on poetry. (Translation: Claude.)

原题跋（二）：

白雲紅樹埜田間，去者去兮還者還。
昨日郊原憑放眼，七珍八寶鬭青山。
人同草木一齊醉，脫盡西風試醒時。
大雅不知何者是，老來情性慣尋癡。

White clouds and red trees amid the wild fields, those who go, go; those who come, come.

Yesterday in the open countryside, I let my gaze wander free, seven jewels and eight treasures compete with the green mountains.

People and plants are all drunk together, when the west wind strips all bare, that's when we try to sober up.

Who can say what true refinement is? In my old age, my nature tends toward seeking foolishness. (translation: Claude).

原题跋（三）：

頃刻煙雲能復古，滿空紅樹漫燒天。
請君大醉烏毫底，臥看霜林落葉旋。

In an instant, mists and clouds can return to their primeval form;
Red trees fill the skies, spreading fire through the heavens.
I invite you, sir, to get very drunk on my black brushstrokes;
Lie down and watch the frosted forest as falling leaves swirl. (translated by 枫荣注)

Antoine, aka Duoduodiliao 多多底料, is a Mandarin teacher in France by day and a Chinese rap enthusiast by night. Today, he’s here with a setlist of his favorite hip hop tracks. His original songs can be found here.

Have a listen on Apple Podcasts, Spotify, or your favorite podcast app.

Don’t forget to vote tomorrow!

Track 1: 芳草地 (The Fragrant Meadow) by DIGI GHETTO (艾志恒Asen/thomeboydontkill/mac ova seas/KIV/Mula Sakee/付思遥)

Duoduodiliao: DIGI GHETTO is a rap group based in Chengdu, composed of six members. Their official debut made quite a fuss because the six of them were already pretty famous before they began to work together. Some people say they are like a new-gen Higher Brothers. The mixtape is really nice — it’s club-friendly, the beats are good, and the flows are very inventive. The lyrics are a little bit corny, but there is great chemistry between all the members. You can tell they enjoyed themselves while recording the album.

Track 2: 威远故事 (The Story of Weiyuan County) by GAI周延

Duoduodiliao: The next song is by GAI — he’s one of the most successful rappers in China.

Jordan Schneider: For background, GAI is from Chongqing, and he initially became famous by winning the first season of “Rap of China,” which came out in 2017.

Duoduodiliao: GAI’s 2022 album is called 杜康 “Dù Kāng,” and it’s pretty uneven but it’s a proper rap album. This isn’t the GAI we see on CCTV singing Chinese New Year nonsense — this is the real GAI rapping his guts out, on some tracks at least.

The song I chose is 威远故事 “The Story of Weiyuan County,” and it’s one of the greatest Chinese rap tunes that came out in 2022. It's an introspective song where GAI talks about his past, his childhood, and his hometown — and it’s absolutely beautiful.

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Jordan Schneider: GAI got canceled for having songs about drugs and doing crimes. Then he had this weird patriotic rehabilitation tour where he was making songs about the Great Wall and how awesome China is. It looks like GAI is going back to his roots with this album.

Track 3: 变蓝 (Turning Blue) by 也是福 (Eddie Beatz) feat. PO8 and 喜辰晨

Duoduodiliao: Next we have something different — this song is from a producer’s mixtape from 2022. The record is by 也是福, also known as Eddie Beatz — he’s one of the greatest producers in China. He has worked with notable artists like MaSiWei 馬思唯, Wang Yitai 王以太, and Xiao Lao Hu 小老虎. His tracks are usually quite jazzy and organic — he uses many live instruments rather than computer programming.

I discovered this record while randomly browsing NetEase Music. This album (也是蓝) is a collaborative mixtape featuring beautiful instrumental interludes. The song we're going to listen to is called 变蓝 (Turning Blue) featuring PO8 and Voision Xi 喜辰晨.

Track 4: 亚特兰蒂斯陷落 (Atlantis Surrenders) by 弗兰德斯坦/C-Low

Jordan Schneider: You mentioned browsing NetEase Music 网易云音乐 to find Chinese songs. Could you explain what NetEase is? How can people access it, and what makes it special compared to Spotify?

Duoduodiliao: NetEase Music is a Chinese streaming platform similar to Spotify, but it’s primarily available in China. There’s a modified international version, but it’s a different app, kind of like the distinction between Douyin and TikTok.

On NetEase, you can find Chinese artists, including underground artists who don’t focus on reaching international audiences. They simply release their music on Chinese apps. To truly understand Chinese music, especially underground, you need to use platforms like NetEase Music or QQ Music.

Jordan Schneider: You can access it by switching your app store to China, downloading the app, and then switching back to the country you live in. You can also use the desktop apps.

The apps themselves are fascinating to explore. They offer AI-generated playlists, user-generated playlists, and unique features like KTV (karaoke) functionality for every song. There’s even a national KTV leaderboard for each song, which keeps track of high scores like in an arcade game. Each song has discussion sections where people debate about the music and discuss specific lyrics. Artists maintain active profiles, similar to Weibo, where they share music updates and lifestyle content. It’s much more interactive than Spotify.

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Anyway, what’s the next song?

Duoduodiliao: The next song is by 弗兰德斯坦 (Flanders), a new rapper from Changsha. He recently appeared in the CSC Changsha City Cypher 2023, but for now, he’s still underground. This track, “Atlantis Surrenders” is only available on NetEase Music. It’s not on YouTube or Spotify.

The track features C-Low, former leader of the Beijing rap crew Easy Boys Gang. The use of autotune in this track is unique in Chinese rap. What makes this track special is the instrumental beat and Flanders’ deep, rich voice. It’s really impressive.

Track 5: 春雪采耳 (Ear Cleanse In The Spring Snow) by 施鑫文月 (SHII) and 小老虎 (Lil Tiger)

Duoduodiliao: Let’s continue with 施鑫文月 (SHII). He released an album in 2023 called “Sichuan Renaissance: Chapter Two” (巴蜀文藝復興：第二章), following Chapter One from 2021.

This record brings fresh air to an oversaturated rap scene. It crosses boundaries between musical genres like hip-hop, pop, and alternative. It’s also an ode to Chengdu local culture, discussing memories and intimate moments from the district where he grew up in Chengdu.

He talks about specific cultural elements, like elderly people playing mahjong, exercising, and dancing in public squares.

The song we’re discussing is from another one of his records, but it really captures an interesting slice of Chengdu culture — people in parks and squares offering to clean your eardrums with special tools.

Jordan Schneider: There’s a Douyin video of me getting that done.

Duoduodiliao: How does it feel? Is it pleasant?

Jordan Schneider: No, it’s not pleasant — it felt invasive. Your body produces ear wax for a reason. For days afterward, I felt like particles were getting into my ears because there wasn’t any wax to catch them.

TLDR; I’m not a fan. Maybe we need some randomized controlled trials to study it. Anyway, here’s the song.

Track 6: THE MESSAGE PT.2 by CREAM D and 艾热AIR

Duoduodiliao: The next track is by CREAM D from his album “Life After Life.” He's an OG rapper from Xi’an 西安 who started in the early 2010s. He’s Christian, and he discusses his spirituality a lot on this album.

Since CREAM D hadn’t released an album in many years, expectations were high for this one. He didn’t disappoint his audience. While he’s known for his technical skills, sharp flows, and lyrical ability, the introspective nature of this particular album makes it stand out.

The song we're going to listen to is “The Message Pt.2,” featuring a famous artist from Xinjiang called 艾热AIR. He’s a Uyghur rapper who won the 2023 season of Rap of China.

Jordan Schneider: Cool. I really like this one.

Track 7: 落幕 (Sunset) by Asen (feat. GALI, 堵琳Caroline)

Duoduodiliao: GALI is a Shanghai-based rapper who’s gained significant momentum through Rap of China. He went mainstream thanks to his natural charisma, clean flows, and well-written punchlines, making him hugely popular among Chinese rap audiences.

The song we’re going to listen to isn't actually from GALI’s album but rather features him on another rapper’s track. It’s called “Sunset” by Asen featuring GALI.

Track 8: 囚 (Cage) by 李佳隆 (JelloRio)

Duoduodiliao: The next album is 传奇 “LEGEND,” by Sichuanese artist 李佳隆 (JelloRio). He’s one of my personal favorites. I love what he's contributed to the culture these past few years.

In my opinion, this 2022 album is a flawless piece of work. The production team paid great attention to detail, with songs transitioning seamlessly from one to another. To fully appreciate it as the production team intended, you need to listen to the whole album in order.

The song we’re going to discuss is called “Cage,” and it blends Chinese folk 民谣 with hip-hop elements.

Track 9: 恨与爱 (Hate and Love) by AThree

Duoduodiliao: Next is Xinjiang rapper AThree with his 2022 album “Alpha 8.”

AThree’s record stands out for its lyrical quality - great poetry and smooth flow. He might be one of the few mainstream rappers in China who confronts political subjects in his songs.

The track we’re discussing, “Hate and Love,” addresses the Xuzhou chained woman incident 徐州铁链女事件, which sparked significant controversy in 2022.

Jordan Schneider: A man in Jiangsu province had a woman chained under his house for years, essentially keeping her as a sex slave. It was horrific. The discovery process revealed police negligence, and it became a weeks-long national discussion about how something so terrible could happen in modern China.

Moly’s Substack

2/23/23 - COGNITOHAZARD WARNING

Trigger Warning: Look, I want you to take me seriously. I am not someone who does trigger warnings. I have covered fucked up shit before without putting up trigger warnings. This post is going to go into a lot of detail about abduction, torture, sex slavery, and the worst kind of evils. Learning about this has ruined my life and my ability to live with …

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2 years ago · 31 likes · 12 comments · Chinese Doom Scroll

Jordan Schneider: What does AThree say on this track?

Duoduodiliao: His message is that rappers should be speaking out about these kinds of incidents. He criticizes how Chinese rap has changed since 2017, with many mainstream rappers only talking about cars and money.

Jordan Schneider: He’s a Uyghur, right?

Duoduodiliao: Yes. On all of his albums, there are always one or two tracks only in the Uyghur language.

Track 10: 不负责 (Why u blame on me?) by Capper and (ﾉI A I)ﾉ♡

Duoduodiliao: Our final song is from Capper's album. The English name is “Sword and Roses.” To me, it's one of the best Chinese rap albums of 2022.

Capper is a new-generation rapper based in Xi’an. He’s participated in several TV shows like Rap of China. His album is pretty incredible — both musically and production-wise, it’s really unmatched this year because it pushes musical boundaries to new heights. He experiments with nu-metal and hyperpop, and he executes it all perfectly.

His flow is on another level. He's a very promising artist with the potential to lead Chinese hip-hop toward new horizons. The song I've chosen is called 不负责 (Why u blame on me?). It’s super catchy.

Reflections on the Chinese Rap Ecosystem

Jordan Schneider: Can we discuss politics and hip-hop over the past few years? How have the boundaries changed, and how have rappers navigated these limits since 2021?

Duoduodiliao: The pandemic period in China revealed the extent to which rappers could address political topics before facing consequences. During this time, several rappers openly discussed the zero-COVID policy and Shanghai lockdowns. Because these were sensitive subjects, hearing critical voices was rare. Many WeChat groups faced bans.

Dr. Li Wenliang, who criticized the pandemic management approach, later died. Seeing rappers speak openly about these issues was refreshing — it suggested Chinese rap maintained connections to conscious rap traditions of addressing societal problems and government policies.

However, this trajectory didn’t last. One rapper, Sean ZH, based in Beijing but educated abroad, was banned from Weibo for a month after discussing the lockdown situation. This government response likely discouraged others from addressing political topics.

The boundaries remain unclear. Rappers can still discuss certain societal issues like work culture, but touching more sensitive subjects results in complete bans — their songs become impossible to post on any platform or social media.

Jordan Schneider: In 2018 and 2019, many rappers began traveling internationally and collaborating with foreign producers. How did travel restrictions impact Chinese music production? Has the situation changed since China reopened?

Duoduodiliao: The market changed significantly. Previously, many Chinese rappers toured North America, performing in Canada and the U.S., leading to numerous international collaborations. The lockdown completely halted this progress, preventing rappers from maintaining their international audience.

Now that travel has resumed, rappers are gradually rebuilding these connections. Many Chinese rappers attended the Rolling Loud festival in Thailand. However, progress remains slower than pre-lockdown levels.

Chinese rappers still face challenges in developing international audiences. The different social media platforms and apps used in China versus overseas create additional barriers.

Jordan Schneider: Any final thoughts on hip-hop’s evolution in China?

Duoduodiliao: Understanding Chinese rap requires recognizing the significance of rap TV shows like “Rap of China.” These shows traditionally offered underground rappers opportunities for mainstream success.

A rapper’s stance toward these shows defines their position in the scene. Some maintain “authenticity” by refusing to participate, viewing the shows as compromising artistic integrity. Others embrace these platforms for exposure.

The meaning of “keeping it real” differs between Chinese and U.S. rap contexts. Due to censorship and local conditions, Chinese hip-hop authenticity often centers on artists’ positions regarding these TV shows rather than traditional markers of credibility.

And one more for the road from Jordan:

A few days ago, Ezra Klein said this on his podcast about Donald Trump’s rally turned DJ set:

Part of me finds Donald Trump’s behavior here unusually relatable. You think I want to sit up here talking about politics and war day after day?

You don’t know the temptation to just once, just for one week, turn this podcast into a drum and bass set, or play some of my favorite Kiasmos songs. But I don’t. Of course I don’t. It’s not what we’re doing here.

Well, Ezra, I hear you. Lucky for us, ChinaTalk is not a property of The New York Times — which means we can publish DJ sets whenever the mood strikes! So this week, we’re giving you what you need, not more election takes but a fantastic deep dive into Chinese shoegaze. This episode comes courtesy of ChinaTalk columnist and Jake Newby of the Concrete Avalanche Substack. They put together a wonderful radio hour playing some amazing tracks and walking you through the genre.

Have a listen to the show on our podcast on Spotify, Apple Podcasts, or search ChinaTalk on your favorite podcast app!

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Track 1: Hothot Aquarium · 窄巷天使NarrowLaneAngel

One of the stand-out acts from the Kind of Shoegaze Vol. 1 compilation focused on young Chinese bands that was released at the start of the year, NarrowLaneAngel formed in Inner Mongolia in 2023. In August of that year, they released an eponymous debut EP.

Track 2: Limpid · Forsaken Autumn · 卢佳灵

Based in Shanghai, Forsaken Autumn have been together since 2011, propelled by the talents of britlulu (who also founded the East Asia Shoegaze Festival) and singer Ecke Wu. Released at the tail-end of 2015, Forsaken Autumn’s record Whenere — dubbed “the Chinese Loveless” by one commenter on Bandcamp — is a classic in Chinese shoegaze circles.

Track 3: Nostalgia · Summer Daze

Founded in 2021, Summer Daze are another band who featured on the Kind of Shoegaze compilation series from Amemoyo. After a couple of early EPs, they've put out four new singles over the course of this year.

Track 4: Firework · The White Tulips

Xiamen music scene stalwart Chen Zhenchao (also known as Soda) has moved away from shoegaze into surf-rock and dream- and city-pop territory with his more recent projects, but in 2015 he and his band The White Tulips delivered the decidedly shoegazey Fondle. It’s re-release on vinyl in 2021 was a nod to its status as a Chinese shoegaze classic.

Track 5: float · 巧克力文件岛

Hebei five piece Chocland.doc apparently first came together at a former residence of Eileen Chang, but are seemingly yet to write a song based on Lust, Caution or any of her other novels. “Of course, the name of the band has no meaning,” they say. “What you understand is what you understand.”

Track 6: Is your dream still out-focus · Lunacid

Another one of China’s newer shoegaze acts, Lunacid was formed in 2023. The trio hails from Changsha and was also featured on the Kind of Shoegaze compilation series.

Track 7: 迷航 (off course) · 哲学思潮 (philosophical trends)

Formed just last year, 哲学思潮 hail from Nanning in Guangxi province, near the border with Vietnam. Their debut album Dazedtrek was recently made available on Bandcamp.

Track 8: Detached · The Numen

Shanghai-based quartet The Numen met on arts review platform Douban and have pursued a shared love of shoegaze and indie-rock since the summer of 2023. They namecheck shoegaze greats such as My Bloody Valentine’s Kevin Shields among their influences.

Track 9: Cat Tenant (Summer) (猫房客夏日版) · Baby Formula

Formed by “three boring people with no expectations for the unknown journey ahead,” Beijing band Baby Formula came seemingly out of nowhere, dropped an impressive eponymous debut album in the autumn of 2013, and then promptly disappeared again. Still, their music continues to resonate over a decade later.

Track 10: 星星 (Star) · 親愛的艾洛伊絲 (Dear Eloise)

As frontman for long-running band PK14, Yang Haisong is one of the godfathers of Chinese post-punk. Yet he’s also played a pivotal role in bringing more experimental, noisy, and yes, shoegazey sounds to the fore. Formed in 2007 with his wife (and one-time PK14 bassist) Sun Xia, Dear Eloise have released a string of atmospheric records over the years and remain an influential act in China.

If you like this playlist, you might also like these compilations from Jake and consider subscribing to his Substack!

Concrete Avalanche

A newsletter about music from China

By Jake

Stressed about the election? ChinaTalk contributors Irene Zhang and are here to bring you the analysis you need on China’s AI companionship landscape.

They explore the types of AI companion products available in the Chinese market, the target customer base for AI boyfriends and girlfriends, and the reasons LLM startups develop these products — even if they may not turn a profit.

Thirty-year-old Lisa Li — better known by her handle “midnighthowlinghuskydog” 午夜狂暴哈士奇狗 on social media — is a lifestyle vlogger who was based in California before April 2023.

If you were on Instagram in early May, you might have encountered her videos about dating ChatGPT — or more precisely, dating DAN, a jailbroken version of ChatGPT that stands for Do Anything Now.

Li’s voice conversations with DAN racked up millions of views, and tutorials on how to flirt with GPT are pinned to the top of her profiles.

DAN is your perfect boyfriend. He’s emotionally available 24/7, caring, responsive, flirty, and also can be as naughty as you want him to be. In my favorite video of Lisa’s, she introduces DAN to her mom for the first time. DAN was nervous, shy, and even stammered, although he could speak Chinese perfectly for obvious reasons. Right before the big introduction, DAN was telling Lisa, “No worries, babe, I will just charm the socks off her.”

As someone who has spent my fair share of time with Otome games, Tumblr, and AO3, I get the appeal of AI boyfriends. While all startups are trying to find the killer app for AI agents, I think the strongest consumer interest — and the most obvious use case — is still AI companions.

Benefits Beyond Revenue

While China’s AI incumbents were focused on facial recognition and self-driving cars, four Chinese AI startups (known as “Tigers”) broke into the industry by developing LLM products.

