Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neural networks overfit data when they can, and how evolution works the same way on a much slower timescale.
Show notes:
It’s generally agreed machine learning and AI provide neuroscience with tools for analysis and theoretical principles to test in brains, but there is less...
Show notes: His new book, The Deep Learning Revolution: His Computational Neurobiology Laboratory at the Salk Institute. His faculty page at UCSD. His first...
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