Chinese AI models appear close to the frontier primarily because they are trained on the outputs of leading U.S. models. This creates a dependency loop: they can only catch up by using the latest from the West, ensuring they remain followers rather than innovators who can achieve a true breakthrough.

The proposed data center moratorium, while intended to address safety, would create a strategic advantage for China and other nations if enacted unilaterally. An American slowdown without global agreement allows adversaries to catch up or surpass the US in AI, highlighting the prisoner's dilemma inherent in global AI regulation.

Despite impressive models from companies like DeepSeek, China's AI ecosystem is heavily reliant on "distilling"—essentially copying and refining—open-source models from the US. This dependency on an external innovation engine is a major weakness in their national strategy to achieve genuine AI leadership and self-sufficiency.

Facing compute and capital shortages, Chinese AI labs don't pioneer frontier research. They wait for Western labs to publish breakthroughs, likening it to 'knowing the answer to the homework,' then work backwards to replicate them, focusing resources on efficient post-training.

China's AI lag isn't just from US sanctions; it's a strategic error of believing domestic chips are adequate. Their labs excel at distilling Western models, but this parasitic strategy fails completely if frontier models are no longer released openly.

Pausing or regulating AI development domestically is futile. Because AI offers a winner-take-all advantage, competing nations like China will inevitably lie about slowing down while developing it in secret. Unilateral restraint is therefore a form of self-sabotage.

A US policy that slows down its own AI labs for safety is logically flawed and self-defeating unless it also effectively slows China's progress. Unilateral deceleration doesn't make the world safer; it simply cedes ground to a less safety-conscious competitor, increasing net risk.

Framing the US-China AI dynamic as a zero-sum race is inaccurate. The reality is a complex 'coopetition' where both sides compete, cooperate on research, and actively co-opt each other's open-weight models to accelerate their own development, creating deep interdependencies.

Pausing frontier AI development is an asymmetric strategic concession by the U.S. It halts progress in a key area of American advantage while giving China time to close its own critical gaps, particularly in semiconductor manufacturing. This could reset the geopolitical race on less favorable terms for the U.S.