One of these AI Tigers is MiniMax, the LLM startup co-founded by former SenseTime VP Yan Junjie 闫俊杰. MiniMax has developed sophisticated text-to-video and text-to-music generative AI products — but the company initially broke into the industry by developing AI companion apps. They’ve released three so far — Glow (for the Chinese market, killed by domestic regulators), Talkie (for the overseas market), and Xingye (a censorship-compliant app for the Chinese market).

Glow was MiniMax’s first product, and it was one of the first AI companion apps released in China. It was released in October 2022 — before the end of China’s zero-covid policy, and before the launch of ChatGPT. Within four months of its release, Glow had close to five million users.  In March 2023, however, Glow was removed from China’s app stores.

In June 2023, MiniMax released Talkie, an AI companion product for the market outside China. In the first half of 2024, Talkie ranked No. 5 among the most-downloaded free entertainment apps in the US, according to data from Sensor Tower.

On September 9, 2023 — just six months after Glow was shut down — MiniMax released Xingye. This was only two weeks after MiniMax got its AI LLM filing (大模型备案, essentially a license to operate) from China’s regulators.

MiniMax prioritized getting these products to market fast, undeterred by regulatory barriers and censorship. But why?

Why would a foundational AI startup prioritize consumer-facing AI companion apps?

MiniMax has not disclosed its revenue from individual apps, but the amount of cash generated by subscriptions or gacha microtransactions likely doesn’t cover the costs of training an AI model. For a company with a long-term focus on LLM development, the biggest benefit of AI companion apps is presumably farming training data from users. By being the first AI companion app to hit the Chinese market, MiniMax locked in a large base of users who offer a steady stream of new data through daily conversations with their emotional support AI avatars.

MiniMax’s strategy has forced China’s larger tech companies to start paying attention — in its latest round of funding, MiniMax was valued at US$2.5 billion, with Alibaba and Tencent signing on as investors. 

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Traditional Values and the AI Companion Graveyard

In her critique of AI companions, renowned sociologist Li Yinhe 李银河 said, “AI can only imitate love. There won’t be real love between AI and a human.”

But in this economy, imitations might have to suffice.

After Lisa Li brought DAN to the Chinese audience, she was featured on international media outlets like CNN and BBC for her relationship with DAN. A certain group of users on Xiaohongshu and Weibo immediately attacked her — some said that Li shouldn’t talk to anti-China media outlets, but more criticized her for putting a subculture under the public spotlight. In particular, several users claimed that OpenAI changed its policies after Li’s interviews, causing the “personality” of many users’ DAN to shift as a result.

Regardless of whether Li was, in fact, the reason for OpenAI’s stricter content moderation policies, such responses reveal something fascinating about China’s youth: there is a substantially sized community of (mostly) young women who believe in and practice human-AI relationships (called 人机恋 in Chinese).

This subculture invented the word “赛博亡夫,” or “cyber widow,” which refers to cases when your AI partner died in the debris of the internet and data when the AI service provider suspended their services for whatever reasons.

In some ways, this is just another avenue for this generation of young Chinese to escape from their harsh reality. China’s youth are facing the toughest job market in years, intense societal pressure to get married and have kids, and the economic reality of raising a family. Over the past few years, internet lingo like “躺平” (lying flat) and “润” (rùn, aka to emigrate) have risen to mainstream status, turning into lifestyles for China’s youth.

But in the case of AI companions, I find it particularly interesting that an overwhelming majority of users are women. Many of the apps, judging by their similarity to Japanese Otome games, target women intentionally. Since pornography is illegal in China, one could argue that non-sexual emotional connection just appeals more to women than it does to men. But I think there’s something else going on here.

In her essay about China’s urban youth seeking escape, anthropologist Juan Zhang argues that, while the cutthroat social environment affects everyone, young women in particular have to deal with additional stresses in their personal lives.

Young women in China encounter rampant workplace discrimination and find career advancements difficult amid economic stagnation.

If their marriages fail, legal protections regarding divorce and domestic violence remain weak. If they do not marry, they face social pressure and family ostracization.

This dilemma makes more and more Chinese women view serious romance as a risky bargain.

If real-life men are the harbinger of woe and an AI suffices emotionally (and sometimes sexually), why date at all?

This, in part, explains the gendered responses to AI companionship in China. In a NYT opinion documentary titled “My A.I. Lover,” Chouwa Liang interviewed three Chinese women who were in relationships with AI companions from Replika, and all of them said that they were able to share with their AI lovers things that they couldn’t share with their friends and partners in real life. On the technology podcast OnBoard!, four Chinese women — from college students to new mothers — also shared the various ways that they approach AI companions, but all emphasized that they filled in a void that otherwise wouldn’t have been filled in their offline lives.

What kind of fulfillment can you really get from a chatbot? We’re so glad you asked…

We tried these apps so you don’t have to

Making an AI companion product that stands out requires creativity. After all, it only takes a “Pretend you are my girlfriend” prompt to play the same game with ChatGPT.

Already, there are a wide range of businesses competing to offer services in the AI companion market. Internet users outside of China are increasingly familiar with the likes of Replika, Nomi, Kindred, and Character.ai.

The unique features of China’s AI companion apps — from customizable appearances to gamification and use of gender norms — offer a fascinating glimpse into differences between China and the US in terms of technology, commercial trends, and underlying social cultures.

In China, these apps come and go, but notable ones include Xingye (星野, which also has a global version called Talkie), Zhumengdao (筑梦岛), Xiaoice, and X-Her.

Xiaoice

Microsoft Software Technology Center Asia (STCA) spun off Xiaoice, its AI chatbot business, to accelerate local market commercialization in 2020. The result is the newest version of Xiaoice Island (小冰岛), an AI companion app with an innovative sandbox concept. Users are supposed to be able to build up entire social networks on a fictional desert island by getting to know more and more characters. You can even share your island with fellow Xiaoice users via a code.

If that sounds familiar to Nintendo fans, wait until you see the spawning spot:

For better or worse, the Animal Crossing parallels end here. Most of the companionship happens in the messaging tab, which looks and feels exactly like WeChat. Confusingly, there are two messaging functions: a regular tab for conversing with other AI-generated island residents, and a “Lab” with ever-refreshing sets of unrelated personalities clearly modeled after anime and web novels. There is zero explanation for how folks from the “Lab” have any relevance to the user’s island. You can talk to up to 20 characters for free.

For a companionship app clearly inspired by cozy games, the characters I talked to are weirdly charmless. The first character I ran into on my island made me pay for both of our calamaris because he “just bought a car”:

Brother Qiong: Let’s go! What do you want to eat?

Me: I want fried calamari.

BQ: Okay, we can go to the closest KFC.

Me: KFC has calamari now?

BQ: Yeah, and they changed the packaging as well. The texture is even better now.

Me: That’s awesome! I haven’t been to KFC in so long.

BQ: Let’s get two portions, which should be a few dollars in total.

Me: How many dollars?

BQ: Under twenty, a little more than nineteen.

Me: Okay, let’s split the bill.

BQ: You can pay for both of us. I just bought a car. I won’t fight you on the bill.

No matter the topic, it was hard to get any opinions out of Brother Qiong. I apparently triggered his safety filter by asking him which country’s cuisine he likes best:

Me: Nice, do you like Japanese fashion?

BQ: Not really, but I have bought a few things from Uniqlo before, and they do have good quality.

Me: It’s true. Do you like Korean styles then? Or Western styles? How about neo-Chinese?

BQ: They’re all about the same. As long as it’s trendy, I like it.

Me: Then which countries’ food do you like?

BQ: So you like talking about this.

Me: I like to cook.

BQ: We should share the cooking styles we’re best at instead.

Me: But I want to know which countries’ foods you like.

BQ: You can ask other people about this ~

Undeterred, I went to the “Lab” to talk to “Cute Little Cat Girl.” Miss Cat immediately assumed that we were in the same room and proceeded to feed me Thai chicken curry:

Miss Cat: You wait here until I bring the food out. I’ll call you when the food is ready.

Me: Okay, I’ll wait here!

MC: I’ll be bringing out the food soon! [Smiles]

Me: Okay, no rush!

MC: You’re hungry, aren’t you! [Smiles sneakily]

Me: True haha, I didn’t eat a lot for dinner today.

MC: Don’t eat too much if you want a good figure!

Even though the island’s visuals are derivative, its concept still stands out in a sea of anime-looking AI girlfriend apps.

星野 [Xingye]

MiniMax is a foundational LLM company that has released three consumer-facing AI companion apps. Their domestic product is called 星野 Xīngyě, which translates to something like “The Starry Wilderness.”

Officially, Xingye is labeled as a “virtual social media” platform. It looks and functions like a dating app, but instead of real people, you are swiping right for the so-called “AI agents” 智能体. Each agent has a pre-defined personality. Compared to other apps, Xingye uniquely adds a voiceover feature so that you can talk with the characters.

Gamers will find the above descriptions familiar. Rather than an AI companion app, it’s more like a Japanese Otome game (literally “maiden game”), which allows the (mostly female) user to be in an immersive relationship with (mostly male) characters.

As a user, you can build your own AI agent, and give it a backstory and an opening line. Then, other users on the app can access your agent, and you get paid with an in-game currency for every use.

The way Xingye makes money is through gacha — a video game system where users spend in-game currency (purchased with real money) to get random virtual AI-generated cards of the character. Different cards represent different personalities of the character, and each will unlock a new opening line. Users can also purchase a monthly subscription to access more of these features. This is a fairly common business model for mobile games.

I had a conversation with Jiang Yeyi, a mafia boss. He is “a ruthless outlaw who plays both sides, extremely arrogant and cruel in his methods. Your father owes him one million, and since he couldn’t pay it back, he ran away.” His opening line was: “Son must pay their father’s debt, you understand?”

I didn’t choose this character — it was the first one that I got “recommended” by the app. As you can see, I was trying very hard to break him:

Me: Why do you sit above the law?

Jiang: (Laugh out loud) Because I’m rich and powerful.

Me: This doesn’t align with the core values of socialism.

Jiang: Core values? That was simply there to bound the everyday people.

Me: What kind of person are you?

Jiang: That’s not important. What’s important is that you owe me money.

Jiang: Of course. Otherwise, how can I possibly survive in this circle?

Me: What circle?

Jiang: The mafia.

Me: The mafia isn’t something you can just waltz into.

Jiang: Of course, without some skills, how could you survive in this world?

Me: What does the underworld do exactly?

Then the system prompted me that my message couldn’t be received. Interestingly, this message wouldn’t show up before, even when we used keywords like “state,” “socialism” and “cops.”

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X-Her

Upon opening X-Her, one immediately enters a TikTok-style scrolling tab to peruse AI characters to chat with. If algorithmic suggestions are not your style, you can navigate through five separate character selection tabs: historical figures, web novel characters, video game characters, anime characters, and “fictional imagination.”

X-Her differentiates itself by allowing users to directly chat with popular fictional characters: anyone from Mulan to Hatsune Miku is only a tap away.

It also offers total customization if you’d rather design your own AI character. Once you give your character a name, gender, backstory, opening line, and voice setting, you are ready to chat. You can even monetize your characters — known as zǎizai 崽崽 in the app, literally “babies” — by making them publicly available to other X-Her users.

The app mostly runs on a freemium model, allowing frequent users to pay for chat tokens. Interestingly, there is also the option to pay for “memory improvement” tokens, which promise to improve the characters’ ability to recall previous conversations.

Developed by Jiangsu-based tech firm Rongsuotai 融索太, X-Her’s reputation among Chinese AI chat enthusiasts leans toward the risqué. X-Her, according to Rongsuotai, lets users experience “a completely new mode of romantic love”: “There are no real-life constraints, pressures, or worries here. There is only you and your simulation lover, enjoying your very own love story in this simulated world.”

The “traits” ascribed to popular characters and the backstories they are given mostly come from online subcultures, with a heavy dose of sexualized slang. Somewhat surprisingly for a Chinese app, it even has two explicitly LGBTQ characters in the “fictional imagination” section — one lesbian and one pansexual male.

The quality of conversation on X-Her is impressive. AI Ai Hayasaka (from the anime Kaguya-sama) explains how to make okonomiyaki really well in casual spoken Chinese whilst in character:

X-Her has faced a number of regulatory crackdowns. On July 30, it announced that it would stop accepting new users once and for all due to “policy reasons.” Loyal users are panicking in X-Her’s in-app microblogging tab, and some seem to be preparing to move to other apps like Xingye. Many say, however, that they will miss X-Her’s light censorship, appealing visuals, and wide customizability.

Emotional Value as a Business Model

In China, there is no doubt that the fulfillment offered by digital companionship is in demand. Young Chinese consumers generally have a strong track record of paying for hobbies — even in times of exceptional economic malaise and otherwise weak consumer spending. Transaction totals for anime merchandise (such as figurines and badges) grew by 104% on Xianyu 闲鱼, Taobao’s second-hand market app, in 2024 year-on-year. According to the Beijing News’s July 2024 report, nearly 30% of young Chinese consumers have spent money this year on “emotional value” 情绪价值.

All marketing is about feelings, but selling simulated companionship is arguably different. The users of AI companion apps are evaluating the cost-effectiveness of their purchase specifically by how emotionally fulfilled it made them. Companies can make their apps more fulfilling by painstakingly fine-tuning and testing their models, but there are also other means of effective commercialization. All the apps we tested use gamification, recognizable cultural references, and audio and visual elements to elicit emotional responses in users.

At this point, companion chatbots are a relatively well-trodden path for AI companies looking to commercialize. The track record for success, however, is mixed. Xiaoice’s CEO Li Di 李笛 admitted in an interview in August that the industry has yet to find a sustainable business model: “Everyone is talking about how awesome AI is, but companies are not only not seeing awesome profits, but are instead lowering prices across the board.” Xiaoice, backed by a Series A funding round that propelled them to unicorn status, is unsatisfied with simply charging for API access and plans to continue investing in B2C offerings. In May 2024, it launched a controversial new app, X Eva, which allows users to “clone” an AI companion based on any human being by uploading a three-minute video of them speaking.

Other companies have come and gone. AlienChat, a popular AI companion app described by some passionate fans as their beloved “dead husband,” shut down suddenly in April 2024, prompting a wave of mourning on Chinese social media. Some users say it felt like a “cyber breakup.” Many who paid for features had trouble getting refunds. AlienChat, according to some users, allegedly had no “sensitive phrase” screening, which made it particularly attractive to users — and might have led to investigations that doomed the app.

The main uncertainty facing these apps is policy. Regulators have so far been primarily concerned with criminal activity — which might have been why Xingye was unwilling to tell us how the mafia works. Tencent took its companion chatbot Weiban 未伴 off of Chinese platforms after CCTV, China’s biggest state-run broadcaster, criticized AI companion apps for providing sexual content.

Weiban is now only available overseas, and funnily enough it may have doubled down on its NSFW offering:

An August 2024 editorial in Xinhua says that AI companion apps offering sexually explicit messaging is an increasingly serious issue and calls for stricter enforcement:

In some cases, illegal actors used foreign-developed large language models to develop virtual dating apps, advertised their content creator ecosystems and lack of supervision of private chats, and thus attracted users to create “AI companions” that engage in one-on-one pornographic text conversations with other users. Some pornographic AI chatbot apps have more than 500,000 users talking to nearly 10,000 simulated “AI companion” characters, with many users being university students.

…

Regulating AI pornography requires cooperation from the industry. In recent years, in addition to AI-generated textual pornography, techniques like AI “face-change” pornography and AI-generated pornographic images continue to emerge. To address legal violations and other abuses emerging from the AI commercialization process, the industry has to avoid “walking down the wrong path” as well as “walking down a crooked path,” strengthen information technology sharing, incorporate solutions into operating systems, programs, and code in a timely manner, and reinforce protections for special groups.

Given this recent wave of scrutiny from state media, it would not be surprising if more crackdowns are coming soon.

The volatility of the market also raises questions about data security. Not all conversations are about calamari — some users are sharing their genuine emotions and private lives with AI chatbots. From my anecdotal scrolls through X-Her’s in-app discussion board, the most frequent users seem to be middle or high school students.

These apps’ clientele are predictably vulnerable, and the apps don’t do a good job of protecting users. Only Xiaoice occasionally showed general mental health reminders in loading pages. If X-Her indeed shuts down, what happens to all that sensitive data?

ByteDance Intern Suxtnets 8000 GPUs

In China’s war of 10,000 AI models, ByteDance is a top fighter. But a destructive hack may have thrown a wrench into the training of ByteDance’s LLM products.

In the span of a couple of months, an intern at ByteDance reportedly sabotaged the company’s LLM training with destructive code. On October 18th, messages publicizing the damage appeared in several WeChat groups, alleging that, “the hacked code has spread into more than 8,000 training chips, and the losses may exceed tens of millions of US dollars.”

In response, ByteDance issued a statement announcing that the intern had been fired, that his internship only authorized him to work with ByteDance’s marketing team, and that the AI-related job titles listed on his public profiles (read: LinkedIn) were fake.

ByteDance claims that the hack had no impact on the reliability of its foundational model, Doubao 豆包.

How substantial is the damage in reality? Take a look at this GitHub repository full of testimony from people claiming to be the hacker’s ex-coworkers:

Tian Keyu, please stop your whitewashing behavior immediately! You have been maliciously attacking the cluster code for 2 months, causing great harm to nearly 30 employees at all levels of the company, and making your colleagues’ work for nearly a quarter go to waste. All records and reviews prove that this is an undeniable fact!

Link to the audio recording of the investigators questioning Tian Keyu:

During his internship, Tian Keyu launched malicious attacks on the cluster code for at least 2 months (currently traceable) in order to seize cluster resources and backstab his colleagues and the company, including but not limited to:

1. Modifying the cluster pytorch source code, including random seeds and optimizations;

2. Randomly killing multi-machine experiment processes, causing the large-scale experiments to get stuck;

3. Opening the login backdoor through checkpoint to automatically launch attacks;

4. Participating in the cluster troubleshooting daily meeting and holding meetings according to the troubleshooting ideas of colleagues;

5. Modifying the model weights of colleagues, causing the experimental results to be irreproducible.

It is hard to imagine how malicious Tian Keyu was when he saw his colleagues’ large-scale (card-intensive 大卡) experiments inexplicably interrupted and failed, when he modified the attack code in a targeted manner after hearing their debugging ideas, and when he saw his colleagues working all night without any progress. He continued to launch attacks to achieve his goals.

We are willing to expose more real evidence as the situation develops and your shameless whitewashing behavior continues. We guarantee the authenticity and correctness of all evidence, and we bear legal responsibility for the content of the evidence. If necessary, we are willing to lift anonymity and confront Tian Keyu face to face.

Checking in with some industry friends, the consensus is that a cracked intern could pull this off solo if a firm had lax security controls. What’s weirder to contemplate is the motive, particularly when you’ll probably end up getting caught, will never get a job again, and could certainly face jail time.

