# Lambert says distillation isn't clearly bad for US AI competitiveness

> Original title: Glad to see more institutions exploring the ideas here. I don’t think it’s cut and dry that distillation is bad for the US’s AI competiti...

- Source: Nathan Lambert
- Published: 2026-10-29T18:58:53.000Z
- Bad Influence: https://badinfluence.news/items/du1ln90bs893wt29ziqj93gdt
- Original: https://x.com/natolambert/status/2115881074115084733

## Summary

Nathan Lambert says it is not cut and dry that distillation harms US AI competitiveness, replying to institutions exploring the question. He is responding to a post by Archie Hall, which argues in The Economist that efforts to ban Chinese models trained partly on American ones are misguided. Hall's case is that distillation can aid price competition and national security, and that US developers' IP claims are weak given their own fair use defense for training data.

## Post

Glad to see more institutions exploring the ideas here. I don’t think it’s cut and dry that distillation is bad for the US’s AI competitiveness.

## Quoted post @ArchieHall

> In praise of distillation. We (@kuhhbin) argue in @TheEconomist this week against efforts to ban Chinese models trained in part on American ones. 
> 
> OpenAI and Anthropic may dislike distillation, but:
> — Price competition is good for the ecosystem
> — Paradoxically, distillation may be good for national security, both in propagating US developers' safeguards on cyber/bio risk to Chinese models, and in keeping China in fast-follower mode
> — The US developers' own IP claims here are pretty flimsy, since distillation isn't all that different to the 'fair use' defense they're using for the training data they hoover up.
> 
> https://www.economist.com/leaders/2026/10/29/let-china-copy-american-ai

https://x.com/ArchieHall/status/2115851542511161620