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Silicon Oasis: How Abu Dhabi Plays Both Sides of US-China

14 November 2025 at 20:06

Anonymous contributor “Masa Rick” returns to ChinaTalk. Last year, Masa Rick discussed China’s growing interest in the Middle East. Today’s report assesses how the UAE in particular has been responding China’s advances toward the region.

The United Arab Emirates has emerged as a formidable player in artificial intelligence, leveraging its immense financial resources, influence over the Global South, and a deliberate balance between the United States and China.

So when Emarati tech-investment firm MGX joined the likes of OpenAI, SoftBank, and Oracle in pledging $7 billion to Stargate, the move was perceived as the UAE pivoting away from Chinese partnerships and toward the United States. Has the swing vote officially been cast?

The reality is more complex. This report examines China’s strategic interests in the UAE, the UAE’s need for Chinese expertise, and whether Abu Dhabi is genuinely decoupling from Beijing or simply playing both sides to maximize its AI dominance. The evidence shows that the UAE is still probably playing both sides: leaning toward the US for access to chips, while hedging their bets with Chinese brains.

Current landscape: why is the UAE working with China?

The stereotype in China toward the Middle East goes something like this: “the deep-pocketed, oil-rich gulf countries will invest in anything that helps them diversify their economies away from oil.” But that stereotype obscures more than it reveals. The UAE, in particular, is not simply throwing money at Chinese firms. Rather, it demands the best technology, regulatory clarity, and alignment with its national priorities to boost its domestic growth (indigenization). Chinese PE/VC executives who go to Abu Dhabi to raise capital often lament the Western preference that Middle Eastern elites seem to have: after all, most Emirati elites were educated in the UK or other Western countries.

The UAE also prefers sustainability over quick results. As Hazem Ben-Gacem, former co-CEO of Investcorp (a global-investment firm backed by the Abu Dhabi sovereign fund Mubadala), put it, Emirati investment patterns can be summed up in three concepts: “patience,” “strategically distributed,” and “long term.” That approach hardly aligns with the interests of Chinese investors, who have little interest in ending up “trapped” in the UAE.

Caixin: “Cross-regional investment of private equity in the Middle East and Asia”; red = “Middle East deals involving Asian investors”; black = “Asian deals involving Middle Eastern investors”; 100亿美元 = US$10 billion

Even so, the UAE’s pickiness does not imply that it will stop engaging with China in developing its AI capacity. The UAE’s sovereign wealth funds, for example, are still prime targets for Chinese firms seeking capital — especially as China’s AI sector faces mounting financial pressures due to US sanctions and chip export controls.

In February 2024, Emirati AI firm G42 was prompted by the US government to divest from China — but that $105 billion investment was simply transferred to another Emirati investment vehicle called Lunate, an arm of the Tahnoun bin Zayed Al Nahyan’s business empire. Given Lunate’s significant investments in Chinese firms, a CSIS team led by Greg Allen argued in a January report that this spinoff represents more of a reorganization than true divestment. So far, their argument has aged well: in the past few weeks, Lunate’s holding in Alibaba has increased to 30.48%.

The UAE government has also continued its engagement with China in the telecom sector — which doesn’t exactly scream divestment from China, either. According to the CSIS report,

Huawei and UAE’s state-owned telecommunications company e& launched a 5G cloud edge computing platform called 5G Edge Box. The announcement came just months after e& launched a similar 5G edge cloud computing platform with Microsoft.

The UAE and other nondemocratic gulf states are also prime targets for Chinese cooperation because of their shared disregard for environmental regulations and human rights (exemplified by recent China-UAE joint military exercises in Xinjiang of all places). Rather than navigating Western restrictions, China and the UAE can remain focused on “pragmatic cooperation” — as well as extending non-Western tech capacity (like building data centers) and norms (like setting data-security standards) to the Global South.

The UAE, in other words, is no bystander in the global AI race.

Is the next DeepSeek going to be Emirati?

Investment is only half the picture. China and the UAE show no signs of slowing down their academic and research cooperation — as evidenced by Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), the only AI institution in the world where Chinese researchers dominate the academic roster.

The jury is still out on whether MBZUAI’s AI investments will ultimately boost the UAE’s tech capabilities. But in light of DeepSeek’s success with a small team of engineers from a very short list of Chinese universities, it’s not farfetched to imagine a major leap in AI innovation coming out of MBZUAI in the near future.

Since its founding in 2019, MBZUAI has been massively alluring to top-notch Chinese scholars for several reasons:

  • Chinese researchers, especially in STEM, face growing US scrutiny over espionage and national-security concerns. MBZUAI lets US-trained Chinese researchers work without these constraints.

