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:
Chris and I discuss his Spaun large scale model of the human brain (Semantic Pointer Architecture Unified Network), as detailed in his book How...
Support the show to get full episodes and join the Discord community. Steve Byrnes is a physicist turned AGI safety researcher. He's concerned that...
Support the show to get full episodes and join the Discord community. Check out my short video series about what's missing in AI and...
