Positive users praise the new paper on joint scaling laws for LLM pretraining and RL post-training as insightful and useful, while negative users dismiss the research as only feasible with unrealistic unlimited compute.
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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 How much do you think more PT → better RL will generalize to larger scales / other tasks?
@Pavel_Izmailov You have to have unlimited compute budget to even think about researching this stuff
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.
Positive users praise the new paper on joint scaling laws for LLM pretraining and RL post-training as insightful and useful, while negative users dismiss the research as only feasible with unrealistic unlimited compute.
Based on 7 visible X reactions from 16 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.