Chess and Models
The discussion highlights how a language model can not only generate valid chess moves but also perform at a high level of quality. This capability suggests an underlying understanding of the chessboard that transcends simple statistical predictions. The ability of the model to reconstruct the board state and make informed decisions without explicit rule training challenges traditional notions of model limitations and understanding.In this clip
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Machine Learning Street Talk (MLST)
Nicholas Carlini (Google DeepMind)
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