  • MBZUAI has resources. A Chinese source claims MBZUAI “is equipped with top-tier GPU facilities, including over 800 NVIDIA GPUs, 400 A100 GPUs, and 400 V100 GPUs.”

  • And MBZUAI has Eric Xing, the university’s president since 2021 and a leading voice in ML research. With someone of his stature at the helm, his position not only attracts significant talent from top-tier institutions, but also legitimizes UAE’s intentions. For example, Xing was recently spotted in Paris, meeting French officials and forging connections with French institutions to launch their AI initiatives in Europe.

MBZUAI has assembled a star roster of Chinese researchers, some of whom were Professor Xing’s advisees and others well-known within their respective fields. Of the 77 current faculty members on their directory, 25 are from mainland China, and three more are from Taiwan — including a Taiwanese-German “celebrity” scholar. The inclusion of Taiwanese professors seems to be highly intentional, too. Tei-Wei Kuo 郭大維, one of the Taiwanese professors, recently resigned from the board of Foxconn; now he can bring his insights on semiconductor supply chain management to Abu Dhabi. (A full list of all current Chinese and Taiwanese faculty at MBZUAI is produced at the end of this article.)

The composition of MBZUAI’s board of trustees also provides insights into UAE’s intentions on AI innovations: it’s a top-down initiative with immense financial resources and unlimited partnership possibilities (as seen by, for instance, Lisa Su’s entry and Li-Kai Fu’s exit).

Khaldoon Khalifa Al Mubarak (chair)

  • Corporate Positions:

    • Managing Director and Group Chief Executive Officer, Mubadala Investment Company (sovereign fund)

  • Board Positions:

    • Vice Chairman, MGX

    • G42 (Board Director)

    • Abu Dhabi Commercial Bank 

    • Emirates Global Aluminium

    • Abu Dhabi National Oil Company (ADNOC)

    • Emirates Nuclear Energy Corporation

    • New York University Board of Trustees (instrumental in establishing NYU Abu Dhabi Campus as well)

  • Governmental:

    • Chairman of the Executive Affairs Authority ( Serving as an Advisor of MbZ, President of UAE)

    • Presidential Special Envoy to China

Jassem Mohamed Bu Ataba Al-Zaabi

  • Board Positions:

    • Vice Chairman, e&

    • Chairman, Modon Holding PJSC

    • Vice Chairman, Abu Dhabi Holding Company (ADQ) (sovereign wealth fund) 

    • Board member, Abu Dhabi Investment Authority (ADIA) (sovereign wealth fund)

    • Board member, Abu Dhabi National Oil Company (ADNOC)

    • Board member, First Abu Dhabi Bank (FAB)

  • Governmental:

    • Secretary General, Artificial Intelligence & Advanced Technology Council

    • Board member, Tawazun Economic Council (the defense and security acquisitions authority for the UAE Armed Forces and Abu Dhabi Police)

    • Chairman of the Department of Finance

    • Chairman, Abu Dhabi Pension Fund

    • Vice Chairman, UAE Central Bank

Saif Saeed Ghobash 

  • Board Positions:

    • Board Member, Mubadala Investment Company (sovereign fund)

  • Governmental:

    • Secretary General, the Abu Dhabi Executive Council

    • Under-Secretary, the Department of Culture and Tourism - Abu Dhabi

Rima Al Mokarrab Al Muhairi (aka the designated quasi-NGO/think tank person)

  • NGO: 

    • President, Ideas Abu Dhabi (partnership with a US-based NGO Aspen Institute)

  • Governmental:

    • Executive Director, the Executive Affairs Authority of Abu Dhabi (advisor to the President of UAE)

  • Board Positions:

    • Chair, Tamkeen LLC

    • Board of Trustees, NYU

    • Board Member, the Emirates Centre for Strategic Studies and Research (think a think tank)

    • Vice Chair, Zayed University

Professor Daniela Rus (aka “the academic”)

  • Director, the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT

Dr. Lisa Su (aka “The Semiconductor Giant”) 

  • Corporate Positions:

    • CEO of Advanced Micro Devices (AMD)

Peng Xiao

  • Corporate Positions:

    • CEO, G42

  • Board Positions:

    • Board Member, MGX

Martin Edelman (aka “the lawyer”)

  • Corporate Positions:

    • Senior of Counsel, Paul Hastings

    • Partner, Fisher Brothers

    • Advisor, Mubadala Investment Company

  • Board Positions:

    • Board Member, MGX

    • Board Member, Lionheart Strategic Management

Professor Eric Xing (aka “the Academic” + face of the university)

  • Corporate Positions:

    • CEO and Founder, Petuum Inc. 