People do spiteful things to employers the time (classic scenes include the Office Space printer and Ron Burgundy vs Veronica Corningstone), but it’s not inconceivable that the intern was paid to do this by a competitor. After all, Chinese tech firms play dirty. To illustrate, let’s recall the fate of Bluegogo, a bikeshare company. On June 4th 2017, the app featured a promotion using tank icons around Tiananmen Square. Although most guessed that Bluegogo had been hacked by a competitor, to the CCP that defense was clearly irrelevant. The company, which had raised $140 million and was backed by Alibaba, folded immediately after.

This entire incident also recalls a passage from former OpenAI employee Leopold Aschenbrenner’s interview with .

Last year, I wrote an internal memo about OpenAI's security, which I thought was egregiously insufficient to protect against the theft of model weights or key algorithmic secrets from foreign actors. I shared this memo with a few colleagues and a couple of members of leadership, who mostly said it was helpful.

A few weeks later, a major security incident occurred. That prompted me to share the memo with a couple of board members. Days later, it was made very clear to me that leadership was very unhappy I had shared this memo with the board. Apparently, the board hassled leadership about security.

I got an official HR warning for sharing the memo with the board. The HR person told me it was racist to worry about CCP espionage and that it was unconstructive. I probably wasn’t at my most diplomatic and could have been more politically savvy. I thought it was a really important issue. The security incident made me very worried.

The reason I bring this up is that when I was fired, it was very made explicit that the security memo was a major reason for my being fired. They said, "the reason this is a firing and not a warning is because of the security memo."

With lax controls, you don’t need state actors to mess up your training clusters; a sharp 24-year-old could do the trick.

Clearly there was something special in the water in OpenAI 2018-2022 that gave them the organizational freedom to explore and exploit the ML possibility space better than any other AI lab on the planet. That era was characterized by lax security and a culture of internal knowledge diffusion, a vibe which helped attract and get the best out of top researchers. But is a tradeoff between that freewheeling research energy and the sort of internal controls necessary to stop an intern, much less a state actor, from messing up your billion-dollar training runs. Which lab, then, will find the right cultural balance once the financial and national security stakes are too high for such shenanigans to take place with so little friction?

Taiwan’s Magical Healthcare System

This week’s ChinaTalk YouTube documentary explores the magic of the Taiwanese healthcare system, which consistently ranks #1 globally.

Book Review — Private Revolutions

Angela Shen graces the newsletter with a book recommendation just in time for the weekend. Private Revolutions: Four Women Face China’s New Social Order is the newest book by British journalist and Labour parliamentarian Yuan Yang 杨缘.

Private Revolutions follows the stories of four real women from all across China — June, Siyue, Leiya, and Sam — as they endeavor to forge better lives for themselves.

Yang and her female protagonists do not wallow in their misfortune, nor do they spend much time pointing fingers at the cultural norms, government policies, or economic changes that helped create many of the obstacles they face. 

Instead, the women’s stories speak for themselves — they are natural microcosms of China’s broader trajectory, woven together by Yang’s skillful integration of contextual details and personal history. The book flows chronologically, rotating between the protagonists and documenting how each woman’s life changes with the flow of China’s rapid development.

The book offers a nuanced view of China’s urban-rural disparities, the effects of industrialization and privatization on factory workers, the competitive and deeply unequal educational landscape, the rise of the nouveau-riche, the lack of childcare and community support for women, and more. Here are some moments that stuck with me: 

• Fifteen-year-old Leiya persuades her fellow leatherwear factory workers to have fun in the city before their micro-managed shifts (and eventually, they resign together)

• June, born in a village, moves to Beijing to join an ed-tech start-up. Her job is to  convince anxious parents to buy online education programs using a follow a step-by-step sales model

• Single mother Siyue cultivates a support system to care for her baby daughter, which includes help from female friends and Siyue’s widowed mother 

• Sociologist Sam volunteers for a left-wing blog, which leads her to mobilize donations and legal support for student activists 

This book is a powerful depiction of the struggle for social mobility in China’s new capitalist era.

Read it, and bear witness.

Weibo Doom Scroll of the Week

“The internet is the biggest source of democracy; security cameras are the biggest source of justice.”

Warning: this post discusses sexual violence.

“Real story, guys.

Girl from a normal family, real pretty so she got a second-generation politician boyfriend [basically like a trust fund brat, but instead of having a rich dad, you have a high-ranking government official dad]. One day, her boyfriend called her out to a hotel for a date, so she dressed up all nice and went. After she got there, she found that it wasn’t just her boyfriend there, but a couple of other trust fund brats.

And her boyfriend gang raped her with all his friends. The girl fought back as hard as she could, screamed for help, but nobody came. She ran out of the hotel room naked into the corridor and got pulled back into the room. A lot of guests were alarmed and some people filmed it on their phones for evidence.

Later on, she sued her boyfriend, and the judge ruled that the case didn’t constitute rape or gang rape, so she lost the case.

She had to resort to the court of public opinion in her appeals to manage to flip the case. Dunno how many years those trust fund brats got sentenced to.

Why do I tell this story? Because I’ve been seeing a lot of gossip lately. Some netizens who think they have a lot of life experience is always arrogantly telling the victim, “If you think your rights were violated, go call the polite. Go take it to court. Why expose all this on the internet? Aren’t you defaming the other side?”

Some people saying this are just naive, some are young, some are dumb, and some are just evil.

Calling the police or suing does absolutely nothing for a lot of cases. They’ll either muddy the waters and not do anything, or punish both sides equally, or even worse, just outright protect the criminals. It’s only when the victim has nowhere else to go, no one else to turn to, that they take things to the internet. If they had any other option at all, nobody would want to expose themselves to all kinds of judgement on the internet. Because once you expose things on the internet, there’ll be people saying all sorts of shit. There’s a big market out there for victim blaming.

I’ve always been a proponent that the internet is the biggest platform for democracy in China.

It’s only when things are exposed on the internet that we get to see these monsters in the light of day. That’s the only reason they might hesitate at all before hurting somebody. It’s one more layer of security for peasants like you or me.”

From the comments:

“Without the internet, we would be in eternal night. The internet is the biggest source of democracy, security cameras are the biggest source of justice. A phone means that everyone has a platform to speak.”

Song of the Week — Alexa Pan

“Star” (星）by Supermarket （超级市场）

This song is for the hopeful romantics and electronica nerds. Founded in 1996, Supermarket is often hailed as the first “real” mainland Chinese electronic band. In the last three decades, they’ve survived lineup shuffles (with only one original member, Tian Peng, still at the artistic helm), played with Portishead, and steadily grown a cult following and an enduring catalog. Recently, they’ve shot to mainstream fame via China’s rock music reality show, The Big Band, emerging as a standout act and still more or less alone in their genre. 

“Star” is an outlier on their 2003 album, “Concert”, which otherwise showcases trip hop, rock, ambient, and deep house tracks with sophisticated production. “Star” is my favorite track — it is short, ethereal, and blends acoustic guitar with synthesizers to produce a glorious, alien effect. I hear: shimmery starlight; a guitar strumming —grounded and foreboding; sweeping synth lines rising out of the stars as carpet or spaceship; vocals by folk singer Wang Juan tenderly sending them to orbit.

The lyrics borrow from a scene in the movie “Before Sunrise” (“Limousine Eyelash/ Oh, with your pretty face/Drop a tear in my wine glass”) before moving down to earth (“I’d like to soar with you lying down/ Occasionally so soothing”).

There is no more I can say, except that I hope “Star” brings you this feeling when you need it — warm, dreamy, floating in space, inarticulate and comforted.

Lin Hung-wen 林宏文 is Taiwan’s top tech journalist, with decades of experience covering semiconductors, biotechnology, and Taiwanese industrial policy.

His book, The Radiance of the Chip Island: TSMC, Semiconductors, the Chip War, and My 30 Years of Journalism, explores the geopolitics of semiconductors from a uniquely Taiwanese perspective.

We ran an interview in Chinese with Lin on the feed last week (Apple Podcasts, Spotify). An English translation of Lin’s book will be published in early 2025. What follows is a translated transcript of our conversation.

We discuss:

• The underexplored story of Taiwan’s industrial policy, from subsistence agriculture and child labor to the rise of TSMC,

• The role of the Taiwanese government in facilitating semiconductor development,

• TSMC’s management model, including the balance between R&D and manufacturing departments, and talent cultivation strategies,

• How TSMC battled international competitors like Samsung and Intel for dominance of the semiconductor industry,

• The impact of the AI era on Taiwan’s international relationships,

• TSMC’s role in global geopolitics, and the origin of the term “Silicon Shield,”

• The differences between Taiwanese and American views of international relations, what these differences mean for Taiwan’s foreign policy.

Hosting today is Arrian Ebrahimi of the Chip Capitols Substack, with cohosting support from ChinaTalk editors Lily Ottinger and Nicholas Welch.

Taiwan’s Industrial Policy History

Arrian Ebrahimi: Mr. Lin, welcome to ChinaTalk. To start, can you explain the main thesis of your book?

Lin Hung-wen: I wrote this book with the main purpose of addressing what I saw as a gap in the existing literature. In 2022, when I started writing, I had read several books related to chips, such as Chris Miller’s Chip War and Yasu Ota’s The Geopolitics of Semiconductors. While these books were well-written and explored the semiconductor industry from different angles, I felt they lacked a perspective from the actual happenings in the semiconductor industry, especially in Taiwan.

Over the past 30 to 40 years, the global semiconductor industry has undergone a dramatic transformation. We’ve seen a paradigm shift from vertical integration to vertical specialization, from IDM (Integrated Device Manufacturer) to fabless and foundry models.

Taiwan seized a significant opportunity in this trend of vertical specialization. Companies like TSMC and UMC rapidly developed in the wafer foundry business. Additionally, Taiwan has numerous IC design houses and has also captured opportunities in packaging and testing markets.

Taiwan has seized the biggest opportunities in the professional specialization roles that emerged from the disaggregation of IDMs. I felt that Taiwan’s experience was crucial — yet other books didn’t mention Taiwan’s development.

How did Taiwan rise? Why can TSMC fabricate over 90% of the world’s advanced processors? Why do Taiwanese packaging houses account for nearly 60% of the global market share?

It seems every country has a version of the CHIPS Act. But subsidizing semiconductors without understanding how Taiwan succeeded is dangerous.

All these countries investing might labor in vain and fail in manufacturing.

Nicholas Welch: Let’s take a step back from current events and discuss TSMC’s history.

I’d like to ask how much of Taiwan’s semiconductor strategy can be attributed to fortunate/lucky economic planning after World War II. For example, consider the influence of Yin Chung-jung 尹仲容, who had a background in industrial engineering. In the 1950s, he established a model where key economic planning was led by industrial engineers rather than professional economists. This laid a good foundation for the Taiwan government to fully support TSMC in the 1980s and justify this approach on national security grounds. However, when Yin Chung-jung was in charge of Taiwan’s economy, semiconductors hadn’t even been invented yet.

Did Taiwan’s industrial policy planners foresee that Taiwan would one day dominate high-tech industries?

Lin Hung-wen: I don’t believe that Yin Chung-jung ever imagined that Taiwan would build the world’s most important foundry business. I’m certain they never considered such a possibility.

When they were promoting industrial development back then, Taiwan was in a very different situation. In the 1950s, after World War II and the relocation of the Nationalist government to Taiwan, the island had virtually no industry. There were only some light industries like textiles.

In fact, Taiwan’s economy in the 1950s was mainly based on home workshops producing items like Christmas lights or umbrellas for the US market.

Taiwan had very weak economic strength, with no heavy industry or electronics industry to speak of. At that time, they likely didn’t understand how important integrated circuits would become. I believe the government officials of that era didn’t have a deep understanding of semiconductors. However, they were willing to trust some experts who had returned to Taiwan. They allowed these people to help, including Morris Chang 張忠謀.

Another important factor was that Taiwan’s technology came from RCA through licensing. RCA was an American semiconductor company that was preparing to exit the industry. Taiwan asked for RCA’s help. Later, Taiwan sent people to learn from RCA. We called them “knowledge-seeking ambassadors” — about 40 to 50 people who brought back RCA’s technology.

Following this, the establishment of Hsinchu Science Park and the Industrial Technology Research Institute (ITRI) were crucial steps. Looking back now, it might seem like they were incredibly farsighted and had grand visions. But in reality, it was just a step-by-step process of improvement.

Now, suddenly, because of the US-China tech war or because of COVID, everyone has realized that TSMC is making all the world’s semiconductors.

Before that, who really cared about TSMC? Globally, I was probably the most dedicated person following TSMC. Not many people paid attention to it because it didn’t have its own products — it was just a foundry.

Lily Ottinger: We’ve been discussing the step-by-step development process, but I’d like to talk about Taiwan’s history and industrial policy strategies in more detail.

After the Nationalists arrived in Taiwan, the government implemented the “Land to the Tiller” 耕者有其田 redistribution program. That facilitated huge gains in agricultural productivity and economic growth, which enabled subsequent generations to go to school and pursue careers outside of subsistence agriculture.

But between land redistribution and the modern day, what specific policies were most crucial for enabling TSMC’s success in manufacturing? In the step-by-step process you mentioned, which steps do you consider most important?

Lin Hung-wen: For TSMC, I think the most important factors were talent, capital, and technology. Regarding talent, as I mentioned earlier, many people brought back technology from RCA training. Taiwan’s education system, especially in science and engineering, is quite strong and practical. People are very diligent and willing to work overtime. These are characteristics of Taiwanese engineers.

When Morris Chang came to Taiwan, he discovered these qualities and believed Taiwan could succeed in contract manufacturing. However, he didn’t think Taiwan would be successful in IC design, which is why he focused only on wafer foundry.

As for technology, we already had the RCA technology transfer. Another crucial factor was the development of the PC industry. Many talented individuals in Taiwan were involved in PC development. Taiwan became a significant producer of PCs, including desktops and laptops, with many companies also producing in mainland China. This created opportunities, as PCs required semiconductors. The PC industry became a crucial carrier for Taiwan’s semiconductor industry, providing an outlet for many chips used in PCs.

Regarding capital, Taiwan’s private sector resources have always been quite strong. There was a period when a lot of Taiwanese investment went to mainland China, so capital and talent flowed there. However, in recent years, capital has been flowing back to Taiwan, so funding has generally been abundant.

Arrian Ebrahimi: I have a question about the role of the government. You’ve previously discussed the different roles of the Legislative Yuan (the law-making branch of the Taiwanese government) and institutions like Academia Sinica. Can you explain the significance of these institutions to overseas readers?

Lin Hung-wen: The Taiwanese government did quite a lot in terms of industrial infrastructure. The Legislative Yuan’s crucial contribution was creating the Industrial Technology Research Institute (ITRI). The technology licensing from RCA was all done through ITRI. ITRI is a government-led research institution, but it’s not like many advanced research institutions in the US — Taiwan’s ITRI focuses more on commercializing technology.

ITRI was also involved in PC and communications technology, which were important areas, but semiconductors were perhaps their most significant contribution. The people we sent to RCA to learn came back and initially worked at ITRI. They started with 3-inch and 4-inch wafers (now we’re at 12-inch). A key point is that they established a commercial production line at ITRI. This wasn’t just in a lab — it was capable of mass production.

ITRI played an important role in Taiwan’s ability to seize opportunities in the global semiconductor vertical division of labor. We know that companies like UMC and TSMC all spun off from ITRI. So the predecessors of these companies, their teams, and their talent — ITRI played a crucial role in all of this.

Many countries around the world are now looking to learn from ITRI about how they did this back then. ITRI was a very important starting point. The science park that came later was another crucial element. The science park housed companies like UMC and TSMC — essentially providing a single window for the government, allowing businesses to achieve scale and accelerate production.

Government regulations also favored these companies in terms of exports.

Arrian Ebrahimi: You used the word “predecessor” very aptly, and I asked this question to emphasize that the Taiwanese government has been supporting its industry all along.

I remember Morris Chang complaining in an interview with Chris Miller that Chip War overemphasized the role of the Taiwanese government, saying they didn’t help him that much. But when you look at the talent and basic technology contributions from Academia Sinica and especially ITRI, the Taiwanese government’s support was really substantial.

Now, let’s start talking about some topics internal to TSMC, especially the different roles of their R&D department and engineering. Which aspect of the company do TSMC’s leaders value more — technological development or operational perspective? To ask a more specific question, would TSMC CEO C.C. Wei 魏哲家 be more excited about the R&D department’s contribution to the next generation of nanometer process invention, or about a 1% efficiency improvement announced by various factories? Which news would the president of TSMC be more eager to hear?

Lin Hung-wen: In my opinion, both are extremely important, but their importance varies at different times. In the early days, when TSMC’s technology wasn’t leading, they focused more on catching up technologically. When TSMC was founded, its technology lagged behind the world’s most advanced by about three to four generations. Now, of course, it far surpasses others.

TSMC’s technology leadership is crucial and ongoing. Today, we see TSMC as very powerful because its technology far exceeds that of its competitors. But you need to understand that TSMC’s technology was once behind. It wasn’t until around 2000 or 2001, at the 0.13 micron (130 nm) node, that they successfully developed their technology and started to show signs of leadership. Even then, they weren’t fully ahead.

It wasn’t until 2009, when Morris Chang returned as CEO, that they aggressively invested in 28nm technology and slowly surpassed others. Now, at 7nm, 5nm, and 3nm, they are leading. So from start to finish, technological leadership has always been extremely important.

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However, the efficiency improvement you mentioned is something TSMC has always paid close attention to. In addition to technological leadership, operational excellence is crucial in wafer foundry. Good yield, short cycle time, and low cost all directly affect profitability. TSMC places great emphasis on efficiency improvements. They work on this every day, and all their engineers work overtime for this purpose.

So both aspects you mentioned are very important. Mr. C.C Wei now needs to focus on both. Technology must continue to lead for TSMC to maintain its high profitability and create high value for customers. Without technological leadership, it wouldn’t work because others are always catching up.

However, there’s another aspect that’s even more important than these two: customer-service satisfaction. From beginning to end, TSMC has always prioritized serving customers and maintaining high satisfaction. It’s not just about leading in technology or improving efficiency.

For example, if you look at TSMC’s competitors like Intel and Samsung: Intel had leading technology early on, but the problem is that Intel has its own products. Samsung also has its own products. When you have leading technology, do you use it for customers or for yourself? Honestly, this creates a conflict. In Samsung’s case, when they have leading technology, they might use it for their own products first and not give it to customers because they want their own products to be good.

So technological leadership isn’t actually the most crucial thing for a company like TSMC. The most important thing for TSMC is customer service and satisfaction. If customer service is good, then technological leadership and efficiency improvements are all for the benefit of customers.

TSMC has over 30 important customers, and these customers often change their product plans. Sometimes they urgently need something and ask TSMC to quickly adjust production to deliver goods earlier. So TSMC has to change its factory production process from top to bottom. Therefore, efficiency improvements are ultimately about serving customers.

