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Connections between physics and deep learning
MITCBMM
Max Tegmark's MIT CBMM talk on why deep learning works so well. He argues that the laws of physics and the symmetries in physical data make it compressible into small neural networks, tying physics to network structure.
HN recommends it as a clear argument for why deep and cheap learning succeeds, often alongside the associated paper.
6 Hacker News mentions · 2016–2026