Many users praised the new paper on joint scaling laws linking LLM pretraining to RL post-training as insightful and useful work, while others dismissed the research as only feasible with unlimited compute or mere vibe research.
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The study optimizes compute splits between pretraining and RL.
Cool! I’m curious how the optimal compute split btwn pre and post training would change if you measured by $ instead of FLOPs FLOPs are much more expensive in post training cuz gpu utilization is much lower (and learning rates are lower so weights change less per FLOP too), so maybe “model quality gain per $ spent” is better in pretraining just off the fact that a gpu hour gets you more value? Not sure abt this though If we had a fixed budget like let’s say $1M of b200 computer hours, it would be interesting to see how this work can inform that balance Either way, awesome work!
@Pavel_Izmailov awesome work! internally we also ended up with a similar law for midtraining/CPT <> RL on totally new synthetic tasks.
@Pavel_Izmailov @yeabu369 Somehow there’s no “reasoning” anywhere in the single forward pass. What kind of research is this?
@Pavel_Izmailov You have to have unlimited compute budget to even think about researching this stuff
@j_foerst Games are mostly easy to understand, yet have complex dynamics and outcomes. Great tool
we have gone full circle: RL was first popularised on games, then forgotten about in the early era of LLMs, reinvented for reasoning and those approaches are now being tested on games.
Many users praised the new paper on joint scaling laws linking LLM pretraining to RL post-training as insightful and useful work, while others dismissed the research as only feasible with unlimited compute or mere vibe research.
Based on 8 visible X reactions from 20 accounts; directional sample.
Ask a question below.
Published answers will appear here.
@j_foerst Sarcasm aside, it's worth noting one of the first papers on scaling laws for test time scaling was from Andy Jones on the Game of Hex.
Best game of all times
@j_foerst We may someday solve the true test of AGI: playing StarCraft from pixels instead of game state.
@j_foerst verrrrrry slowly. >50m sps single-gpu now.