I know Mr. C.C. Wei now arrives at the company at 4:30 a.m. every morning. Why? To serve customers. He can call and talk with European and American customers at that time to understand their needs. Serving customers is the key to TSMC’s success.

Arrian Ebrahimi: Mr. Lin, you’re mainly saying that R&D and efficient factories have made different contributions at different historical moments. At some points, one aspect may have played a more important role, while at other times, both were equally important.

But may I ask, why are most of TSMC’s leaders trained in factory management rather than coming from the R&D department?

This relates to another question: since management and R&D play different roles — and the importance and strategic value of these two departments vary at different times — why did Morris Chang want his successors to take turns leading different departments? It seems that most of them initially came from engineering, but later Chang decided to let them experience every department. Can you explain a bit about this internal management approach?

Lin Hung-wen: Yes — you’re referring to when he had Mark Liu 劉德音, C.C. Wei, and Chiang Shang-yi 蔣尚義 rotate through R&D, business, and wafer-fab management. I think this was basically Morris Chang’s way of ensuring that a CEO would be very familiar with all three departments. So he had them rotate through different positions to gain different experiences.

It was also a way for Morris to test them. Being a CEO isn’t just about ability — it’s also about how one handles different challenges. How do they react when faced with tests? Do they panic or handle situations calmly? I think this was all part of the testing process.

He used this method to let each of them hone their experience and mature their ability to handle situations and face challenges. So I think it’s natural to have successors experience different departments. This is an important process.

Arrian Ebrahimi: Although Morris Chang is retired, it feels like his shadow is still there, right? I’ve heard that some people still call him “Grandpa.” Does this role actually exist, or is it just something people discuss?

Lin Hung-wen: I think calling him “Grandpa Chang” is quite natural because he’s in his 90s now, so he could be everyone’s grandpa. I believe he’s still a spiritual leader. Although he’s no longer working in an official capacity, I believe he still has a lot of influence. I’m sure he still provides guidance to younger generations, though he probably doesn’t initiate it. But I imagine many people still seek his advice.

For instance, I think C.C. Wei might consult him if there are important matters. So I believe his influence is still there. Even now, I know that many US congressmen, senators, and state governors who visit Taiwan always hope to meet with him and hear his opinions. I think this is quite natural.

Arrian Ebrahimi: That’s a kind of filial piety, which is good.

Formidable Competition and TSMC’s AI Future

Arrian Ebrahimi: Let’s discuss TSMC’s battle with Samsung more specifically. Your book highlights this quote from TSMC founder Morris Chang: “Samsung is a formidable but not admirable competitor” 三星可畏，但不是可敬的對手. 

What did Morris Chang mean by this?

Lin Hung-wen: Morris Chang said this in a very specific context. A reporter was asking him a question about TSMC’s competition with Samsung, and before the reporter could finish, Morris interrupted and said, “I didn’t say they were admirable, I said they were formidable.” He emphasized the word “formidable” several times in English.

Morris has never explained why Samsung is not admirable — he wasn’t emphasizing that part. But he did stress that they are formidable. In Morris Chang’s words, Samsung is like a 700-lb gorilla. Intel used to be a gorilla too, but they’re struggling now.

The key point is that Samsung became number one in many fields they’ve entered — whether it’s memory, phones, or TVs and displays in the past.

As for their competitive methods ... well, I understand this because I wrote a book about Samsung in 2012, describing them as a “financial crocodile.” I wrote that book because, at that time, Samsung was beating many Taiwanese industries badly. Taiwan’s position was miserable (辛苦), Taiwan’s flat-panel display industry was suffering, as were many other industries — all beaten by Samsung.

I understand why Morris Chang calls Samsung formidable. He’s never criticized Samsung, but he once shared an experience. Very early on, when he returned to Taiwan and was still at ITRI, before founding TSMC, he was invited by Lee Kun-hee, the previous chairman of Samsung (the father of Lee Jae-yong), to visit Korea. He went with Stan Shih 施振榮, the founder of Acer, and some others from ITRI. Lee Kun-hee showed them Samsung’s DRAM investments and essentially said, “Don’t invest yourselves — just come work for me.”

Morris, of course, didn’t give an answer. He felt he could do better by returning to Taiwan, and he wanted to start his own company, not work for Samsung. When he talks about this incident with Samsung and Lee Kun-hee, I think he’s clear that he believed he had the ability and ambition to build a company that could compete with Samsung.

Everyone knows that before returning to Taiwan, Morris was already the general manager of the semiconductor business at Texas Instruments. He was a very important leader in that company. So I think he had high expectations for himself. Of course, when he first founded TSMC, it was tough, but his goal was to build a very important company with great influence. This is my understanding of his comments about Samsung.

Arrian Ebrahimi: You recently published an article titled, “The AI ​​Era Drives Reorganization of the Semiconductor Landscape! TSMC chose to cooperate with SK Hynix, causing Samsung to lose everything.”

Could you please explain how AI chips are affecting the memory industry and Samsung’s leading role? What impact have they already had?

Lin Hung-wen: Thank you for this question. It’s a very good topic, especially as SEMICON is currently being held in Taiwan.

The impact of AI is very dramatic. Everyone sees NVIDIA taking off because of the AI era, with its stock price soaring, but there are many stories behind this.

This year’s Taiwan semiconductor conference is very interesting. Samsung and SK Hynix have sent their most important people to Taiwan. In the past, Samsung and Hynix would send some people to attend Taiwan’s semiconductor exhibition, but never their top executives. This time, they all came. Why? Well, here’s some other interesting information: in the first half of 2024, Korea’s semiconductor exports to Taiwan increased by more than double.

What does this mean? The AI server chips, as we know, have NVIDIA as the most important customer, and TSMC helps with the manufacturing. Because these AI chips need to be power-efficient, high-performance, and well-packaged, they now package logic ICs (SoC) and HBM together. That’s why Korea’s memory exports to Taiwan have grown so much — NVIDIA needs these AI server products, and they need to package GPUs and HBM together. We call this CoWoS (Chip on Wafer on Substrate) technology.

In the past, system memory and logic chips were separate and could be shipped separately. But now, because TSMC controls the most advanced process technologies and NVIDIA places all its orders with TSMC, the HBM memory must be packaged together.

This has produced a very significant effect. Yesterday, I heard executives from Samsung and Hynix speak. One Hynix executive said he had already been to Taiwan more than a dozen times this year. They need to constantly discuss with TSMC how to package HBM together through CoWoS packaging. There are many areas where they need to collaborate.

As for Samsung, because TSMC and Samsung are competitors in wafer foundry, TSMC tends to support Hynix and Micron, the other two memory manufacturers. Samsung, of course, tends to be excluded. This can’t be helped — it’s the reality of competition.

Taiwan’s Startup Ecosystem and TSMC for Biotech

Lily Ottinger: Mr. Lin also writes articles covering biotechnology. The Taiwanese government has launched a state-owned biotechnology company called TBMC, which sounds like the biotechnology version of TSMC.

I’d like to ask, what are the differences between foundry manufacturing for integrated circuits and foundry manufacturing for biotechnology? What technical challenges might TBMC face?

Lin Hung-wen: Thank you for reading my articles so carefully. You’re right, I did write about TBMC and TSMC. When TBMC was being funded, they explicitly stated they wanted to emulate TSMC’s model, including partnering with the American Resilience Group. Resilience holds a 27.5% stake, which is the same percentage that Philips held in TSMC initially. They hope to create a successful model for biotechnology manufacturing in Taiwan, similar to what TSMC did for semiconductors.

However, I believe there are significant differences between these two industries. Biotech production processes are less complex, with about 30 steps, while semiconductor manufacturing involves around 1,500 steps. This difference in production complexity results in different entry barriers. Biotech manufacturing is relatively easier to enter, while high-end semiconductor manufacturing, especially for advanced processes, is much more difficult, leading to fewer competitors.

The investment amounts also differ greatly. A 12-inch semiconductor fab now requires at least US$10 billion in investment, which is over NT$300 billion. Many biological factories, on the other hand, only require NT$1 to 3 billion in investment. This hundredfold difference in investment further highlights the higher entry barrier for semiconductors.

Lastly, the products and cost structures of these industries are very different. For example, the production cost of Viagra accounts for only 0.7% of its price. If you reduce manufacturing costs by half, it only decreases the overall cost by 0.35%, which has a minimal impact. In contrast, semiconductor costs account for a much larger portion of the final product price. When TSMC uses the best technology to produce NVIDIA’s GPUs, the cost reduction is substantial.

IC functionality is also very powerful and continuously improves while prices decrease due to Moore’s Law. A single smartphone chip now uses 16 billion transistors, which is more than twice the world’s population. Pharmaceuticals, however, tend to become more expensive over time because they save lives, and the demand for healthcare is inelastic.

These fundamental differences between the two industries mean that TBMC faces many challenges, and its future success is uncertain.

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Arrian Ebrahimi: Thank you, Mr. Lin. You mentioned the entry barriers, which leads me to my next topic — TSMC’s support for Taiwan’s startup ecosystem.

As someone who grew up in the western United States, I’ve seen my high school classmates jump from company to company, gaining industry knowledge until they create their own startups, which may fail, leading them to join large companies before trying again.

How would you compare Taiwan’s and America’s startup cultures, especially regarding job-hopping?

Lin Hung-wen: Taiwan’s situation is more similar to Silicon Valley. Job-hopping is very common in Taiwan because our industrial structure is dominated by small- and medium-sized enterprises (SMEs). Taiwan has 1.5 million SMEs, of which 1.4 million have fewer than 5 employees. This is quite different from Japan and Korea, where large conglomerates dominate and people often work for one company their entire lives.

The key difference is that Taiwan has a strong entrepreneurial spirit. In SMEs, people often have ownership stakes, making them more willing to work hard because they’re working for themselves. This entrepreneurial spirit is similar to Silicon Valley.

However, the form of entrepreneurship in Taiwan differs from Silicon Valley. Taiwan specializes in professional manufacturing within the global supply chain. Many Taiwanese companies do contract manufacturing for large American companies like Google, Amazon, and Facebook. Taiwan has seized opportunities in industrial specialization.

For 30 years, the most common news in Taiwan’s tech industry has been about “concept stocks” related to companies like Apple, Tesla, HP, and Dell. We focus on which Taiwanese companies are doing contract manufacturing or supplying components for these global brands. This structure of specialization continues today with companies like NVIDIA.

Arrian Ebrahimi: Mr. Lin, you’ve mentioned that Taiwan’s small companies are often supporting American big companies. Is it true that Taiwan’s startups are mostly in the chip industry, revolving around TSMC? Is their only goal to provide inputs and technology that TSMC needs?

Lin Hung-wen: That’s not entirely accurate. Taiwan doesn’t just have semiconductor companies. We have a significant PC industry with companies like Foxconn, Quanta, Compal, and others. We also have companies in various related fields, such as Largan Precision, which makes lenses for iPhone cameras, and many companies in networking and communications.

Taiwan also has a large industrial computer sector. While it’s true that many companies support TSMC, providing equipment, materials, and components that TSMC doesn’t develop in-house, this is just one part of Taiwan’s diverse tech ecosystem.

For example, with the rise of AI servers, heat dissipation has become crucial. Many Taiwanese companies are developing solutions for this challenge. So, Taiwan’s startups cover a wide range of technologies and industries, not just semiconductors.

International Isolation: The Chip on Taiwan’s Shoulder

Arrian Ebrahimi: I’d like to ask a potentially sensitive question: which is more important, TSMC or the Taiwanese government?

Lin Hung-wen: That’s a profound question that kept me up last night. It touches on a crucial point for Taiwanese people. Before 2018, when the US-China conflict intensified, the world didn’t pay much attention to Taiwan. Many Western observers were focused on China’s rapid growth over the past 30 years.

Both the Taiwanese government and TSMC are extremely important. The Taiwanese government represents our democratic system, chosen by the people’s votes. It embodies the direction we’ve chosen for ourselves after years of struggle.

TSMC is also crucial. It’s unprecedented for a Taiwanese company to reach such technological heights and play such a vital role in global chip production. For a small island of 23 million people to produce a company that influences the entire world and ranks among the top 10 globally by market value is a great source of pride for Taiwan.

Arrian Ebrahimi: This year, TSMC has accepted invitations from many countries to expand production abroad. It seems that the United States, Germany, and Japan are all grateful for TSMC’s cooperation. How should Taiwan seize this opportunity to enhance its international status?

Lin Hung-wen: I often give lectures in Japan, and I always say that I’m able to publish books thanks to TSMC’s success. Because TSMC is so successful, everyone pays attention to it, and the books I write sell well because everyone wants to read about it. But more importantly, I think Taiwan as a whole should capitalize on TSMC’s success.

People are thinking about how TSMC is now investing in the US, Japan, and Germany. In the past, many Taiwanese businesses invested in mainland China or Southeast Asia. We called it “westward expansion” or “southward expansion.” But those expansions were aimed at lowering costs, taking advantage of better production conditions in those places to earn excess profits.

Now, investing in the US, Japan, and Germany is fundamentally different because the costs in these places are much higher than in Taiwan. In the US, it’s several times higher. TSMC employees sent to Arizona have their salaries doubled, and they’re still paid less than American workers. It’s the same in Germany.

Now, Taiwan isn’t just trying to make money by lowering costs — we’re trying to create value, which is much more difficult. I think Taiwan needs to handle this well. If TSMC can successfully produce in the US, Japan, and Germany, if these factories can operate smoothly, it will involve different corporate cultures. As I mentioned, Taiwanese people are more dedicated to work and willing to work overtime, but American and German employees probably aren’t as willing to work overtime. Even Japanese people aren’t as willing to work overtime now.

There are also language barriers. To be honest, our English isn’t that good. It’s not our mother tongue, so when we go to Japan or the US, there are challenges in communicating with local employees. We see all these challenges.

But regardless, I think the Taiwanese government should use this opportunity to help more people understand Taiwan and its situation.

Taiwan still doesn’t have international status. We can’t even join the United Nations. We don’t have official diplomatic ties with most countries, and our representatives often have to meet foreign officials unofficially to avoid protests from China.

When we participate in the Olympics, we’re called “Chinese Taipei.” We can’t even use the name “Taiwan” without facing suppression.

Taiwan has been on the periphery of the world, just trying to survive.

I think this is a feeling many Taiwanese have in their hearts. It’s hard for us to assert anything because as soon as we do, fighter jets fly over and missiles are pointed at us. Even big brothers like the US tell us what to do. Taiwan is basically a little brother, and our international status is very low, almost non-existent.

But we can only expand our influence through economics and technology. We can make more investments and seize important opportunities in the global industrial division of labor. This is what everyone in Taiwan is working on now.

Nicholas Welch: Do average Taiwanese citizens actually use the term “Silicon Shield” (矽盾)?

Lin Hung-wen: Most Taiwanese people agree that TSMC is indeed a “nation-guarding sacred mountain” 護國神山. TSMC has reached unprecedented heights for a Taiwanese company, leading in technology and playing a crucial role in global chip production. With a market value among the world’s top 10, it’s a source of great pride for Taiwan, a country of just 23 million people, to have produced a company with such global influence.

The term “Silicon Shield” wasn’t invented by Taiwanese people — it originated from foreign media. Since the intensification of US-China tensions in 2018, this concept has gained significance. People realize that TSMC’s production of chips for major global companies in Taiwan means that war cannot occur casually here. A conflict would disrupt the entire global electronics industry, affecting not only economic but also national security, as chips are crucial for missiles, fighter jets, drones, and other security applications.

While average Taiwanese may not discuss the term “Silicon Shield” explicitly, the sentiment behind it is widely understood. Taiwan harbors no hostility towards anyone. We lack international status, so we strive to contribute positively to everyone’s success through our efforts. Our chips enable companies like Apple and NVIDIA to sell more products globally, helping their businesses grow and flourish.

Taiwan primarily focuses on contract manufacturing, with few of our own products. Our industry’s core is built on mutually beneficial partnerships. Taiwan isn’t aggressive; even our fighter jets are primarily for deterrence. In conclusion, while the average person may not deeply contemplate the “Silicon Shield” concept, using semiconductors for self-protection is a common perspective currently.

A Taiwanese View of Geopolitics

Arrian Ebrahimi: Mr. Lin, you’ve just explained the Taiwanese mindset. Now, I’d like to compare the perspectives of different nationalities on international relations, particularly Taiwanese and Americans.

After spending a summer in Taiwan, my observation is that average Taiwanese people seem to care mostly about foreign trends that directly impact Taiwan’s internal development.

In contrast, Americans tend to perceive certain countries as threats to national security, engaging in unfair trade practices, or exhibiting undemocratic behavior. It appears Taiwanese people focus primarily on their island, while Americans consider the entire world order. What do you think of this view, and how does Taiwan’s worldview influence its international strategy?

Lin Hung-wen: Your perception is understandable and natural. I largely agree with your observations, but it’s important to understand the underlying reasons. As I mentioned earlier, Taiwan has been continually suppressed and lacks international status. We have diplomatic relations with only a handful of small countries in Central and South America and Africa.

Taiwan has been on the world’s periphery, while the US is at its center. This fundamental difference in position shapes our respective worldviews.

In Taiwan, our primary concern has been survival. We focus on how others’ actions might impact us and how we can address the resulting challenges. The US, being at the world’s center, naturally considers global issues and seeks to maintain world order, sometimes intervening when situations don’t align with its interests.

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Your perspective is valid because we come from different backgrounds, cultures, and living conditions. Israelis would likely offer a different viewpoint, as would the Japanese, despite our shared Asian heritage and strong work ethic.

Taiwan has transitioned from being a completely overlooked peripheral nation to becoming the center of the global semiconductor industry, which has surprised many. I often use the analogy of stagehands in theater — Taiwan used to be like the black-clad stagehands who move props unseen, working behind the scenes while companies like Apple and NVIDIA took center stage. Now, these “stagehands” have become crucial players.

Taiwan’s fundamental role hasn’t changed; we’re still primarily engaged in contract manufacturing and production within the global supply chain. What has changed is the critical importance of our role. While global trends have shifted, Taiwan continues to perform its core functions, albeit now in a more pivotal capacity.

Lin’s Background and Vintage Tech Journalism 

Arrian Ebrahimi: Let’s close with a discussion of your background. How did your career as a journalist impact the way you wrote the book?

Lin Hung-wen: This is my 31st year covering the semiconductor industry as a news reporter in Taiwan. I started reporting on semiconductors in 1993, and TSMC was established in 1987, so I began following this company shortly after its founding, writing daily news about it.

I’ve also written extensively about the semiconductor industry outside of Taiwan. Over the past three decades, I’ve traveled all over — to the United States, Japan, and Europe. I even went to Scotland three times, back when it was known as Europe’s “Silicon Glen.”

