开启时会模糊预览图，关闭后正常显示
can we appreciate the insanity of “Older hardware underperformed in evals and was removed” for what is conceptually a lot of parallel General Matrix Multiplications
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or do we already do that because we are minimising KL with more recency bias rather than over the entire distribution?
RL and efficient distributed pretraining • eXperiments lab • memes and training lores
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why do we accept approximating distribution from data/model with forward KL (left picture)? why not work towards algos that look like (right picture)?
or do we already do that because we are minimising KL with more recency bias rather than over the entire distribution?