How AI Discovered a Faster Matrix Multiplication Algorithm

Researchers at Google research lab DeepMind trained an AI system called AlphaTensor to find new, faster algorithms to tackle an age-old math problem: matrix multiplication. Advances in matrix multiplication could lead to breakthroughs in physics, engineering and computer science. AlphaTensor quickly rediscovered - and surpassed, for some cases - the reigning algorithm discovered by German mathematician Volker Strassen in 1969. However, mathematicians soon took inspiration from the results of the game-playing neural network to make advances of their own. Read the full article at Quanta Magazine: https://www.quantamagazine.org/ai-rev... Correction: At 2:53 in the video, the text previously read "67% less" but has been changed to "67%" for accuracy. 00:00 What is matrix multiplication? 01:06 The standard algorithm for multiplying matrices 02:06 Strassen's faster algorithm for faster matrix multiplication methods 03:55 DeepMind AlphaGo beats a human 04:28 DeepMind uses AI system AlphaTensor to search for new algorithms 05:18 A computer helps prove the four color theorem 06:17 What is a tensor? 07:16 Tensor decomposition explained 08:48 AlphaTensor discovers new and faster faster matrix multiplication algorithms 11:09 Mathematician Manuel Kauers improves on AlphaTensor's results VISIT our Website: https://www.quantamagazine.org LIKE us on Facebook:   / quantanews   FOLLOW us Twitter:   / quantamagazine   Quanta Magazine is an editorially independent publication supported by the Simons Foundation: https://www.simonsfoundation.org/ #math #AlphaTensor #matrices