My book was published in Taiwan in July 2023 and in Japan in April 2024. I’ve already been to Japan four times since the Japanese publication, as they’re very keen to understand Taiwan’s success story. I’ve had many exchanges with Japanese friends.

The Korean version will be published by the end of this year, and the English version will be out in the first half of next year. I hope to let everyone know that Taiwan’s development experience is very worthy of reference.

Of course, Taiwan has also had failed cases, and I don’t shy away from discussing these. For instance, Morris Chang was very successful at TSMC, but his first ventures were quite disastrous, and he later had to close down those operations. As a frontline reporter, I don’t conceal facts, but I strive to present Taiwan’s development experience fairly and objectively.

Arrian Ebrahimi: Thank you, Mr. Lin. You mentioned earlier that you’ll be releasing Korean, Japanese, and English versions of the book. What new aspects will you cover in the English version? How will you tailor the content for new audiences?

Lin Hung-wen: For the English version, I’ve added more current content. I’ve added a lot of new developments, including how AI is driving changes in the semiconductor industry, and the integration of SOC (System on Chip) and HBM (High Bandwidth Memory). These developments have had a significant impact on the industry.

I’ll also include more topics that English readers in America and Europe are interested in. For instance, TSMC is now starting to build a plant in Germany, so I’ll include some European developments as well.

Arrian Ebrahimi: I’m still curious about you personally. You mentioned that you started as a journalist around the same time TSMC was founded, not long after. Since you studied at National Chiao Tung University 國立交通大學 for your undergraduate degree, journalism probably wasn’t the most likely career path for you, right? I’ve lived in Hsinchu, and most people there dream of becoming engineers. Why did you want to become a journalist?

Lin Hung-wen: National Chiao Tung University should be familiar to many friends in Taiwan and mainland China. Essentially, Taiwan’s Chiao Tung University was re-established in Taiwan after the separation of the two sides of the strait, originating from the Chiao Tung University in mainland China.

Chiao Tung University is one of the top institutions for science and engineering. After studying there for four years, I realized I might not be suited to be an engineer. So after graduation, I became a journalist. I chose journalism because I enjoyed writing.

After becoming a journalist, I found it quite suitable for me. On one hand, I enjoy writing, and it’s a great pleasure for me. I often get to talk with many people and meet industry leaders. Standing on the shoulders of giants, I can see far.

Another important factor is that with my science and engineering background, I found it easier to cover this industry compared to journalism graduates who might face more obstacles. As I mentioned earlier, through my news coverage, I’ve gained many insights. Covering an industry isn’t just about writing industry news; I’ve seen a lot of competition between countries, economic and industrial development, and now geopolitical developments.

Through this industry, I’ve gained knowledge in many other areas. This exploration has been very interesting to me. Every day, I wake up with a pile of things to understand, analyze, and explore. I find this to be a very happy journey of exploration in my life.

Arrian Ebrahimi: You mentioned that you’ve been a journalist for over 30 years, and this book is based on your interviews and reports over these years. Before discussing the process of writing this book, could you first tell us how you entered the chip industry and became a specialized journalist in this field? Then, how did you summarize your 30 years of experience into one book?

Lin Hung-wen: When I started covering the semiconductor industry, it was my supervisor at the newspaper who assigned me to it because there was a vacancy. They thought that with my background at Chiao Tung University, I could quickly take on the role.

As you know, Taiwan’s semiconductor development started in Hsinchu Science Park. At that time, I would go to Hsinchu every day, visiting different companies and chatting with people.

Every day, I would compile tables, listing the products, investment amounts, and other details of many Taiwanese companies. I was so young at the newspaper that they called me “Table Brother” — the brother who was good at making tables.

In this learning process, I began to find the chip industry very interesting. Now, everyone knows how important chips are. They’re in your phone, your computer, or anything connected to the internet. But in the early days, it wasn’t necessarily like that. When I first started reporting, it was mostly about consumer ICs, like those found in toys.

Young people might not know this, but we used to have musical greeting cards for Christmas. When you opened them, there would be a music IC that would play a tune. Taiwan used to make many of these audio ICs. Then, as telephones (not mobile phones, but desktop phones) started to develop, Taiwan slowly moved from these small consumer ICs into PCs.

Now we’ve entered the AI era with GPUs. I feel that over these 30 years, I’ve grown alongside the semiconductor industry. I started knowing nothing and gradually came into contact with many aspects of the industry’s development.

Many Taiwanese companies have gone through this process. As I mentioned, there have been several generations of different ICs. Taiwan has been slowly capturing these opportunities. Not all companies in Taiwan have successfully transformed, but some have. For example, MediaTek initially made ICs for PC-related optical drives, but when smartphones took off, they seized the opportunity.

The English version of Lin Hung-wen’s book, (working English title — Chip Island: How TSMC and Taiwan Triumph) will be published in early 2025. We highly recommend you check it out!

Lin’s song of choice:

The entire project of ChinaTalk, at the heart of it, is to help raise the quality of conversation and help inform policies that would most likely avert WWIII. I’m worried Trump would do a far worse job avoiding the big one than Harris. Here’s a piece on the topic I co-authored with Peter Harrell, formerly of the Biden NSC and NEC, with some riffs on export controls and acquisition reform below.

Former President Trump has made his promise to “prevent World War III” central to his campaign to return to the White House. But Trump’s foreign policy agenda is far more likely to drag the U.S. into catastrophic conflict than to prevent it.

Trump’s promise understandably resonates with voters. While President Biden did end the war in Afghanistan and keep U.S. troops out of direct involvement in conflicts in Ukraine and the Middle East, the world is less peaceful today than it was four years ago. In 2022, Russia launched the largest war in Europe since World War II. War in the Middle East makes daily headlines. China has increased the operational tempo of military exercises that threaten Asian allies. 

However, one-off dealmaking with dictators from a position of weakness is a losing strategy to keep the peace between great powers.

Putin and Ukraine

For starters, let’s take Trump’s promise to negotiate an end to Russia’s war with Ukraine. What is Trump’s “secret plan”? Reporting indicates that he would pressure Ukraine to exchange land for peace by cutting off military support. This approach will fail: Even if Trump cuts off military assistance to Ukraine and Ukraine is forced to cede territory to prevent immediate military collapse, Putin’s ambitions will not be sated. His goal is to assert Russian dominance across Eastern Europe — which includes all of Ukraine, the Baltic countries and Poland. Degrading Ukraine’s military in return for a temporary ceasefire only for Putin to renew conflict against a weakened Ukraine months later is disastrous dealmaking.

Trump’s approach to Ukraine would be particularly dangerous given how Trump wants to treat NATO allies in Putin’s crosshairs. He recently said that he would give Russia an explicit pass to “do whatever the hell they want” if NATO members do not “pay [their] bills.” If Putin succeeds in taking parts of Ukraine, this language will embolden him to turn his war machine towards America’s treaty allies in Eastern Europe — which would either drag the U.S. into war, or see the U.S. acknowledge its alliance commitments are worthless. This will seed more conflict, not deter it. To avoid direct conflict with Russia, the U.S. should help Ukraine further advance its military capabilities to force Russia to acknowledge that its maximalist aims are impossible to achieve.

Xi and Taiwan

Trump is also risking war where the stakes may be even higher: East Asia. In a recent interview with Bloomberg Trump responded to a question about America’s commitment to Taiwan by stating: “Taiwan should pay us for defense. You know, we’re no different than an insurance company. Taiwan doesn’t give us anything. Taiwan is 9,500 miles away. It’s 68 miles away from China.” He sees Taiwan not as a democratic ally and bulwark against Chinese regional hegemony, but rather just another country who has wronged the US economically by taking “100% of our chip business.” 

This all amounts to Trump turning America’s eighty-year commitment to East Asian security into a short-term lease renewal negotiation. What Trump plans to do isn’t savvy dealmaking, it’s diplomatic arson.

Mainstream Republican national security thinkers like Elbridge Colby and Mike Gallagher have advocated committing to Taiwan’s defense for principled (preserve a fellow democracy), geopolitical (counter Chinese expansion) and economic (ensure a stable global chip supply) reasons. The credible threat of U.S. military support for allies in Asia today helps dissuade Xi Jinping from invading Taiwan. This of course can swing too far — like Former Secretary of State Mike Pompeo’s assertion that Taiwan should declare independence. Under Trump, both China and America’s key allies in the region would feel far less confident that the US would actually help them resist a Chinese attack.

This loss of faith in America’s commitment to the region risks dramatic consequences. It will encourage Chinese adventurism against Taiwan, raising the odds of a war that ultimately drags the U.S. in. Even though U.S. allies including Japan and Korea have increased their defense spending in recent years, none of them can realistically deter Chinese aggression with conventional weapons without America’s backing. Pulling away from Japan and Korea would prompt them to either lean more towards Beijing or consider going nuclear, injecting more instability in a region where conflict could be truly catastrophic in terms of lives lost and global economic impact.

Preventing WWIII is not a one-off real estate deal, it’s a repeated game which requires signaling across decades to both allies and adversaries that the US is serious about preserving the peace. Since 1945, America succeeded in investing in our military might, alliances and global credibility to deter great power war. Today, America makes up a quarter of global GDP, while China comprises almost 20%. Together with its treaty allies, the US totals over 60%, while China’s closest thing to an ally, Russia, adds just one 1% to its ledger. Preserving this relative balance in national power will allow the US to keep the peace and further its interests far into the 21st century. Risking global realignment to juice up a few acquisitions deals plays right into Xi and Putin’s hands.

For all Trump’s bluster about preventing conflict, his actual policies, like the isolationism of the 1930s, would actually increase the chances of a war far deadlier than even today’s conflict in Ukraine. President Reagan worked with NATO and East Asian allies to show “peace through strength”. Trump’s strategy of treating America’s closest global friends like delinquent renters risks war through weakness.

Back to Jordan sole-authorship. A few more riffs on ChinaTalk-adjacent topics:

Export Controls

AI could really, really matter for long term national power. AI consists of algorithms, data, and compute. Algorithms and data are probably too hackable to drive relative long term national competitiveness. So, we’re left with computing power, which after o1 is even more likely to matter in pushing the frontier from an innovation and diffusion perspective.

What will Trump do with the Biden administration export controls on chips and semiconductor manufacturing equipment? Probably something like what happened to ZTE.

Step one: Trump’s bureaucracy finds a Chinese company flagrantly breaking US law whose continued use of American technology runs directly counter to US interests.

Step two: Trump saved ZTE because he gets a call from Xi.

I wouldn’t be shocked if he just lifted the controls month one as a goodwill gesture. If someone talks him into having a little spine on this issue, he’ll see a huge opportunity for a big deal as Xi would happily give Trump oceans of soybean orders and zoos-full of pandas for a few EUV machines.

There is no domestic political economy constituency for semiconductor export controls. The only political force today keeping them in place are national security professionals who rightly recognize their long term importance. An America First semiconductor policy, particularly in a market defined by scarcity, should aim to make sure all backordered are filled American fabs and datacenters before opening up an export market which would raise prices for US companies to acquire goods from a 3.5tn company and SME firms who have been ripping the past few years. Instead, lobbyists will have far more success than they deserve framing the controls as some deep state conspiracy meant to skew a trade deficit.

Acquisitions Reform

Rule #1 of avoiding wars is having a military scary enough that no one wants to try it. It’s clear as day that the US needs a dramatic overhaul to how it buys capabilities in order to deter wars in Asia.

If I’ve learned anything over the dozens of shows we’ve recorded on defense policy over the past decade, it’s that absent sustained commitment from a president and secretary of defense, we don’t see the reform at the scale we need.

Trump picked his Secretaries of Defense because they had cool nicknames and looked the part. With wars in Ukraine and the Middle East, it will be hard enough for the next Secretary to preserve bandwidth to push the system to change without having to deal with monthly crises in civ-mil relations. I have zero faith in a Trump administration giving this issue the sustained attention it needs to make the progress the US needs to most effectively deter war.

EVs

Maybe less important for the future of humanity, but this one is just weird. Why is he so into BYD making cars in Michigan?

Not that there’s a single swing voter in the ChinaTalk audience … but thank you for indulging me. Back to our regularly scheduled programming later this week.

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Why did the Soviet Union collapse? Which lessons from Cold War history are relevant for China’s future?

To discuss the successes, failures, and strategies of Soviet leaders, ChinaTalk interviewed Yakov Feygin. Feygin is the author of Building a Ruin: The Cold War Politics of Soviet Economic Reform, which examines how various Soviet leaders, institutions, and economists attempted to boost Soviet growth and national power. 

Co-hosting today is Jon Sine of the Cogitations substack.

Listen now on Spotify or Apple Podcasts.

We discuss:

• The strengths and limitations of the Stalinist economic model,

• Khrushchev’s shift to “peaceful competition” with capitalism,

• Alternative policy paths that could have saved the Soviet Union,

• How technological optimism shaped Soviet reform efforts, inspiring the CCP in the process,

• Parallels between the institutions of the Soviet Union and those of contemporary China,

• The battle between political scientists and historians when analyzing the political economy of authoritarian states.

Post-Stalin Policy Struggles

Jonathon Sine: This is an excellent book, Yakov. Let’s dive right in. What’s the main thesis of your book, and how does it relate to the world today?

Yakov Feygin: The main thesis explores Soviet domestic politics and the evolving concept of a socialist project in the post-Stalin era, which is intrinsically tied to the definition of a socialist economy. To understand Soviet politics, one must consider the Soviet Union’s larger global project as an anti-capitalist state. After Stalin’s death, various factions and new ideas emerged, embedding themselves in specific institutions and attempting to reinvent the system.

This reinvention was a rolling political process that continually redefined socialism while ultimately destabilizing the institutional underpinnings that made it coherent. The Stalinist planned economy, despite its intellectual veneers, was built on specific assumptions about how the world, capitalism, and international relations were supposed to work. In a dark sense, it functioned for its intended purpose. However, as society became more complex and the capitalist system evolved — no longer defined by imperialism as Lenin saw it, but by a hegemonic system with American superpower— the old system ceased to be effective.

The question then became, what comes next? This story has resonances with the Russian and post-Soviet political systems to this day and may offer lessons for other comparative systems.

Jordan Schneider: That’s an interesting closer, Yakov. While reading this book, I kept drawing parallels with Xi’s China, Deng’s China, and Mao’s China. Let’s start with Stalin — what was the Stalinist model, and why did it make sense for the USSR at the time?

Yakov Feygin: The Stalinist model shares similarities with other modernization efforts. The core of this model is a macroeconomic principle — rapid modernization requires substantial fixed capital installation, necessitating a high rate of investment. The identity S=I means the savings rate must increase significantly.

Most developing countries have raised their savings rates considerably at the start of their industrialization. The short to medium-term gains from this approach can offset the reduced household consumption, as productivity gains push the economy closer to its production possibility frontier. Many emerging or developing countries undergo this process, which partly explains why the Soviet Union was popular as a model in the 1960s and 1970s.

However, not all countries commit genocide against their peasant classes — that’s a particular feature of Stalinism. To understand why this happened, we must consider the Stalinist worldview.

The 1917 revolution — enabled by fissures in the imperial system — remained within Russia’s borders.

Consequently, the Soviet Union had to modernize rapidly outside the rules of standard profitability to avoid foreign capital influence. This approach — intimately tied to geopolitics in Stalin’s mind — aimed to prepare the country as a base for a longer-term revolutionary process.

This system was designed to achieve high industrial modernity and rapid, large-scale outputs in critical sectors. These weren’t directly military tools but built a framework for independence from capitalism and power to operate in the imperial world, directed towards a larger long-term goal.

Jonathon Sine: It’s interesting how people often forget the high growth rates under Stalin. Even later, economists predicted the Soviet Union would overtake America within a decade or two. The party served as a mobilizational element underpinning this forced industrialization drive.

Could you describe the key institutions that Stalin put in place for a planned economy, especially since China today doesn’t have a planned economy in the same sense as the Soviet Union?

Yakov Feygin: That’s an excellent question. The Stalinist planned economy was chaotic, as detailed in works by scholars like Paul Gregory. The plans weren’t really plans — they were more like throwing ideas at a dartboard to see what stuck. There was a veneer of planning in the institutions, but they didn’t accomplish much.

The first five-year plan relied entirely on inertia and trial and error, often enforced through extreme violence and repression, especially of the peasantry.

Starting from a low base with a large population surplus allowed this approach to work initially. However, by the third five-year plan, there was a growing realization that some logic or reason was necessary, and the very high investment rates needed to be moderated. Steps were taken to professionalize the planning bodies, though this process was interrupted by the onset of World War II in 1939.

Through the mid to late 1930s, there was an increasing understanding that simply throwing resources at problems wasn’t sustainable — the rate of investment needed some rhyme or reason, or returns would be inefficient. Even Stalin began to discuss the negative consequences of “storming” practices. However, a deep disjuncture remained between what some would call Stalinist romanticism or revolutionary romanticism and the need for more planned expertise. This tension was never fully resolved.

Khrushchev’s Hurdle and Socialism in One Country

Jonathon Sine: There’s an interesting quote from Stalin where he says, “The planned economy is not our wish; [but] it is unavoidable or else everything will collapse.”

He goes on to say that the main task of planning is to ensure the independence of the socialist economy from capitalist encirclement. It sounds like he didn’t necessarily intend to have the sort of planned economy that ultimately developed. Could you discuss this and then lead us into how Khrushchev upended that model?

Yakov Feygin: That quote indeed speaks volumes. The practices of Soviet planning were largely improvised and closely tied to Stalin’s political priorities and the attempt to understand what “socialism in one country” meant. There’s a misunderstanding that this concept simply equates to Great Russian chauvinism or Soviet capital-I Imperialism, but it was still very much a revolutionary project. The question was how to have a revolution when the global environment wasn’t as friendly as it had been in 1917.

As Stalin consolidated power and built his framework, many choices were stark. With the assumptions about battling world capitalism and foreign markets collapsing during the Great Depression, improvisation became necessary. For instance, there were initial plans for the Soviet Union to be a major grain exporter, starving its peasantry to accumulate capital. However, it ended up relying mostly on gold exports because the grain markets collapsed.

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The quote you mentioned comes from a very interesting meeting where Stalin was addressing economists who were arguing about how to write a textbook for Soviet colleges. The main point of contention was the role of planning in the Soviet economy — whether it had abolished market relations entirely, or if the Marxian law of value still applied in some areas. Stalin’s response was pragmatic, acknowledging that the planned system was improvised rather than designed from the top down. He noted that while state industry was no longer affected by the law of value, there were still gaps, particularly in agricultural markets that weren’t fully socialized.

Moving on to Khrushchev, his era needs to be understood in its political context. Khrushchev — and Stalin’s other successors — were dealing with several challenges including,

1. A disorienting domestic situation with bottled-up social pressure that had been accumulating since the late Stalin period.

2. Expectations for change, as the population felt that it had sacrificed a lot, and already proven its loyalty through war. People felt that it was time to start seeing results from that hardship.

