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: 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: - LIKE us on Facebook: - FOLLOW us Twitter: Quanta Magazine is an editorially independent publication supported by the Simons Foundation: #math #AlphaTensor #matrices