In an essay not so long ago, I argued that the technology that we consider as artificial intelligence today is in reality a very good solution-finder. Given that AlphaTensor is finding faster matrix multiplication algorithms, you can even take a more ominous view of AI systems creating better AI systems.īut a deeper reality of AlphaTensor, which has been less highlighted in its media coverage, is how the right combination of human and artificial intelligence can help find the right solutions to the right problems. At first glance, it seems that DeepMind has managed to create an AI system that is general enough to tackle a wide range of unrelated problems. To create AlphaTensor, scientists at DeepMind used AlphaZero, the deep learning system that previously mastered board games like go, chess, and shogi. Therefore, there are many immediate applications for an AI system that can improve the efficiency of matrix multiplication. Matrix multiplication is at the heart of many computational tasks, including neural networks, 3D graphics, and data compression. This article is part of our coverage of the latest in AI research.ĭeepMind has made another impressive artificial intelligence announcement with AlphaTensor, a deep reinforcement learning system that discovers algorithms to make matrix multiplications much more efficient.
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