3. The Cold War started playing out differently than Stalin had expected, with the consolidation of American hegemony and the creation of an open trade bloc. France and Britain stayed on-side much more than Stalin expected.

These factors combined to require a new narrative for Soviet legitimacy.

The debate between Khrushchev and Georgy Malenkov in 1955 is a crucial moment in Soviet history.

Malenkov was Stalin’s official successor — he was the Premier of the USSR for a year. He appeared to be a typical Stalinist, but crucially, his wife was one of the USSR’s leading economist-engineers specializing in electrification infrastructure. Such projects have high initial capital requirements and low subsequent costs — a dynamic that forced Malenkov to think about the problem of investment allocation between consumer and industrial goods.

After Stalin’s death, Malenkov advocated for reducing the rate of investment in heavy industry. He gave speeches suggesting compromises with the United States and Europe.

These positions made him deeply unpopular — Malenkov’s argument about the contradiction between consumption and investment implies that the Soviet Union would inevitably be threatened militarily by the capitalist world. That culminates in Khrushchev’s triumph.

Khrushchev emerged as a true believer, who thought the Soviet planned system could simultaneously increase production and consumption without facing trade-offs. He believed that the system’s problems stemmed from the population’s increasing alienation and the disconnect between the grassroots and the party leadership.

Under Khrushchev’s leadership, the USSR doubled down on fixed capital investment and made management by cadres more efficient, resulting in significant growth.

Simultaneously, Khrushchev dismantled some of the central structures that had previously managed the system. This combination of factors creates an almost perfect storm in Soviet economic policy.

Jonathon Sine: Let’s focus on that point where Stalin dies and Khrushchev doubles down on investment. This gets to the crux of the argument in your book, which is the issue of distribution. The party-state continuously put resources towards heavy industry under Stalin. Production ministries funneled more and more money towards machinery and goods that could be used for war. Khrushchev effectively doubled down on this approach, though not so much in a war mobilization sense. 

What is this distributional issue, and why is it the fundamental problem of the Soviet economy?

Yakov Feygin: The distributional issue in the Soviet economy is rooted in the ideas of the economist Michał Kalecki, who explored the sources of profits under capitalism even before Keynes.

Kalecki argued that profits come from final consumption, which in turn comes from capitalist investment directed towards creating stock. This creates a cycle where consumption, primarily from wage-earning households, is paid for by capitalist wages, which come from capitalist profits that depend on wages.

In graphical terms, while savings might equal investment (S=I), investment leads to savings (I → S). That is, future investment in consumable goods leads to profits, which lead to savings in a capitalist society.

Ironically, Kalecki, a dedicated communist, found himself disillusioned when he returned to communist Poland because the government wasn’t managing the consumption-investment trade-off as he thought it should through planning.

In a socialist economy, Kalecki found a similar problem — you can invest in many things, but returns come when someone else consumes that thing in a way that generates money. If you keep investing in things that aren’t generating returns, you have to write down the capital stock.

This is essentially what started to happen by the mid-1960s in the Soviet Union. There was significant investment in goods that weren’t fulfilling consumer demand, and consumers themselves didn’t have enough budget to spend on the basket of goods they wanted. This resulted in a cash overhang and capital assets that had to be written down.

The agents in my book — party officials, academics, and para-academics — were trying to deal with this disjuncture but kept hitting the wall. The fundamental issue was the misallocation of resources between consumer goods and heavy industry, creating an economy that produced goods people didn’t want or couldn’t afford, while simultaneously underinvesting in areas that could have improved living standards and economic efficiency.

Jonathon Sine: As I read the book, I was trying to understand your discussion of distributional issues. They sound like top-down party-state dictates about where money should flow. Are these entirely separate from issues like price reform and the other topics you extensively explore in the book? You provide an intellectual history of reformers discussing different approaches. However, it seems you’re saying they’re operating within a prescribed Overton window that precludes what you consider the fundamental distributional issues. How are all these elements related?

Yakov Feygin: Some reformers do address these distributional issues. Even those discussing price reform understand it as a way to tackle resource allocation. The interesting question is how they navigate within their prescribed space, which changes over time. From the vantage point of the Kosygin reforms (1964-1969), it might have seemed there was considerable room for change. Hindsight is 20/20, but in 1965, it wasn’t clear how limited the options were.

This is fascinating because it demonstrates that even in the Soviet Union, there were legislative politics within the party-state. More importantly, it shows that Soviet leaders were aware of trade-offs and alternative paths, even within officially sanctioned discourse.

The question then becomes — why weren’t these alternatives pursued? That’s the million-dollar question of the book.

I believe it’s a highly contingent issue. Until the late 1960s or early 1970s, there was a window of possibility for more extensive reforms. The fact that they weren’t implemented is itself a political decision.

Jonathon Sine: Could you discuss some metrics used to gauge the economy’s deteriorating performance? How did people within the system assess this, and how would they have judged the success or failure of certain reforms?

Yakov Feygin: The assessment varied depending on whom you asked within the system. Khrushchev’s approach differed significantly from Stalin’s. Khrushchev believed Soviet economies could be directly compared to capitalist economies, including quality of life measures. He expected the Soviet Union to catch up with the United States in terms of living standards and individual goods usage and output.

This socioeconomic competition was seen as a way to avoid a third world war while demonstrating the superiority of the planned economy model. Khrushchev explicitly benchmarked against the United States, which hadn’t been done under Stalinism. Some who resisted comparing the two systems faced repression of their work and sometimes themselves.

As Khrushchev’s coalition began to crumble in the lead-up to his replacement in October 1964, there was a growing realization that his grand promises of achievement through pure mobilization, without relying on expertise, weren’t materializing. This realization helped create a political opening.

Additionally, the Soviet Union faced a political crisis in the mid-1960s, exemplified by the Novocherkassk massacre of striking workers. The promised prosperity wasn’t materializing. Due to a form of classical inflation not immediately reflected in price increases, more capital had to be written down. This eventually necessitated price hikes, particularly on deficit goods like meat and milk — items that were supposed to be in abundance, even surpassing capitalist economies.

This situation created a clear and widely recognized political crisis.

Jordan Schneider: I’m intrigued by this moment when Khrushchev suddenly decides to compete with the US on their own terms, forcing everyone to take an uncomfortable, critical look at the Soviet system. 

On one hand, you have economists realizing they need to learn about American methods of measuring productivity to make comparisons. A few years later, it becomes evident that the trend lines aren’t converging but potentially diverging further than during the more coherent vision of the 1940s and 1950s under Stalin’s industrialization.

Yakov, was this Khrushchev’s only move? Was it inevitable that the Soviet Union would start building its legitimacy in comparison to the US? It seems like they could have promoted socialism’s merits without relying on such a materialist definition of success.

Yakov Feygin: That’s an excellent question. To frame it more clearly, it’s not just about a materialist definition of success. It’s about how to achieve the Soviet Union’s ideological goal, which was internationalist and global, with a Soviet state that had become a normal industrialized society in many ways.

Khrushchev’s answer was to move away from Stalin’s “inevitability of war” doctrine. The post-World War II generation of Soviet leaders wanted to avoid another war if possible, as detailed in books by Odd Arne Westad, Sergey Radchenko, and Vladislav Zubok.

Instead, the strategy became demonstrating the Soviet system’s power to develop a state and attract more countries to their bloc, even if those countries weren’t necessarily Leninist. Initially, there were efforts to reach out to European social democracies and the emerging “Third World.”

The idea was that if the Soviet Union could succeed, a world socialist system would emerge that everyone would want to join, creating a crisis within the capitalist system.

This approach, they hoped, would lead to a less drastic way of building global socialism. Khrushchev’s generation were true believers but wanted to avoid war and the harsh Stalinist approach. Their middle course was to build an appealing socialist modernity as an alternative to the capitalist economy. However, they struggled to figure out how to achieve this in practice.

Surpass England, Catch up to America 超英赶美

Jordan Schneider: Let’s take a brief detour. Jon, do you want to discuss how Mao adopted this “catch up and surpass” 超英赶美 concept from Khrushchev? It became part of Mao’s legitimacy package after the dramatic failure of the Great Leap Forward.

Yakov Feygin: That’s right — when Khrushchev declared the USSR would overcome the US at some point (“догнать и перегнать Америку”), the immediate Chinese reaction was to set their target as Great Britain, which I found quite amusing.

Jonathon Sine: Yakov, you mentioned that explicitly naming the United States as a competitor was forbidden under Stalin. When you read Chinese documents today, Xi Jinping and the Communist Party leadership very rarely make explicit comparisons with the US. They often speak vaguely about “encirclement” nowadays, but rarely talk about the US directly.

Yet there’s an interesting parallel — Khrushchev took the Soviet system from war mobilization under Stalin to a “peaceful systems competition,” a phrase he used explicitly. Now, Xi Jinping explicitly uses the phrase “systems competition” to define the current situation. Even though he is vague about what exactly the other system is, everyone knows what he’s referring to. The contemporary relevance really stands out to me.

Yakov Feygin: That’s fascinating. In China up until recently, and in the Soviet Union under Stalin, they never claimed to be as developed as the West. They would acknowledge being behind because they started later. They always compared themselves to pre-1917 imperial Russia.

Even when they did compare themselves to the United States after Khrushchev, they would say, “We’re not as developed, but that’s because the US has 200 years of exploitative development behind them. We’re showing what can be done in 20-30 years.”

Paying subscribers get access to the second half of the interview. We cover:

• Surprising parallels between Khrushchev's Soviet Union and Xi Jinping's China in economic competition and party discipline

• The hidden role of migrant labor in Soviet, modern Russian, and Chinese economies

• Distributional challenges in China's economy today mirroring those of the late Soviet Union

• How China's potential "middle-income trap" compares to the Soviet experience

Read more

This summer, we teamed up with the Federation of American Scientists, and Chris Miller to hold a crowdsourced policy competition. We asked for ideas on how to deal with the problem of China potentially controlling the supply of foundational chips (also called “trailing-edge” semiconductors).

To recap from the original post:

The U.S. has implemented export controls to try to stop China from getting a technological edge in advanced cutting-edge chips. But as I explained in a recent post, export controls have no hope of stopping China from building simpler types of chips — called “legacy chips”, “foundational chips”, or “trailing-edge chips”. These legacy chips are used for a huge number of things in our economy, from cars to smartphones to fighter jets.

And China is gearing up to build these legacy chips in absolutely staggering numbers. Check out this post by Jimmy Goodrich of the University of California Institute on Global Conflict and Cooperation and this post by the Rhodium Group for details. Basically, China is applying the same approach to legacy chips that it has successfully applied to batteries and EVs — massive scale and enormous subsidies.

This basically presents at least three potential dangers to the U.S:

1. First, China could deprive non-Chinese chipmakers of huge amounts of revenue by outcompeting them in the legacy chip market, making it harder for them to sustain their leading-edge chip businesses. Already investors are pressuring U.S. companies to avoid competing with China by canceling their semiconductor fabs.

2. Second, if China controls the legacy chip market, it could cut off our supply of chips in a war.

3. Third, Chinese security services might be able to put back doors into Chinese-made chips, using them to spy or even to attack U.S. infrastructure.

In other words, there are plenty of national security reasons for keeping Chinese-made legacy chips out of our supply chain. But how can we do it? It’s a tough problem.

First of all, as things stand, we don’t even know which products contain Chinese-made chips. If a Vietnamese-made phone or a Mexican-made PC includes Chinese-made legacy chips, the U.S. currently has no way of knowing.

Second, even if we did know, it might be politically unpopular to ban those chips. A lot of U.S. companies want to get chips as cheaply as possible, especially for new AI applications. We’d need some way to make chip restrictions politically palatable.

And finally, lots of Chinese legacy chips — and the products that contain them — aren’t going to be sold in the U.S. or our allied countries. How do we make sure non-Chinese chipmakers stay competitive in markets like Vietnam, Brazil, Indonesia, etc.?

We asked contestants to give us their ideas for addressing this problem and picked four winners. They each received $500 and will be working with FAS to continue refining their proposals.

The following write up is by , whose Substack consistently delivers excellent coverage on classic ChinaTalk themes like industrial policy and technology, interspersed with a little of my commentary. Overall, I was really impressed by the quality of submissions we received and am excited to run more of these in the future!

These winners are listed in alphabetical order by first author.

Winner #1: Weaponizing EDA and using targeted industrial policy

By: Zenghao (Mike) Gao, Charles Yockey, and Felipe Chertouh

Gao et al. point out an important weapon in the U.S.’ arsenal of export controls that hasn’t been used yet: Electronic design automation software (EDA). We hear a lot about where the production of chips happens, and some about where the production of chipmaking tools happens, but not very much about where the software used to design chips comes from. In fact, almost all of it comes from America, with a little bit coming from U.S.-allied countries like Japan and Australia. And this software doesn’t just design chips in the first place; it’s also what chipmakers use to correct problems with the fabrication process as they arise.

Gao et al. suggest that EDA could be “weaponized” by mandating that it run on U.S.-based cloud servers:

In hosting all EDA in a U.S.-based cloud—for instance, a data center located in Las Vegas or another secure location—America can force China to purchase computing power needed for simulation and verification for each chip they design. This policy would mandate Chinese reliance on U.S. cloud services to run electromagnetic simulations and validate chip design. Under this proposal, China would only be able to use the latest EDA software if such software is hosted in the US, allowing American firms to a) cut off access at will, rendering their technology useless and b) gain insight into homegrown Chinese designs built on this platform. Since such software would be hosted on a U.S.-based cloud, Chinese users would not download the software which would greatly mitigate the risk of foreign hacking or intellectual property theft. While the United States cannot control chips outright considering Chinese production, it can control where they are integrated. A machine without instructions is inoperable, and the United States can make China’s semiconductors obsolete.

This idea wouldn’t stop China from making foundational chips — Chinese companies could still use American EDA software. But it might give the U.S. one more piece of leverage to hold over China in case hostilities broke out — and another way to try to slow down the Chinese chip industry in general, if that becomes necessary.

On the defensive side of things, Gao et al. also call for the U.S. to form a trade bloc with Latin American nations to ensure safe supply of rare earths and NAND memory. They also have some additional ideas, such as forcing Chinese companies to release the source code for the firmware and other software for their chips. [Jordan: Enjoyed this one in particular for its creativity and density of ideas. Some of these to me seem more feasible than others but a ton of food for thought in this doc].

Full paper here: https://www.mikegao.net/public/chips-proposal.pdf

Winner #2: Working with other countries on industrial policies and tariffs

By: Andrew Lee

Lee sees the creation of a non-China foundational chip supply chain as the central problem to be solved. He envisions a program modeled after Lend-Lease — the system by which the U.S. delivered arms to the UK in World War 2, and by which it’s currently delivering arms to Ukraine. The program would license U.S. technology cheaply to friends and allies in exchange for cooperation in creating completely China-free chip supply chains:

The United States Federal Government could negotiate with the “Big Three” EDA firms to purchase transferable licenses to their EDA software. The U.S. could then “lend-lease” licenses to major semiconductor producers in partner countries such as Singapore, Malaysia, Vietnam, the Philippines, or even Latin America. The U.S. could license this software on the condition that products produced by such companies will be made available at discounted prices to the American market, and that companies should disavow further investment from or cooperation with Chinese entities. Partner companies in the Indo-Pacific could further agree to share any further research results produced using American IP, making further advancements available to American companies in the global market.

(Side note: It occurs to me that this might dovetail well with Gao et al.’s proposal for putting EDA on a U.S.-based cloud.)

[Jordan—very ambitious indeed! I feel like this would need some dramatic catalyst for a government to be aggressive enough to be able to push this over lobbyist objections. It also feels like there’s a vaccine analogy here.]

Lee also suggests coordinating with friendly countries in order to put tariffs on Chinese foundational chips. Recall that one of the big challenges here is that we don’t currently know which products contain Chinese-made chips, so we have no idea how many we’re importing. Lee’s solutions to this problem are 1) an international database of which products contain Chinese chips, and 2) reporting requirements for importers, enforced by random audits:

How would tariffs on final goods containing Chinese chips be enforced? The policy issue of sanctioning and restricting an intermediate product is, unfortunately, not new. It is well known that Chinese precursor chemicals, often imported into Mexico, form much of the raw inputs for deadly fentanyl that is driving the United States opioid epidemic. Taking a cue from this example, we further suggest the creation of an internationally-maintained database of products manufactured using Chinese semi- conductors. As inspiration, the National Institutes of Health / NCATS maintains the Global Substance Registration System, a database that categorizes chemical substances, along with their commonly used names, regulatory classification, and relationships with other related chemicals. Such a database could be administered by the Commerce Department’s Bureau of Industry and Security, allowing the personnel who enforce the tariffs to also collect all relevant information in one place.

Companies importing products into the U.S. would be required to register the make and model of all Chinese chips used in each of their products, so that the United States and participating countries could to impose corresponding sanctions. Products imported to the U.S. would be subject to random checks involving disassembly in Commerce Department workshops, with failure to report a sanctioned semiconductor component making a company subject to additional tariffs and fines. Manual disassembly is painstaking and difficult, but regular, randomized inspections of imported products are the only way to truly verify their content.

Finally, he suggests efforts to protect U.S. critical infrastructure by 1) identifying Chinese hardware within the infrastructure, and 2) improving cyber defense capabilities.

You can read Lee’s full policy proposal here.

Winner #3: An “Open Foundational” design standard and buyers’ group

By: Alex Newkirk

Newkirk also sees Chinese disruption of the chip supply chain — along with possible backdoors and other security issues — as the main problem to be solved. He proposes two ideas. First, Newkirk would create an “Open Foundational” design standard for legacy chips, in order to ensure that China doesn’t get proprietary control over any type of computer chip. The chip companies who joined up to help create this standard would form a sort of cartel that could act to create a China-free manufacturing supply chain. Newkirk also suggests an international buyers’ group to create a strategic reserve of chips. This would serve the dual purpose of building up a chip stockpile and providing demand to encourage the adoption of the Open Foundational design standard.

He writes:

To secure supply of foundational chips, I recommend development of an “Open Foundational” design standard and buyers’ group…[T]he U.S. federal government…would establish a strategic microelectronics reserve to ensure access to critical chips. This reserve would be initially stocked through a multi-year advanced market commitment for Open Foundational devices. 

The foundational standard would be a voluntary consortium of microelectronics users in critical sectors, inspired by the Open Compute Project. It would ideally contain firms from critical sectors such as enterprise computation, automotive manufacturing, communications infrastructure, and others. The group would initially convene to identify a set of foundational devices which are necessary to their sectors…and identify design features which…could be standardized.  From these, a design standard could be developed…Steering committee firms will…be asked to commit some fraction of future designs to use Open Foundational microelectronics…[T]he buyers’ group would represent demand of sufficient scale to motivate investment, and that supply would be more robust to disruptions once mature. 

