Who’s Afraid of Chinese Models?

The U.S. should pass a law making data collection for training models fair use and barring terms of service that forbid distillation, argues Ben Thompson on Stratechery. He also suggests Alibaba's release of Qwen 3.8 Max as open weights may have been influenced by a Xi Jinping speech encouraging open source and collaboration.

Who’s Afraid of Chinese Models? https://stratechery.com/2026/whos-afraid-of-chinese-models/ The U.S. should pass a law that 1 makes explicit that collecting data for training models is fair use, and 2 bars terms of service that forbid distillation, for U.S. companies at a minimum. Stopping distillation — which is literally just querying the API — is nearly impossible; the U.S. should go the other way and lean into a new copyright policy that both indemnifies the labs and also guarantees that what they learned fuels further innovation for everyone else. Ben also theorizes that Alibaba's decision to release Qwen 3.8 Max as open weights - a reversal from their decision not to release Qwen 3.7 Max https://qwen.ai/blog?id=qwen3.7 in May - may have been influenced by a recent speech http://english.scio.gov.cn/topnews/2026-07/18/content 118605932.html by Xi Jinping, who said: We should seize this rare, historic opportunity to encourage open source, openness, collaboration and sharing. Via John Gruber https://daringfireball.net/linked/2026/07/20/thompson-chinese-models-distillation Tags: ai https://simonwillison.net/tags/ai , generative-ai https://simonwillison.net/tags/generative-ai , llms https://simonwillison.net/tags/llms , training-data https://simonwillison.net/tags/training-data , qwen https://simonwillison.net/tags/qwen , ai-ethics https://simonwillison.net/tags/ai-ethics , ai-in-china https://simonwillison.net/tags/ai-in-china