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Excited to share our work published in the @Nature cover, which surpasses human knowledge in a 50-year-old open question in Mathematics!
We introduce #AlphaTensor, an #AlphaZero-based RL agent that discovers faster exact matrix multiplication algorithms.
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We introduce #AlphaTensor, an #AlphaZero-based RL agent that discovers faster exact matrix multiplication algorithms.
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Matrix Multiplication (MatMul) is one of the root node problems where any speedup results in improvements in many areas, including Matrix Inversion, Factorization, & Neural Networks.
In industry, MatMul is used for image processing, speech recognition, computer graphics, etc. 2/
In industry, MatMul is used for image processing, speech recognition, computer graphics, etc. 2/
We formulated the problem of finding MatMul algorithms as a single-player game. In each episode, the agent starts from a tensor representing a MatMul operator and has to find the shortest path to an all-zero tensor. The length of this path corresponds to the # multiplications. 3/
Today in @Nature: #AlphaTensor, an AI system for discovering novel, efficient, and exact algorithms for matrix multiplication - a building block of modern computations. AlphaTensor finds faster algorithms for many matrix sizes: dpmd.ai/dm-alpha-tensor & dpmd.ai/nature-alpha-t… 1/
Starting from scratch, #AlphaTensor gradually improves from finding the “class-room” algorithm to discovering historical algorithms such as Strassen’s - eventually surpassing them. This work is an example of how AI can advance the field of algorithmic discovery. 2/
By @AlhusseinFawzi, @matejbalog, Aja Huang, Thomas Hubert, @ber24, @BarekatainAmin, @SashaVNovikov, @franciscuto, @Mononofu, @GrzegorzMS, David Silver, @demishassabis, and @pushmeet. 3/3
