The NSA, FBI and CISA released a joint advisory today accusing China-based AI companies of conducting what they describe as “aggressive, industrial-scale distillation” of U.S. frontier AI models. According to the advisory, the companies are systematically extracting capabilities and proprietary functionality from frontier models and using those outputs to train their own systems. U.S. officials say this can let models close the capability gap without paying the full cost of frontier-scale compute, electricity, research and development. The agencies also claim these operations are distributed across multiple AI providers, cloud platforms and infrastructure to make detection more difficult. Distillation itself is a completely legitimate ML technique, so the interesting question isn’t whether distillation exists — it’s whether frontier capabilities can actually be reproduced at large scale by repeatedly querying stronger models. If frontier capabilities can be efficiently distilled from other models, does that fundamentally change what “having a better model” means in the AI race? submitted by /u/Cklly2004
Originally posted by u/Cklly2004 on r/ArtificialInteligence