Doubling Sample Impact
Ryan discusses the diminishing returns of doubling sample sizes in machine learning models, highlighting the exponential growth needed for marginal improvements. He reflects on achieving non-trivial performance with a small number of doublings, showcasing the challenges and potential of optimizing language models.In this clip
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