The US-China AI competition is far more complicated than a simple arms race. While both nations publicly frame their AI efforts as strategic rivals, a surprising pattern is emerging: Chinese AI leaders are presenting at American tech conferences, US chipmakers are profiting from Chinese customers, and both ecosystems remain deeply interconnected despite export controls and geopolitical tensions .

Why Are Chinese AI Startups Speaking at US Tech Events?

In March 2026, Yang Zhilin, founder of Beijing-based Moonshot AI, delivered a keynote presentation at Nvidia's GPU Technology Conference in San Jose, California, one of the world's most influential semiconductor events. Less than two weeks later, Yang presented nearly identical remarks at China's state-backed Zhongguancun Forum in Beijing, where attendees included Beijing Mayor Yin Yong and Ding Xuexiang, a member of the Communist Party's Politburo Standing Committee . This unusual pattern reveals something unexpected about how the AI race actually functions on the ground.

Yang, a Carnegie Mellon University doctoral graduate, leads development of the Kimi family of foundational AI models, which are large language models (LLMs) that power conversational AI systems. His presence at Nvidia's flagship event might seem contradictory given heated rhetoric about US-China AI competition, yet it reflects a deeper reality: the two ecosystems remain symbiotically connected even as geopolitical forces push them apart .

"There's many different cross-cutting factors and interests that are pulling in either direction. Even among the US companies themselves, they have very different perspectives and views on Chinese AI and competition," said Kyle Chan, a fellow at the Washington-based Brookings Institution think tank.

Kyle Chan, Fellow at Brookings Institution

What Is 'Co-opetition' and How Does It Shape the AI Race?

Experts describe the current US-China AI dynamic as "co-opetition," a term blending competition with cooperation. This framework acknowledges that while both nations compete for AI dominance, they simultaneously depend on each other's technologies, talent, and markets . Nvidia exemplifies this paradox perfectly. The company, the world's leading designer of advanced semiconductor chips that power the global AI industry, announced at its 2026 conference a revenue outlook of at least $1 trillion through 2027, driven by exploding demand for its most advanced Blackwell and Rubin chips .

Much of that demand comes from Chinese AI companies and research institutions that need Nvidia's hardware to train and deploy their own AI models. Simultaneously, Nvidia stands to be the biggest beneficiary of convergence between the US and Chinese AI ecosystems, as both nations require its chips regardless of geopolitical tensions . This creates a situation where the US company profits from competition it ostensibly opposes.

How Are US Policymakers Balancing Competition With Export Strategy?

The Biden and Trump administrations have pursued contradictory approaches to the AI race. While lawmakers on both sides of Congress continue to focus attention on tightening export rules to block foreign access to US AI and chip technology, the administration is simultaneously working to promote global deployment of US-developed "full-stack" AI export packages spanning hardware, software, models, and applications . This reflects a strategic pivot: rather than simply restricting Chinese access, the US government plans to designate these comprehensive AI offerings as priority exports and levy support through coordinated federal export and financing tools .

The administration's willingness to loosen certain export controls represents a significant shift in US policy, closely tied to the goal of maintaining global market leadership in AI . However, this strategy creates tension with the simultaneous push to tighten export rules, revealing fundamental disagreement within US policymaking about whether containment or market dominance is the better approach.

Steps to Understand the Geopolitical Implications of the AI Race

• Monitor Semiconductor Tariff Decisions: Ongoing Section 232 investigations could result in tariffs on key sectors including robotics and industrial machinery, creating uncertainty for companies operating in both US and Chinese markets. The Supreme Court ruling on presidential tariff authority under the International Emergency Economic Powers Act could reshape the entire tariff landscape before the end of June 2026.
• Track Export Control Policy Changes: The administration continues to refine which AI technologies can be exported to which countries. Companies must stay current on whether full-stack AI packages are being promoted as priority exports or restricted, as this directly affects business models and investment decisions.
• Watch for Cross-Border Investment Restrictions: New trade deals signed by the current administration include both investment restrictions and requirements that encourage overseas capital to back US assets. Private equity firms and international investors must implement multijurisdictional due diligence and contractual protections to navigate these evolving requirements.

The geopolitical environment remains unstable despite the current US-China détente. While the relationship is stable for the moment, cracks could be market-moving . The administration continues to threaten tariffs on Europe and other trading partners for foreign policy objectives, and tension is expected to grow with the European Union over its implementation of digital trade regulations that target US technology firms .

What makes the current moment unique is that neither pure competition nor pure cooperation accurately describes the US-China AI race. Instead, both nations are locked in a complex dance where they compete fiercely for technological dominance while remaining dependent on shared infrastructure, talent, and markets. Chinese AI startups will likely continue presenting at US tech conferences, US companies will continue profiting from Chinese demand, and policymakers will continue debating whether to restrict or promote these connections. The outcome of this paradox may ultimately determine which nation leads the global AI industry .