Evolving Benchmarks
Tim and Melanie discuss how benchmarks act as filters to weed out inferior models and the importance of evolving benchmarks to test for generalization beyond initial challenges. They highlight the necessity of continuous engineering and iteration in the learning process.In this clip
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Machine Learning Street Talk (MLST)
Prof. Melanie Mitchell 2.0 - AI Benchmarks are Broken!
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