What about MBZUAI’s students?

MBZUAI offers students free tuition and covers their living stipend. So who’s coming?

So far, it seems the only ones to jump on the bandwagon are US-educated Chinese students: the university’s current student body is about 30% mainland Chinese, according to an admissions officer based in China (private conversation with me). MBZUAI advertises to prospective students funding opportunities for ambitious research projects as well as work opportunities post-graduation: “80% of graduates decided to stay in the UAE, working for companies like ADNOC (UAE national oil company), G42 AIQ (subsidiary of G42) and TII (AI research institute).”

MBZUAI aims to be Abu Dhabi’s Stanford. Before you send in your application, however, it’s probably worth contemplating the following:

What next?

Stay on the lookout for MGX’s next moves on Stargate: Sam Altman is making the rounds to drum up more funding for the $500 billion project, stamping out any skepticism from Elon Musk on the way. And keep an eye out for the conferences that will take place in the AI and technology UAE from October to December — who will be attending and, more importantly, who will be sponsoring.

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Current Mainland Chinese Scholars on MBZUAI Faculty

Eric Xing

  • Undergrad: Tsinghua University

  • PhD: University of California, Berkeley; Rutgers University

  • Department: Machine Learning

  • Notes: President

Anqing Duan

  • Undergrad: Harbin Institute of Technology

  • PhD: Italian Institute of Technology and University of Genova, Italy

  • Department: Robotics

Dezhen Song

  • Undergrad: Zhejiang University

  • PhD: University of California, Berkeley

  • Department: Robotics

Gus Xia

  • Undergrad: Peking University

  • PhD: Carnegie Mellon University

  • Department: Machine Learning

Jin Tian

  • Undergrad: Tsinghua University

  • PhD: University of California, Los Angeles

  • Department: Machine Learning

Ke Wu

  • Undergrad: Chongqing University

  • PhD: National Institute for Research in Computer Science and Automation, Lille, France

  • Department: Robotics

Kun Zhang

  • Undergrad: University of Science and Technology of China

  • PhD: Chinese University of Hong Kong

  • Department: Machine Learning

Le Song

  • Undergrad: South China University of Technology

  • PhD: University of Sydney and National ICT, Australia

    • Post doc: Carnegie Mellon University

  • Department: Machine Learning

Min Xu

  • Undergrad: Beihang University

  • PhD: University of Southern California

  • Department: Computer Vision

Mingming Gong

  • Undergrad: Nanjing University

  • PhD: University of Technology Sydney, Australia

    • Post doc: Carnegie Mellon University

  • Department: Machine Learning

Pengtao Xie

  • Undergrad: Tsinghua University

  • PhD: Carnegie Mellon University

  • Department: Machine Learning

  • Notes: Eric Xing advisee

Qiang Sun

  • Undergrad: University of Science and Technology of China

  • PhD: University of North Carolina at Chapel Hill

  • Department: Statistics and Data Science

Qirong Ho

  • Undergrad: Carnegie Mellon University

  • PhD: Carnegie Mellon University

  • Department: Machine Learning

  • Notes: Eric Xing advisee

Steve Liu

  • Undergrad: Tsinghua University

  • PhD: University of Illinois at Urbana-Champaign

  • Department: Machine Learning

  • Notes: Associate Vice President of Research

Ting Yu

  • Undergrad: Peking University

  • PhD: University of Illinois at Urbana-Champaign

  • Department: Computer Science

Tongliang Liu

  • Undergrad: University of Science and Technology of China

  • PhD: University of Technology Sydney, Australia

  • Department: Machine Learning

Xiaodan Liang

  • Undergrad: Sun Yat-sen University

  • PhD: Carnegie Mellon University

  • Department: Computer Vision

  • Notes: Eric Xing advisee

Xiaojun Chang

  • Undergrad: Northwest University, China

  • PhD: University of Technology Sydney, Australia

    • Post doc: Carnegie Mellon University

  • Department: Computer Vision

  • Notes: Published with Eric Xing

Xiaosong Ma

  • Undergrad: Peking University

  • PhD: University of Illinois at Urbana-Champaign

  • Department: Computer Science

  • Notes: Department Chair of Computer Science

Xiuying Chen

  • Undergrad: Wuhan University

  • PhD: King Abdullah University of Science and Technology (KAUST), Saudi Arabia

  • Department: Natural Language Processing

Youcheng Sun

  • Undergrad: Jilin University

  • PhD: Scuola Superiore Sant’Anna, Italy

  • Department: Computer Science

Yuanzhi Li

  • Undergrad: Tsinghua University

  • PhD: Princeton University

  • Department: Machine Learning

Yutong Xie

  • Undergrad: Northwestern Polytechnical University, China

  • PhD: Northwestern Polytechnical University, China

    • Post doc: University of Adelaide, Australia

  • Department: Computer Vision

Zhiqiang Shen

  • Undergrad: Unknown

  • PhD: joint program — University of Illinois Urbana-Champaign and Fudan University

