Accusations that Chinese labs cheat by copying US models are misleading. The practice, known as distillation, is common across the industry (including by Elon Musk's xAI) and academia. Now, with Chinese labs dominating open source, American startups are increasingly building on top of Chinese models.

There is a profound hypocrisy in the AI industry's stance on intellectual property. Companies that built their foundational models by scraping the entire internet are now seeking regulatory protection to prevent others from distilling or learning from their models—mirroring how the music industry fought Napster after profiting from an open ecosystem.

The U.S. Treasury is threatening sanctions over Chinese AI labs 'distilling' U.S. models, framing a technical training process as intellectual property theft. This political reframing allows the use of powerful economic weapons outside of traditional court systems, escalating the U.S.-China AI rivalry.

The controversial practice of AI 'distillation' is not IP theft but a modern form of competitive benchmarking. It's akin to how early Google submitted queries to Yahoo to compare and improve its own search results. The focus is on learning from a competitor's public output, not stealing their underlying software or code.

US AI labs' efforts to prevent foreign rivals from distilling their models face accusations of hypocrisy. Critics point out that these labs train their own models on vast amounts of public data without permission. This "pot calling the kettle black" dynamic complicates legal and ethical arguments against industrial-scale distillation.

AI companies protest when competitors "distill" their models, calling it a violation. This stance is deeply ironic, as it mirrors the complaints of artists and creators whose work was scraped without permission to build the original models. The industry fails to acknowledge this double standard.

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.

A new battle line in AI is emerging around model distillation. US officials are framing "covert industrial distillation," like Moonshot AI's alleged activities, as unacceptable IP theft. This is distinct from legitimate distillation used to create smaller, efficient open-source models, setting the stage for future regulation and trade disputes.

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.