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Jack Morris
@jxmnop
research @engramlab // language models, information theory, science of AI
加入 October 2016
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there are some really interesting rumors going around related to the distillation of open-weights models (Kimi, Qwen, Minimax, etc.) and they're very related to my PhD work The narrative [speculative]: • good distillation relies on reasoning traces, normally hidden from users • Chinese labs figured out in early 2026 how to reverse-engineer reasoning from Claude Code and Codex • they were able to collect large amounts of long-horizon data *with reasoning traces included* this way • this jailbreak led to a new wave of OSS models we've enjoyed over the past few months I'm not sure how true it is, but reasoning extractability seems like a huge uncertainty around the future of open models in particular i'm curious how much having the reasoning matters. this (plus Anthropic's messaging around distillation attacks) indicates that reasoning chains are crucial for distilling model capabilities. our research ( found something different: if you train a high-quality reasoning inverter, it's often pretty easy to reconstruct useful traces from frontier models given their outputs. figuring out how to approximate frontier model reasoning traces might turn out to be an existential problem for open weights models
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