    • Post doc: Carnegie Mellon University

  • Department: Machine Learning

  • Notes: Eric Xing Lab; published with Eric Xing

Zhiqiang Xu

  • Undergrad: Unknown

  • PhD: Nanyang Technological University, Singapore

  • Department: Machine Learning

Current Taiwanese Scholars on MBZUAI Faculty

Chih-Jen Lin

  • Undergrad: National Taiwan University

  • PhD: University of Michigan

  • Department: Machine Learning

Shih-Hao Hung

  • Undergrad: National Taiwan University

  • PhD: University of Michigan

  • Department: Computer Science

Hao Li

  • Undergrad: Universität Karlsruhe, Germany

  • PhD: ETH Zurich

  • Department: Computer Vision

  • Notes: Director of the MBZUAI Metaverse Center

AI in Chains

13 December 2023 at 21:02

Today’s newsletter is brought to you by International Intrigue, a newsletter delivering daily geopolitical news and insights straight to your inbox. Founded by former diplomats with years of on the ground experience in China, International Intrigue offers a sharp daily update on the most important global stories for less than five minutes a day.

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This piece was authored by Ciel Qi, a researcher specializing in emerging technology, security, and US-China relations.

In a recent article on ChinaTalk, anonymous contributor L-squared illustrated the detrimental impact of China’s stringent AI regulations on Chinese firms: “the scope of regulatory targets is actually wider than expected, and Chinese AI diffusion is being seriously compromised by confused and overbearing regulatory action.” Echoing that article’s sentiment, I put forward three arguments on how China’s regulatory framework could stall its domestic generative AI development:

  1. Its expansive content controls could impair AI model performance,

  2. The excessive responsibility it places on AI providers could overburden them,

  3. And its limitations on providers and bans on generating certain kinds of content could deter users from engaging with Chinese AI models.

    ChinaTalk is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

The Interim Measures for the Management of Generative Artificial Intelligence Services 生成式人工智能服务管理暂行办法 (“the Interim Measures”) are a key part of China’s generative AI regulatory landscape. Drafted in April of this year, they came into effect in August, spelling out the responsibilities of providers offering generative AI services to the Chinese public. Currently, these providers are predominantly Chinese tech giants like Baidu (the provider of Ernie Bot 文心一言) and Alibaba (the provider of Tongyi Qianwen 通义千问). And the Interim Measures are supported by a recently released technical policy document called the Basic Security Requirements for Generative Artificial Intelligence Service 生成式人工智能服务安全基本要求 (“the Basic Security Requirements”).

True, the Interim Measures and the Basic Security Requirements express the Chinese government’s encouragement for developing generative AI — but a deeper examination reveals their potential to stall that development.

Expansive Content Control Impairs Model Performance

Content control is a central aspect of China’s generative AI regulations. The Interim Measures stipulate that the content generated by generative AI must adhere to the “core values of socialism” 坚持社会主义核心价值观. Content is prohibited if it promotes “the subversion of state authority” 煽动颠覆国家政权 or the “overthrow of the socialist system” 推翻社会主义制度, or which “threatens or compromises national security and interests” 危害国家安全和利益. Further, generative AI must not generate “false or harmful information, or any content that is outlawed by legal and administrative frameworks” 虚假有害信息等法律、行政法规禁止的内容 (Article 4.1).

Given that the Chinese government considers a wide spectrum of content “false or harmful,” adhering to these regulations requires China-based generative AI service providers to censor such content, regardless of the technical feasibility of doing so. Moreover, implementing a censorship mechanism during the training phase — which could be required by the Basic Security Requirements (discussed in the following section) — could significantly narrow the breadth and diversity of the data that a generative AI model is trained on. As the robustness and effectiveness of a model largely depend on a wide and diverse set of training data, a generative AI model enforcing under extensive content regulation is likely to exhibit compromised performance — including, as L-squared also suggested, reduced “helpfulness and honesty.”

