Instead of an outright ban on open-source AI, the US administration is signaling a different strategy: cracking down on IP theft. Treasury Secretary Besant stated that if overseas models are found to be stealing from US companies, the government has the ability to sanction the companies behind them, effectively creating a barrier without banning the technology itself.

The launch of Moonshot's powerful open-source AI model, Kimi K3, has polarized the tech community. One side sees it as legitimate innovation with a viable business model, while the other suspects industrial espionage, IP theft, and a deliberate geopolitical strategy to undermine American AI dominance.

The push for stricter US government action against China's AI practices is not just from politicians. Leading AI companies like OpenAI and Anthropic are pressuring Washington to curb Chinese 'distillation' of their models, framing it as a threat to national security and America's lead in AI.

Despite intense domestic rivalry, top US AI labs like OpenAI, Anthropic, and Google are collaborating to detect "adversarial distillation"—where Chinese firms copy their models. This rare cooperation shows the shared commercial and national security threat from foreign competitors outweighs their direct competition.

Comparing AI distillation to Ford taking apart a Tesla is a flawed analogy. Reverse-engineering a legally purchased product is generally legal under trade law. However, large-scale distillation of an AI model via API calls typically violates the provider's terms of service, creating a distinct legal challenge around digital IP and contract law.

US officials and AI labs allege Chinese firms are engaged in industrial-scale IP theft. They reportedly use fraudulent accounts to extract capabilities from US models like Claude to train their own, creating a facade of domestic innovation.

Frontier AI labs are restricting API access not just for security, but to prevent competitors from using 'distillation' to create cheap copies of their models. This practice makes it impossible to recoup massive R&D investments, forcing a move towards more restrictive, geopolitically motivated access.

Anthropic is strategically labeling the copying of its model outputs by Chinese firms as 'distillation attacks.' This reframes a terms-of-service violation into a geopolitical and national security concern, aiming to trigger U.S. legislative action and sanctions against competitors.

China is creating cheaper, 'good enough' AI models by training them on the outputs of US frontier models. This technique, called distillation, undercuts the revenue of US AI companies, threatening their ability to service the massive debt from their infrastructure buildout.