Garry Tan Urges U.S. Open-Weight AI Labs to Distill Frontier Models, Too

In an interview with CNBC earlier this week, Tan said he would do nothing about the practice. “We could argue that there should be an American distillation regime,” he said. He elaborated to TechCrunch that he wants smaller American open-weight AI labs to use the same kind of training techniques on American frontier AI labs, giving the United States a broader set of open-weight options that are not Chinese.

Distillation occurs when a model maker extensively prompts another model to learn how it works and reasons. AI labs commonly and legitimately use the technique to help train new models.

Anthropic this week released its second report alleging that Chinese labs are engaged in “illicit distillation attacks,” hiding their identities to distill without permission and relying on fraud and stolen credentials. Anthropic CEO Dario Amodei had previously publicly called on U.S. regulators to crack down on distillation.

Tan does not agree. He is not advocating that American AI labs use stolen credentials to distill, according to his comments to TechCrunch. He wants them to be free to come in the front door.

His argument is twofold. He said he believes it is an overreach for AI labs to dictate what their customers can do with the information their models share with them. He also noted that proprietary AI labs did not ask permission when they collected as much human knowledge as they could to train their models, and that they ingested copyrighted material without the permission of intellectual property holders.

Asked why American labs should be free to distill too, Tan told TechCrunch: “Controlling what users and customers do with API calls to closed weight models feels constraining, and there’s a role government can play here to normalize the fact that access to intelligence that was trained on broad public access data should itself also be more a form of a public good than something locked away behind restrictive terms of service.”

Tan wants to see a balance between open-weight AI labs and frontier labs. “They are at the frontier and driving it forward. We want that to be fundable, and be a great business model ongoing,” he told CNBC. “You want open weight models to give people freedom and access.”

He described the worst outcome for AI as concentration of frontier power in one proprietary provider. “The nightmare scenario, the doomer scenario for AI is that there’s just one company,” he said. “It has the best access to capital. It has the best AI researchers. It runs away with it and suddenly there’s one company that’s monolithic. And that would be bad.”