Machine Learning Street Talk (MLST) podcast show image

Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

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A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mutations only need to be useful about 1% of the time for the search to keep making progress.Akarsh is a PhD student at MIT working with Phillip Isola, works with Saka… Play episode

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