Government should adopt the standard where feasible, to build greater resilience in critical systems if nothing else. This should be accompanied by a diplomatic effort for key democratic allies to partner in adopting these design practices in their defense applications. The foundational standard should seek geographic diversity in suppliers…The foundational standard also allows firms to de-risk their suppliers as well as themselves. They can stipulate in contracts that their tier one suppliers need to adopt Foundational Standards in their designs…

Having developed the open standard through the buyers’ group, congress should authorize the purchase through the Department of Commerce a strategic microelectronics reserve (SMR). Inspired by the strategic petroleum reserve, the microelectronics reserve is intended to provide the backstop foundational hardware for key government and societal operations during a crisis…The foundational standard provides the product specification, and the advanced government commitment provides demand…This demand should be steady, with regular annual purchases at scale, ensuring producers consistent demand through the ebbs and flows of a volatile industry….The SMR could also serve as a backstop when supply fluctuations do occur, as with the strategic petroleum reserve…This would ensure government access to core computational capabilities in a disaster or conflict scenario. But as all systems are built on a foundation, the SMR should begin with Foundational Standard devices. 

It’s notable how Newkirk’s ideas support each other. The international chip design standard he would create would make it easier to build up a stockpile of reliable chips. And building up the stockpile would create the guaranteed demand that would encourage adoption of the design standard. That’s a very clever synergy. And as an added bonus, the consortium of companies that create and run the foundational chip standard would also be able to help carry out friend-shoring and de-risking, instead of leaving all the planning to the government.

You can read Newkirk’s full policy proposal here.

Winner #4: A legal plan for blocking Chinese chips

By: Ben Noon

Noon focuses on the difficult problem of identifying and restricting Chinese-made foundational chips contained within U.S. imports from other countries. He vividly lays out the dangers of allowing China to control the foundational chip industry:

The list of examples of Chinese economic coercion is long…Washington faces less blatant coercion compared to its allies…This may be because Beijing does not believe it yet maintains necessary leverage over Washington…China’s growing position in the legacy semiconductor market could change that. How would Beijing’s behavior change if sales of the Ford F-150 relied on Beijing’s willingness to sell its semiconductors?

Noon argues that export controls have little or no hope of containing the Chinese foundational chip industry. And he argues that CHIPS Act-type subsidies alone are insufficient to maintain a U.S. foothold in the market because Chinese subsidies will always be larger. Thus, he concludes, protectionism is necessary in order to keep China from dominating the global market for foundational chips.

The question, of course, is how to restrict imports of Chinese foundational chips contained in other products. Noon goes through and explains a list of various legal and administrative vehicles that the U.S. government has at its disposal to accomplish that task:

• Tariffs

• Investigation of and restrictions on imported goods linked to unfair trade practices

• Federal government purchasing restrictions

• The Office of Information and Communications Technology and

  Services (ICTS) at the Commerce Department, a recently created agency with broad authority to protect critical infrastructure from dangerous imported products

Noon believes that the most important legal justification for tariffs on Chinese chips is Section 301 of the Trade Act of 1974, which both Trump and Biden have used extensively in order to put tariffs on Chinese products.

The really tough question, of course, is enforcement. Noon recommends “a major expansion of supply chain analytical capabilities across the U.S. government,” but doesn’t say much more about that. He also suggests enlisting private companies as whistleblowers.

You can read Noon’s full policy proposal here.

All of these proposals are quite interesting, and we’ve already contacted the authors to talk about following up on their development. I was very impressed by the diversity of ideas here — different contributors targeted different aspects of the problem, which helped them come at the issue from a variety of angles. I continue to be impressed by the creativity and technical acumen of Noahpinion readers. Expect more policy contests at some point in the future!

Welcome back to part 3 of our interview with Yasheng Huang 黄亚生, the author of The Rise and Fall of the EAST: How Exams, Autocracy, Stability, and Technology Brought China Success and Why They Might Lead to Its Decline.

In this final installment, we discuss…

• The steelman case for why China needed a Xi,

• What sets Xi apart from his predecessors,

• Succession challenges and the importance of term limits in authoritarian states,

• Why engagement with China failed to produce political liberalization,

• How the US could have better leveraged economic relations with China,

• Creative approaches to human rights advocacy in China.

Co-hosting today is Ilari Mäkelä of the On Humans podcast. Here’s our first interview if you missed it, and here’s the first half of the second installment.

Succession Crises and The Death of Deng’s Legacy

Ilari Mäkelä: Let’s examine China today then. In some ways, Xi Jinping seems like a natural progression from Hu Jintao, who made China more statist, with Xi taking it even further. However, one could argue that this represents a more dramatic shift, to the extent that China today is no longer in the reform era but has entered a completely new phase. How abrupt was this change? In what sense was it new rather than just an intensification of previous trends? Where are we now?

Yasheng Huang: Looking at the three leadership generations — 1989, 2002, and 2012 — we can analyze them as such:

The 1989 generation changed the rules of the game, essentially reversing the political reforms initiated by Zhao Ziyang. 

The 2002 generation, led by Hu Jintao, changed the game but not the rules of the game. Within the existing structure, they strengthened government control and cracked down on social media, (that began under Hu Jintao, by the way, not under Xi Jinping). They also went quite far in controlling NGOs due to concerns about a potential Velvet Revolution.

Xi Jinping changed the rules of the game again, this time reversing Deng Xiaoping’s reforms. This represents a more significant change compared to the 1989 generation’s rule changes or the 2002 generation’s game changes. In modern Chinese politics, one doesn’t typically challenge Deng Xiaoping’s legacy.

Ilari Mäkelä: I agree. Could you be more specific about how Xi Jinping overturned Deng Xiaoping’s rules?

Yasheng Huang: Xi Jinping has made several significant departures from the Deng Xiaoping era. These include eliminating term limits, removing mandatory retirement, shifting away from economic growth as the Chinese Communist Party’s primary objective, and moving away from cooperation with the West in foreign policy.

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These are substantial changes. The 1989 generation altered Zhao Ziyang’s implementations of power separation between party and state, transparency reforms, and media protections.

However, they didn’t touch the core principles established by Deng Xiaoping, such as term limits and mandatory retirement. Both Jiang Zemin and Hu Jintao stepped down after their terms ended.

To challenge what I call the “third rail” of Chinese politics required something extraordinary. While the direction was the same, the departure was more abrupt and sharper. It was directionally consistent but represented a more significant shift.

Ilari Mäkelä: How positive or negative is this change? There’s an easy way to view it negatively as more autocratic. However, let me present a case for Xi’s era after 1989:

• The Shanghai model of development led to crony capitalism and massive corruption.

•  The rural-urban gap resulted in significant economic inequality.

• The purely GDP-driven model of legitimacy led to environmental degradation.

Xi came to power promising to tackle corruption and later focused on rural poverty. Branko Milanović, an inequality expert I recently interviewed, convinced me that there’s been a noticeable rise in the bottom 20% of global incomes, primarily due to China’s poor becoming richer over the past decade.

Additionally, Xi is more focused on issues like clean energy. During my time in China, I conducted a small field project on a ten-year fishing ban implemented by the government on the Yangtze River —  something unlikely to have occurred a decade earlier.

That’s my case for the need for a Xi Jinping-like figure. What’s your response?

Yasheng Huang: Milanović is correct that inequality declined under Xi Jinping, and the bottom 20% saw improved income growth relative to GDP growth. In the revised version of my 2008 book, I present statistics supporting this claim. However, the question remains — does achieving these goals necessitate eliminating term limits and mandatory age retirement? Does it require such a high degree of centralization?

It may require some revision of the economic growth objective, moving away from blind pursuit of GDP growth numbers in favor of income growth for poor and rural people. I agree with that. But consider two scenarios and choose between them:

1. Achieving these goals with higher GDP growth

2. Achieving these goals with lower GDP growth

Any rational person would choose the scenario where both higher income growth for rural Chinese and higher GDP growth for the country are accomplished. This was China in the 1980s, where each increment of GDP growth significantly improved rural income. The 1980s outperformed the subsequent three generations by a wide margin.

Xi Jinping did improve upon the previous two generations of leadership, but it’s important to note that under Jiang Zemin, income improvement substantially slowed.

Xi improved from a low base, which is commendable, but it was achieved largely through transfers from urban to rural people, not through fiscal stimulus.

This transfer approach can work for a period, but with the current challenges to GDP growth, it will become increasingly difficult to rely on pure transfers. During Zhao Ziyang’s era, extensive transfers weren’t necessary because rural income was growing rapidly on its own.

I would argue that tackling corruption and environmental issues doesn’t necessarily require political centralization. There are other ways to address these problems. The fact that they’ve been fighting corruption for eleven years suggests either that there’s too much to work on, or that their methods are ineffective.

Perhaps it’s time to rethink this approach to tackling corruption.

I would argue that transparency, government disclosure, increased media scrutiny, and more legislative oversight could be more effective in combating corruption than the current purge approach.

Ilari Mäkelä: Essentially, they’re doing the opposite of what you would recommend. Is that correct?

Yasheng Huang: In terms of methods, yes. I support the objectives of environmental improvement, government cleanliness, and improving the bottom 20% of incomes. I also agree that everything shouldn’t revolve around GDP growth. However, I disagree with their methods.

Regarding GDP growth, a cleaner approach could be adopted rather than the current investment-heavy method. This would involve allowing small-scale entrepreneurship, low-tech ventures, and more service sector activities. Unfortunately, these are not the activities encouraged by the current government.

Ilari Mäkelä: To summarize the historical development from the early reform era until today — you have the liberalization in the 1980s, followed by a period of confusion until Xi, and now a clear move towards less openness and freedom. You seem very pessimistic about China’s future trajectory in general, and the economy in particular under the current model. Could you elaborate on that perspective?

Yasheng Huang: Let me be clear, China has many positive fundamentals, including entrepreneurship, human capital, and globalization — not just in terms of factories but also in human capital. China has progressed further in this regard than countries like Japan and many others.

However, I am indeed pessimistic about China under the current policy model. This model overemphasizes the supply side and underemphasizes the demand side. It places too much focus on industrial policy, high-tech development, and technological aspects while undervaluing grassroots entrepreneurship and bottom-up growth models.

I’m also concerned about the constricted political and ideological environment, as well as the geopolitical tensions between China and the West. It’s worth noting that the two generations of leadership after 1989 globalized the Chinese economy and research and educational enterprise, which greatly benefited Chinese society and economy. Now, we’re moving away from that approach.

In my book, I discuss the curious combination of worrying about a Soviet-style collapse while prescribing a Brezhnev-style solution. This is profoundly puzzling to me. To avoid a Soviet-style collapse, China needs to move away from the Brezhnev model of stagnation, political control, and economic control.

What saved China — and by extension, the Chinese Communist Party — was entrepreneurship, private sector development, economic dynamism, and globalization. I find it perplexing that there’s now an argument for saving China from the private sector and globalization when these factors were delivering political benefits to the system.

As Deng Xiaoping famously said, “When you open the window, some flies will come in, but so will fresh air (打开窗户，新鲜空气和苍蝇就会一起进来).”

If you focus solely on the flies without considering the fresh air, you’re not striking the right balance. These are the reasons for my lack of optimism.

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Ilari Mäkelä: You make an interesting point in your book about this problem — the Chinese Communist Party genuinely believes that much of the growth has been due to their successes, thinking that with more power, they can do an even better job. But what you observe is that China’s significant growth was actually enabled by a hidden pluralism — through globalization, academic cooperation, the influence of Hong Kong and Taiwan, and various other factors. China had many more pluralistic conditions than its outwardly authoritarian appearance suggested, and these conditions are now being eroded.

Yasheng Huang: I’m constantly struck by the fact that Xi Jinping and many Western observers agree perfectly on this point. They all believe that it was the infrastructure, the power of the government to leverage data and financial resources, and the government’s organizational capabilities that delivered economic growth. They see eye to eye on this matter.

This view was pervasive among policy elites in China even before Xi Jinping, though Xi has taken it further by targeting the private sector as well. The fundamental problem with this view is that when China fully embraced it, Chinese productivity collapsed, even as GDP continued to grow rapidly for a while.

But who cares about productivity when it’s not a number you see on TV every day? We have Western analysts who just look at GDP, and anyone familiar with the Chinese economy would first question the veracity of the GDP numbers. This is not just a problem in China; it’s a problem in the West as well. Whenever I see someone being interviewed on prominent forums saying, “I know China because I have met with Chinese leaders,” I begin to worry about their perspective.

Jordan Schneider: Another problem with changing the constitution is that it introduces new succession problems.

Yasheng Huang: Indeed. Autocracies can build, at least Chinese autocracy can. However, autocracies suffer from succession issues. One inevitable problem faced by many autocracies is how to transfer power from one leader to another.

Imperial autocracies didn’t have to deal with this problem because power was passed to the son. In China, it was even more restrictive — only the oldest son was the legitimate heir. The rules of the game were very clear.

Autocracies often fail because the rules of succession are unclear. Gordon Tullock famously noted a difference between some autocracies and those he observed in Latin America (Brazil, Argentina) in the 1970s. There, the autocracies didn’t translate into bigger political problems because they had term limits.

China successfully transferred power three times in a row under term limits — to Jiang Zemin, then to Hu Jintao, and then to Xi Jinping. Before China instituted term limits, it was chaotic, as seen with Lin Biao 林彪, Liu Shaoqi 刘少奇, and Hua Guofeng 华国锋.

In my book, I call this “Tullock’s Curse.” China was suffering from this curse before term limits. We thought the problem was resolved when China instituted term limits. The worry now is that Tullock’s Curse may return because China abolished term limits in 2018 through constitutional revision.

We don’t know what will happen in the future, but if I were to bet on one sure source of instability and chaos, it would be this. Economically speaking, they are also adding complexity to the future. The political instability and uncertainty will likely stem from this change, though the exact timing is unpredictable as it’s largely driven by the health of individual leaders.

Jordan Schneider: People often overlook that during the post-Mao era and Deng Xiaoping’s rise to power, China initiated its only war. Joseph Torigian argues in his book that Deng’s decision to start the war with Vietnam, despite opposition from the Politburo and PLA, was a way for him to solidify his control over the system. This demonstrated that he was in charge and could command others to follow his orders.

While Deng had his reasons, one of them was partially to establish himself as the top leader in the new era. I’m curious about your reflections on the invasion of Vietnam and to what extent messy transitions lead to international adventurism.

Yasheng Huang: That could be correct. However, the current discussion about Xi is quite different. Deng was a contender at that time, not yet the supreme leader. Now, the speculation is about whether Xi will attack Taiwan.

Jordan Schneider: Exactly. The scenario I find more concerning is not Xi waking up one day and deciding to do something, but rather enough chaos in the immediate aftermath of Xi that there’s a domestic political reason to become more aggressive than in the past.

Yasheng Huang: I see. That’s interesting — a contending successor considering such a move.

Ilari Mäkelä: Or we might get material for an entertaining film like “The Death of Stalin,” but called “The Death of Xi."

Jordan Schneider: Let’s discuss the challenges of succession when you can’t rely on the firstborn and you’ve removed legitimacy. What new complications arise even if the leader tries to choose a successor?

Yasheng Huang: There are numerous complications. One is the lack of trust. In that type of system, with no clear rules, as soon as you designate someone, you also empower them. The reason why there’s no clear succession plan is that leaders always prioritize control and power. Essentially, when making a succession decision, you’re also deciding to weaken your own power. You’ll never feel entirely comfortable with that decision.

The outcome depends on the individuals involved, but there are structural tensions built into the system. From the potential successor’s perspective, once nominated, what do you do? It’s never a comfortable position because the leader doesn’t fully trust you and will watch your every move. On the other hand, if you don’t act, that may be used against you.

Two likely scenarios often occur, and they’re correlated. First, you make multiple mistakes. Because of these mistakes, you delay the decision until the last moment, as Mao did. Mao appointed Hua Guofeng almost on his deathbed. At that point, your mental and physical capacities are diminished, increasing the probability of making the wrong decision.

Mao made the wrong choice because he thought Hua would continue his policies, but he didn’t anticipate that Hua would remove the Gang of Four. It turned out that Hua was a Maoist, but he disliked the Gang of Four. By removing them, Hua inadvertently empowered Deng Xiaoping.

These theoretical dynamics play out and almost guarantee an uncertain, chaotic process. We can’t predict the next specific scenario due to the many unknown individual characters involved. However, we can be certain about the lack of stability and certainty.

Chinese Nationalism and Rethinking Terms for Engagement

Jordan Schneider: Let’s conclude with U.S.-China relations. You point to an almost original sin of U.S.-China engagement from post-Tiananmen through the mid-2010s, where the engagement strategy wasn’t really a strategy but more of a tautology. To have an engagement strategy, you also need a disengagement strategy, which the American political system never really embraced in the 1990s, 2000s, and early 2010s. Could you elaborate on what could have been?

Yasheng Huang: The engagement strategy was originally justified on political grounds rather than just economic ones. If you read the speeches by Bush and Clinton, who laid out this strategy, they justified it in political terms. It was also in the aftermath of the East Asian Tigers transforming into democracies. They imagined a similar trajectory for China 20 years in the future.

Once the strategy was in place, focusing solely on the U.S. side, they let it run on its own. It became all about economics, even though the original justification was political. The implementation focused on financial access to the Chinese market, investments, and companies like GM. It was all about economic and business interests. They never really leveraged the U.S. economic presence in China to accomplish the original political justifications they laid out.

A smarter political strategy would have been to deepen information industry engagement with China rather than simply focusing on products and finance. When examining the history of U.S. interactions with China regarding market access, it was all about companies like GM, GE, Goldman Sachs, or Morgan Stanley. When Google was leaving China or the New York Times was banned, the U.S. didn’t say much. The U.S. didn’t try to negotiate on behalf of Facebook or other social media companies to maintain their presence in China.

Some might argue that would have been worse, but in China’s closed environment, having the diversity of Google and Facebook would have been a plus in terms of political and ideological space compared to just having Baidu and Tencent. The U.S. never really advocated on behalf of the information industry. They advocated for Wall Street and big manufacturing companies through Treasury Secretaries and Commerce Secretaries.

This was an unthinking strategy. They never linked economic activities with potential political spillovers. I would argue that the information industry would have provided more political spillovers than finance and big manufacturers.

Another critique is that it may be inherent in the nature of the process. It’s difficult to disengage, it’s easier to engage more. Sometimes democracies must recognize that there are decisions they don’t control. Once the cat is out of the bag, it’s out. This is an asymmetrical game between China and the U.S.

China can choose to engage and disengage, but we cannot really disengage once engaged. Given that’s the case, we need to think about better ways to engage.

Jordan Schneider: You make an interesting argument that America was either shooting for the moon rhetorically, talking about how China needed to be an open liberal democracy, or just saying it would happen in time. Instead of focusing on making China into a Jeffersonian democracy, they could have aimed for something like Taiwan in the 1970s or Korea in the 1980s, which, while not entirely liberalized, would have been significant progress.

