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.

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.

While China now leads in published AI research papers, this is not a sign of US decline. Instead, it reflects a talent shift from US academia into private AI labs where cutting-edge research is kept proprietary. The US's top talent has gone dark, not disappeared, skewing public data on innovation output.

Counterintuitively, China leads in open-source AI models as a deliberate strategy. This approach allows them to attract global developer talent to accelerate their progress. It also serves to commoditize software, which complements their national strength in hardware manufacturing, a classic competitive tactic.

The performance gap between US and Chinese AI has closed, establishing them as co-leaders. A key divergence is China's embrace of open models, while major US players have shifted to closed, proprietary systems. This creates a significant geopolitical and technological divide in the global AI ecosystem.

The closed nature of leading US AI models has created an information vacuum. Sridhar Ramaswamy notes that academia is now diverging from US industry and instead building upon published work from Chinese companies, which poses a long-term risk to the American innovation ecosystem.

China's greatest asset in the AI race is its human capital. It produces the world's largest number of STEM graduates, creating a deep talent pool of engineers and scientists that makes it a formidable, long-term competitor to the United States.

China identifies top talent early through a brutally selective system, not a mass-production factory. Graduates from these programs disproportionately found and lead the nation's most important tech and AI companies, directly linking this educational pipeline to its global technology ambitions.

Despite leading in AI investment, the United States' ability to attract global talent is plummeting. The Stanford AI Index report highlights a shocking 80% drop in AI researchers and developers moving to the US in the last year, signaling a major shift in the global distribution of expertise.