Nathan Lambert on the distillation ban: It may not harm US competitiveness
In response to Archie Hall and kuhhbin's article in The Economist opposing a ban on some Chinese models trained based on American models, Nathan Lambert said he welcomes more institutions discussing these views and believes that it is not a settled conclusion that distillation harms US AI competitiveness.
View original postIn 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://t.co/suRLpdoGUT
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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://t.co/suRLpdoGUT
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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.