Large-Scale Model Distillation Policy Effect Questioned: Distillation is Merely a Shortcut in Independent Lab Data, Blocking Fails to Stop China's AI Catch-up

According to Dynamic Beating monitoring, in response to Washington and Anthropic's attempt to disrupt China's large model "distillation" pathway through blocking, Kevin S. Xu, former GitHub Internationalization Strategic Lead and founder of Interconnected Capital, pointed out that adversarial distillation is just a desperate shortcut for some Chinese independent labs facing data scarcity, and blocking the API cannot stop the overall progress of Chinese AI.

The mentioned DeepSeek, Dark Side of the Moon, and MiniMax are all independent labs lacking group ecosystem support, facing the hard hit of insufficient high-quality post-training data for inferences. In contrast, labs backed by Alibaba (Qwen), ByteDance (Seed), or Xiaomi have vast proprietary scenario data comparable to Google and Apple and do not rely on distillation. Therefore, the blocking policy may only temporarily hinder independent labs and cannot shake the foundation of Chinese tech giants.

The external hype about China's "data advantage" is actually a misconception: in terms of the high-quality annotated knowledge and evaluation data required to train large models at the forefront, China not only lacks an advantage but also severely lacks a mature commercial data supply chain like Scale AI or Surge. Due to the poor quality of domestic data service providers, independent labs, in their desperation, and out of laziness for shortcuts, have used API distillation as a cheap data acquisition strategy.

However, the data annotation industry is a low-entry commercial model issue, not a technological barrier like lithography. The domestic supply-demand gap can be easily filled. In the long run, although student models distilled purely theoretically cannot surpass teachers, as large models are still built by human engineers, regardless of whether the U.S. forcefully cuts off the API pathway, smart and hardworking Chinese developers will eventually break this theoretical restraint and design large models that outperform mentors. The U.S. blockade policy is not only ineffective but may prematurely cut off the theoretical restraint that could have locked Chinese models under the "student" ceiling.