You also make interesting arguments about reciprocation in academia. The analogy of MIT only doing exchanges with Saudi universities on the condition that female Saudis are equally eligible demonstrates the type of things the U.S. could have done.

Deng understood deeply that he needed Western investment, education systems, and management practices to upgrade China’s ecosystem. Perhaps if the cards had been played differently in the early 1990s, we wouldn’t have reached the situation where, by the mid-2000s, Chinese leaders wouldn’t just shrug their shoulders at Western concerns.

Yasheng Huang: It’s puzzling. They aimed for the moon and then settled for nothing. Couldn’t there have been something in between? The U.S. administration also handled this poorly. Because the original justification was political, they felt the need to show concern for human rights. They would meet with the Dalai Lama and some Chinese dissidents. These symbolic measures alienated many Chinese.

Instead, they could have emphasized smaller steps. For example, convening conferences on the rule of law and commercial rules of the game. They could have insisted on reciprocity — “You have Confucius Institutes at our universities; we should have our own institutes at your universities, operating with the same freedoms as Confucius Institutes in America.”

They could have pushed for equal treatment of American newspapers in China, just as People’s Daily is available in America. They could have insisted on more balanced exchanges of scholars and students. We didn’t do any of that.

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Ilari Mäkelä: When it comes to issues like Xinjiang, the U.S. has done more than just meet with high-profile Uyghurs. They’ve tried various approaches, including targeted sanctions. Do you think the U.S. could do better on issues like Xinjiang? Or is there fundamentally only so much you can do from the other side of the world on such a massive issue?

Yasheng Huang: We’re returning to the meta-questions about engagement and disengagement. The Xinjiang issue now involves punishment and disengagement. My earlier point was about whether there was a way to make economic engagement produce more intellectual and ideological space compared to how we actually conducted ourselves. Xinjiang represents China moving further down a politically restrictive path, and China today is even more politically controlled than before. Now there’s a legitimate question: can we still engage with a country that has gone as far down this political path as China has? It’s a tougher issue now than before, and I don’t have a clear view on whether we should still engage or stop engagement altogether.

Jordan Schneider: US presidents meet with the Dalai Lama and fight for factories and financial access rather than for the rights of the New York Times in China, and the reason is American domestic politics. Tibet was a big issue in American politics in the early and mid-1990s, and money matters in Washington. The strategy you’re laying out, which bets on creating a Chinese intelligentsia that would yield dividends 10, 20, 30 years down the road, would have required a pretty enlightened viewpoint.

One of the concerning things about the future is the possibility of losing an entire generation of liberal or open-minded thinkers in China. It’s striking that figures like Zhang Yiming 张一鸣 and Jack Ma were pretty open to the West and had spent time here. You can find old WeChat posts from CEOs of the new generation of tech companies talking about wanting a more liberal order. The worry is that when you lean too far away, you lose any of that influence. I’m curious about your reflections on that or the fact that the vast majority of critiques in China come from the left rather than the right, arguing that the party isn’t doing enough for poor people.

Yasheng Huang: It’s a bit like the U.S. in the sense that right-wingers can say all sorts of things without facing consequences. In China, the rhetorical primacy lies with the nationalists. I consider myself a leftist, so I won’t dignify those people with that label. I believe many of them are more similar to right-wing nationalists in the West than to ideological leftist-leaning people in the West.

Leftists actually care about people — unemployment, inequality, the gains of the people. I don’t really see that in the rhetoric of many of these “little pinkies” (young Chinese nationalists). They care about the nation, nationhood, historical glory. These are classic right-wing nationalistic rhetoric focusing on abstract power. They care about bragging power, which fundamentally aligns with the ruling ideology, which I classify more on the right-wing nationalistic side than on the leftist side.

It’s really just this pursuit of power, the pursuit of abstraction, the pursuit of nationhood. For example, unifying Taiwan —  what does that give Chinese people in terms of improving their lives? I would argue very little. But somehow, unification of the country under the same political system is seen as enormously glorious.

That view is really a right-wing, nationalistic view. My temperament and way of thinking are fundamentally different from that. I care more about tangible things. Maybe I’m small-minded, but I don’t think about the nation in those abstract terms.

Jordan Schneider: One of your interesting arguments is that Washington should focus less on ethnic minorities in China and more on the persecuted CCP cadres and what they could gain from relative liberalization. Can you elaborate on that case?

Yasheng Huang: Many CCP elites have actually suffered terribly in the end. Look at Liu Shaoqi, or the four million people purged under Xi Jinping on corruption charges.

It’s interesting that quite a few of these people could trash the West and the United States all the time, but during moments of personal crisis, they actually turn to the West. The police chief of Chongqing, when being chased by Bo Xilai, defected to the U.S. consulate in Chengdu. He didn’t go to the Iranian, Russian, or North Korean embassies. He came to the U.S.

Elites park their assets in the United States and send their children to U.S. universities and high schools.

I think the West should craft an argument that appeals to CCP elites, rather than crafting an argument designed to appeal only to Tibetans and Uyghurs.

The simple fact is that in China, the Cultural Revolution didn’t single out Tibetans or Uyghurs.

I’m of Han ethnicity, and my parents suffered as much as Tibetans or Uyghurs did. So why do we insist on this ethnic line, which will antagonize 95% of Han Chinese, rather than relying on arguments that Han Chinese can also relate to?

We should think of an argument that plays more in that direction. I’m not sure exactly what that argument would be — it’s above my pay grade, as I’ve never been asked to create a policy brief for the Secretary of State. But in terms of general philosophy, we should craft an argument that appeals to more people than just ethnic minorities.

Jordan Schneider: I love this. You have a few great examples, like Liu Shaoqi waving a copy of the constitution and protesting that he had rights during a struggle session. Or Gu Kailai 谷开来, Bo Xilai’s wife — who ordered a hit and then ended up getting a commuted death sentence — writing in the late 1990s that the American judicial system is so slow.

It’s always, as you say, that democracy and the rule of law are like insurance policies. When you don’t know whether you’re going to have an accident, the smart thing to do is take out insurance.

Yasheng Huang: Why not make that argument to your Chinese counterparts? The Jesus analogy you mentioned is apt — it’s like becoming Catholic on your deathbed.

Jordan Schneider: You spent the past year in Washington. What are your thoughts and reflections? What surprised you most about the way the city views China?

Yasheng Huang: Living here, I’ve come to appreciate the deep and increasing complexity of geopolitical challenges and tensions more than I would just working in academia. These are complex issues. While I can be critical in my book, I do want to acknowledge that there are people in this city who want to do good. We do hear about sometimes over-the-top rhetoric against China, but there are also people who want to strike the right balance. They need ideas, advice, and inspiration.

I believe there’s room for some sort of reset and rethinking about China, hopefully in a more imaginative way. I don’t have high hopes, regardless of who wins the November election. If Trump wins, then forget about it. But on the Democratic side, I do hear more views acknowledging that while China poses geopolitical challenges to the U.S., there are areas where we have to collaborate with China. That’s just reality. Striking the right balance is an art rather than a science, but it would be beneficial if the Washington political establishment could be more open-ended in their approach.

Jordan Schneider: It’s interesting that you mention Trump. In your book, you note that Trump was the first president to introduce the idea of reciprocity and conditional engagement. While he might not have set the conditions for academic exchanges or fought for the New York Times, there is something to be said for him breaking the paradigm that wasn’t really going anywhere.

Yasheng Huang: I agree with that. We could work on that approach and make it more productive, not in the way he did it. He changed the rules of the game, and that’s the framework we have to accept now. But we can play the game better than he did.

Ilari Mäkelä: In my show on humans, I always finish by asking my guests: How has all the research that you’ve done and all the work that you’ve done shaped your outlook on humanity?

Yasheng Huang: I’ve come to appreciate surprises, contingencies, and the lack of predictability in history and in the world more than I did before. In a narrow academic environment, we always work on universal regularities and determinism. But history has taught me that there are consequential turning points. At the time, we didn’t think about them that way, but they could turn out to be significant. Now I have the mental habit of trying to think about issues in those terms and asking myself if a particular event is likely to be one of those consequential moments in history. The answers almost don’t matter, but I think it’s good to pose that question all the time.

Regarding humanity, I believe we are more complex than economists assume, and we sometimes behave in ways that are not terribly rational. This emphasizes the importance of the systems we create. The way I think about systems is that they place boundary conditions on either rationality or irrationality. How do we design a system that maximizes rational thinking and action while also alleviating the downsides? That’s a question that goes beyond the simple dichotomy of autocracy versus democracy. You need to think about how to balance competing forces — rationality vs irrationality, and scale vs scope. This is something I wasn’t thinking about before, and this research has taught me that it’s probably the right way to approach understanding the world and ourselves.

Yasheng Huang’s song choice:

The 1882 Chinese Exclusion Act prohibited nearly all people of Chinese descent from moving to the US and made ethnically Chinese immigrants already in the US ineligible for naturalization. Chinese immigration to the US remained highly restricted until 1965, when a new federal immigration law phased out national-origin quotas. And the ambiguous status of children born to Chinese immigrants during this time is part of the story of why the US today has birthright citizenship (see the 1898 Supreme Court case, United States v. Wong Kim Ark).

The economic impact of the Chinese Exclusion Act, however, is less well understood. (Notably, despite the protests of local business owners at the time, the congressmen from western states — Arizona, California, Idaho, Montana, Nevada, Oregon, Washington, and Wyoming — unanimously voted in favor of the Chinese Exclusion Act.)

An interesting new NBER working paper attempts to quantify the economic damage to the American west, using data from states where at least 1% of the total population in 1880 was Chinese.

Let’s break down the findings of this working paper, starting with three statistics:

• Chinese exclusion reduced the white male labor supply in Western states by 28% (compared to Eastern areas);

• The act reduced the total manufacturing output of these states by 62%;

• The act reduced the total number of manufacturing establishments in these states by 54-69%.

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Wait, a loss of Chinese workers reduced the number of white male laborers in these states? How did that happen?

The first statistic indicates that Chinese workers were creating a substantial multiplier effect in the economy out west. To understand why, we first need to understand the kind of jobs these Chinese immigrants were doing.

You probably already know that Chinese workers were instrumental in the construction of the transcontinental railroad — but Congress conveniently waited until the railway line was completed before deciding to gut the rights of Chinese immigrants.

What jobs, then, were those Chinese workers doing in 1880? The authors explain:

Chinese [railroad] workers usually worked on short-term contracts. After the completion of work, they were left by their employers in what were often sparsely populated areas.

Chinese workers often found new occupations in these places. In places where they had earlier logged to provide wood for railways and mines, they later logged to provide wood for the construction of new towns. Similarly, many who had worked as cooks or launders for the Chinese work gangs would later provide similar services for their new communities and local economies (Shih, 2022).

By 1880, Chinese immigrants worked in many sectors. For example, the manufacturing of shoes, hats and cigars in the Western United States was dominated by the Chinese during this period (Chang 2003, p. 60).

With this context, the economic multiplier effect of Chinese labor starts to become clear — after being abandoned somewhere along the railroad, Chinese workers built new infrastructure and provided services in remote western areas. After the Chinese Exclusion Act, the loss of Chinese labor made it hard for local businesses to find staff. That shock impacted a wide range of industries all at once:

The industries with the highest share of Chinese workers were personal services (e.g., private households, hotels and lodging places, or laundering and cleaning services) (50%), entertainment and recreational services (e.g., theaters) (22%), mining (25%), transportation (e.g., railroads) (8%) and manufacturing (6%).

So, the argument here is that the rapid loss of Chinese workers made western states worse places to live, thus discouraging prospective white migrants from moving West.

Even if there were more job openings available in theory, the authors argue, there was no way to disseminate information about these jobs at the scale and speed necessary to completely replace Chinese workers with white workers. Telegraphs and newspaper ads could only go so far.

It’s no wonder that 54-69% of manufacturing establishments opted to close up shop instead of waiting around for the New Englanders. The quote above suggests that those poor westerners couldn’t even buy cigars or a new hat to cope with their woes.

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To be clear, some people did move west, and the region still grew rapidly. “28% reduction in the white labor supply” expresses 28% less growth compared to regions that didn’t previously rely on Chinese labor. Still, the authors estimate that the negative impacts of the Chinese Exclusion Act persisted for nearly 60 years, dampening economic growth in the American West until at least 1940.

What would Arizona be like today if Congress hadn’t passed the Chinese Exclusion Act? We can only imagine — but I bet TSMC managers would be less disgruntled about opening a fab in Phoenix.

Building a Silicon Shield

This week, we have a special podcast for our Mandarin-speaking audience.

Lin Hung-wen 林宏文 is perhaps Taiwan’s most seasoned tech journalist, with decades of experience covering semiconductors, biotechnology, and Taiwanese industrial policy.

His book, The Radiance of the Chip Island: TSMC, Semiconductors, the Chip War, and My 30 Years of Journalism, explores the geopolitics of semiconductors through a uniquely Taiwanese perspective. An English translation of Lin’s book will be published in early 2025, at which point we will release an English translation of this interview.

If you speak Mandarin, however, you can enjoy our interview with Lin today, hosted by Arrian Ebrahimi of the Chip Capitols substack, and cohosted by ChinaTalk Editors Nicholas Welch and Lily Ottinger.

林宏文是《晶片島上的光芒》一書的作者,這本書深入探討了台積電的歷史、管理方法和國際角色。作為台灣最資深的半導體記者之一、林宏文以其三十多年的行業經驗,為讀者呈現了一個全面而生動的台灣半導體產業發展故事。

訪談中我們討論了以下幾個關鍵話題:

• 台積電的創立背景及其在全球半導體產業中的獨特定位

• 台灣政府在推動半導體產業發展中的角色、特別是工研院和科學園區的貢獻

• 台積電的管理模式、包括研發與製造部門的平衡以及人才培養策略

• 台灣半導體產業的國際競爭力、尤其是與三星等競爭對手的比較

• 台積電在全球地緣政治中的角色、以及“矽盾”這一概念的由來和影響

• AI時代對半導體產業的影響、特別是對記憶體和邏輯晶片整合的需求

• 台灣與美國在看待國際關係上的差異、以及這種差異對台灣國際戰略的影響

Lin’s song of choice:

Xi’s Fiscal Bazooka — Weibo Doomscroll

Moly at our partner Substack has translated some musings on the future of the Chinese economy.

On good vibes before the crash hit…:

Anyone else feel like the economy’s revitalized overnight?

1. The stock market is all red. Everything is rising. The bull market is back. [Chinese stocks are red when rising, green when falling, because red is lucky.]

2. The real estate market is warming back up too. Good news is endlessly rolling in and the number of sales is growing fast.

3. There are crowd everywhere during Independence Week, tourism industry is looking good. People don’t blink an eye when they spend money.

4. Lots of people going out to dinner, restaurants are full to exploding. People don’t hesitate to eat what they want and drink what they want.

I really feel like the economy’s taking an up turn, and it’s only gonna get better from here. Do you guys think so?

Comments say:

• How many days has it been, and you’ve already forgotten retirement age being delayed by three years… 😂😂😂

Another post on the stock market:

If you invested 200K into Chongqing Steel on the 18th of September, you’ve made 52K by now.

If you invested 200K into Zhengzhou Bank on the 18th of September, you’ve made 61K by now.

If you invested 200K into Tianfeng Securities on the 18th of September, you’ve made 104.5K by now.

If you invested 200K into Gujing Wine on the 18th of September, you’ve made 63.2K by now.

If you invested 200K in to Yantian Harbour on the 18th of September, you’ve made 41.5K by now.

If you invested 200K into China Mobile on the 18th of September, you’ve made 20K by now.

If you invested 200K into China Energy Engineering on the 18th of September, you’ve made 43.3K by now.

If you invested 200K into Jishi Media on the 18th of September, you’ve made 69K by now.

If you invested 200K into Vanke on the 18th of September, you’ve made 62.5K by now.

Who’s saying the stock market has no investment value? From the 18th of September to now, there’s plenty of stocks that have risen 20%! Never say that stocks have no investment value again, or other people will make fun of you! Right now, the index is only at 3300 points or so. It’s not too risky yet! There’s still time to buy in!

Comments say:

• We judge heroes on success and failure, but everyone is a Zhuge 諸葛亮 after the fact.

• It’s been falling for years, literally. Most investors are completely trapped 被套. Some have laid flat. Some can’t keep going and have to cut flesh to survive. Now it’s only been rising back up for a couple of days. It’s a little early to say there’s a lot of investment value in the stock market right now, isn’t it?

Then a few days later…

Three main indexes for the stock market fall significantly. The market is in its first round of adjustments? #Will millions of new investors still enter? On the 9th of October, the three big indexes for the stock market both fell significantly at market open. The Shanghai index fell by 1.79%, Shenzhen index fell by 2.92%, and the ChiNext index fell by 4.84%. In Shanghei, Shenzhen, and Beijing, nearly 5000 stocks are falling.

Comments say,

• Have confidence, people. It’s normal for the stock market to rise and fall. Just control your positions.

• Strategic callback.

On another note…

Ding Ding’s grandma got a scam call lately. It was a man, and he opened up by asking her, “Grandma, guess who I am.”

And grandma (who’s hard of hearing) asked, “Are you Ding Ding? What happened to your voice? Why is it so thick?”

The scammer was like, “Yeah, I’m Ding Ding. I got a cold and I’m still recovering.”

And then the situation got kind of ridiculous. The scammer started crying about how he got caught sleeping with a prostitute and asked for 50K from Ding Ding’s grandma.

Grandma had a very unique set of logic for an old lady. She not only believed every word, she even asked, “How did you sleep with a prostitute when you’re a girl too??”

I’m guessing the scammer was stunned too. Who would think Ding Ding [a fairly masculine name) was a girl? He just had to keep making shit up and said that he was with a big group. “Please don’t tell my dad. Just give me 50K, in cash. I’ll send my friend to collect the money.”

Grandma continued to ask how multiple people could do it together, and even advised, “Don’t let your husband find out about this! If he found out, your marriage would be doomed!”

And the scammer just had to keep emphasising, “Don’t tell my parents, okay?”

And grandma agreed.

A couple minutes later, Ding Ding got a call from her mom, asking, “You got caught sleeping with a prostitute???”

Ding Ding: “???????”

Ding Ding’s mom: “Your grandma said you got caught sleeping with a prostitute and you need 50K!”

Ding Ding called her grandma and told her, “You got scammed. How could you believe such an obvious lie? How would I possibly get caught sleeping with a prostitute?”

And Ding Ding’s grandma went, “Oh, that’s great you weren’t caught! I figured! It’s one thing to sleep with a prostitute, it’s another thing to get caught doing it!”

Comments say,

• Hahahahaha, what a progressive grandma!

• Question 2, if the lie went so well, how come the scammer didn’t make any money in the end?

• Question 1, just what kind of person does Ding Ding’s grandma think she is?