This week’s AlphaTensor announcement shows not only that AI is getting really good at doing things, but also that DeepMind are really good at getting AI to do things. Their approach is a variant of the deep reinforcement-learning-guided Monte Carlo tree search that they have applied so successfully to playing Chess and Go. What they have done, very effectively, is to design a game with the objective of finding the most efficient tensor multiplication algorithm for a matrix of some dimension.
AlphaTensor, Taste, and the Scalability of AIs
AlphaTensor, Taste, and the Scalability of…
AlphaTensor, Taste, and the Scalability of AIs
This week’s AlphaTensor announcement shows not only that AI is getting really good at doing things, but also that DeepMind are really good at getting AI to do things. Their approach is a variant of the deep reinforcement-learning-guided Monte Carlo tree search that they have applied so successfully to playing Chess and Go. What they have done, very effectively, is to design a game with the objective of finding the most efficient tensor multiplication algorithm for a matrix of some dimension.