Jared Kaplan | Scaling Laws and Their Implications for Coding AI
Автор: Harvard CMSA
Загружено: 2022-03-04
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Описание:
New Technologies in Mathematics Seminar 3/2/2022
Speaker: Jared Kaplan, Johns Hopkins Dept. of Physics & Astronomy
Title: Scaling Laws and Their Implications for Coding AI
Abstract: Scaling laws and associated downstream trends can be used as an organizing principle when thinking about current and future ML progress. I will briefly review scaling laws for generative models in a number of domains, emphasizing language modeling. Then I will discuss scaling results for transfer from natural language to code, and results on python programming performance from “codex” and other models. If there’s time I’ll discuss prospects for the future — limitations from dataset sizes, and prospects for RL and other techniques.
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