Excessive Responsibility Overburdens Generative AI Providers

China’s regulations on generative AI impose a significant burden on providers. A key requirement is for them to file algorithms with the Cyberspace Administration of China or its local branches within ten days of launching their generative AI service. As stipulated in the 2022 Administrative Provisions on Algorithm Recommendation for Internet Information Services 互联网信息服务算法推荐管理规定, the Interim Measures mandate this filing obligation only when a provided service possesses “public opinion attributes or social mobilization capabilities” 舆论属性或者社会动员能力. But since the Chinese government could interpret this condition so broadly, it’s likely that any generative AI provider catering to the public will be obligated to fulfill this requirement. While big Chinese tech companies may find compliance straightforward, smaller entities or startups (which L-squared estimates make up 44.2% of Chinese companies that have filed algorithms) may find the process burdensome. And the need to prepare and submit the required documentation shifts companies’ focus away from other vital tasks such as bug fixing and releasing new iterations, which are often crucial steps post-launch.

The Interim Measures demand — without mentioning specifics — that generative AI providers conduct a security review 安全评估 (Article 17). Even so, insight into the expectations can be gleaned from the recently released draft of the Basic Security Requirements. This document mandates providers to carry out a security assessment of training data and blacklist datasets containing more than five percent of “illegal and harmful information” 违法不良信息. While the Interim Measures require providers to offer necessary training of data annotators (see Article 8), the Basic Security Requirements take a step further by requiring providers to regularly evaluate their annotators and certify those who meet the qualifications (Article 8.1). Moreover, providers whose services extend to minors are required to implement measures that prevent addiction and filter out inappropriate content for minors (Article 7.a.3-4). Before public launch (Article 4) and after major updates of a generative AI service (Article 7.g.2), the Basic Security Requirements also demand a security review to evaluate the security of training data and generated content, with the review findings to be submitted to Chinese authorities.

Even for well-resourced big Chinese tech companies, ensuring compliance with such requirements will incur additional costs, either in terms of human capital or financial resources. For example, data annotation in China is commonly outsourced to third parties, but the requirements necessitate that providers now invest additional resources in training, evaluating, and certifying data annotators in-house. For small- and medium-sized companies, compliance with the regulations could potentially drain vital limited resources.

Potential User Disengagement

China’s framework for regulating generative AI could potentially deter user engagement. While, as noted above, regulations primarily delineate the responsibilities of providers, the Interim Measures also mandate that users of generative AI services must not generate false or harmful information. And service providers still don’t escape here: per Article 14, they are required to report to Chinese authorities if they discover users engaging in illegal activities with their generative AI services.

Even a highly fine-tuned model might inadvertently generate content deemed harmful, especially given the Chinese government’s broad categorization of harmful and illegal information. That knowledge may discourage users from utilizing generative AI services: they might fear accidentally generating information which would put them at risk. Moreover, providers might tighten access to their APIs to preempt any possible misuse. Even before the release of the Interim Measures, some Chinese companies already had a relatively stringent screening process for prospective users in place — so with more companies implementing heightened access restrictions, even more potential users will likely be deterred.

The potential unwillingness of users to utilize domestically provided generative AI services, stemming from content-control concerns or restricted access, might drive them to use non-Chinese generative AI services — which may lead to a dwindling user base for China’s local generative AI services, impacting the revenues of the companies behind them. Although the Chinese government might offset these financial drawbacks through research funding, thus ensuring continued innovation despite suboptimal revenues, China’s domestic generative AI could lag behind international competitors without more public testing and feedback as to how to improve a model.

ChinaTalk is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber.

Conclusion and Considerations

The rapid development of generative AI, coupled with the potential risks posed by this technology, underscores the need for regulations. While various governments are examining and evaluating the most viable regulatory framework for generative AI, China has taken a forward-leaning stance by setting out — and in some instances implementing — generative AI regulations. Nevertheless, by focusing on expansive content control and placing excessive responsibility on service providers, China risks stalling its domestic generative AI development.

To be sure, this slowdown is not inevitable. After all, the Interim Measures are called “interim,” suggesting a possible willingness to amend them down the road. Moreover, as the Basic Security Requirements have just concluded the process of soliciting public opinion, it’s possible they will be moderated in the final policy version (likely facilitated, as L-squared points out, by “pushback from [Chinese] industry”). And even if the original form of both regulations remains unchanged — in which case China’s generative AI is likely to be significantly constrained — China’s regulatory framework could still offer other countries interesting angles to consider in shaping their own regulatory frameworks, such as regulating the data annotation industry, preventing addiction among minors, and enhancing transparency in generative AI services.

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