roon’s ‘a few thoughts’ on Cammarata’s essay: interp breakthroughs likely advance capabilities; labs too focused on local incentives
roon @tszzlX
Why it matters
Second high-reach roon post on the essay (~173k views on Oct 16) with an OpenAI insider’s critique that ‘fundamental breakthroughs like this are coming from outside’.
Summary
Three-point post by OpenAI’s roon late on Oct 15 (~173k views, ~2.9k likes on Oct 16 per fxtwitter). (1) Pretraining science is like steam engines before thermodynamics; if Cammarata is right, ‘which i am pretty sure he is’, pretraining was ‘slouching towards monosemanticity’, and ‘my guess would be that major breakthroughs in interp also advance capabilities’. (2) Personal note: Cammarata is a close friend who shaped roon’s start at OpenAI. (3) ‘it does not bode that well for the major model companies, oai included, that fundamental breakthroughs like this are coming from outside. we’ve become too much of a pressure cooker focusing on local incentives … mostly doing engineering, rather than fundamental research’.
Archived text
a few thoughts:
pretraining science is kind of like how people built quite good steam engines before they understood thermodynamics. “Science owes more to the steam engine than the steam engine owes to science.”-(L.J. Henderson). if nick is right, which i am pretty sure he is, progress points in the direction of more interpretability, and pretraining was “slouching towards monosemanticity”. my guess would be that major breakthroughs in interp also advance capabilities
nick is a good friend of mine, safe to say my origin story at openai wouldn’t have happened if i hadn’t met him, and it’s fascinating watching him operate and seeing the early drafts evolve into this. he’s the most profoundly happy guy I know- not driven by guilt, activism, or religious terror, but by fascination. he of course understands the stakes of understanding neural networks, but it doesn’t seem like the core reason he does it: he just loves the neural nets. afaict he’s posting this from some beautiful hideaway in tokyo. there’s a lesson in there for all the +EV maxers. i feel very grateful to have met him
i do think it’s crazy how few people across the world were staring at neural nets growing: most have moved to a different level of behaviorist analysis, thinking about reward functions and test scores and whatnot. it does not bode that well for the major model companies, oai included, that fundamental breakthroughs like this are coming from outside. we’ve become too much of a pressure cooker focusing on local incentives, studying narrow tracks under old paradigms, mostly doing engineering, rather than fundamental research, and implicitly hoping the next model will figure it out
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Nick Cammarata, Interpretability researcher, Goodfire