With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

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High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers continually ...

The 'algorithm for calculating the matrix product' that AlphaTensor worked on this time is used in various fields related to daily life, such as image processing, game graphics processing, weather ...

The new version of AlphaZero discovered a faster way to do matrix multiplication, a core problem in computing that affects thousands of everyday computer tasks. DeepMind has used its board-game ...

In 1971, German mathematicians Schönhage and Strassen predicted a faster algorithm for multiplying large numbers, but it remained unproven for decades. Mathematicians from Australia and France have ...

New lower values for p get discovered all the time (maybe once a year). It is conjectured that they will approach 2.0 without ever getting quite to it. Somehow Quanta Mag heard about the new result ...

AI training time is at a point in an exponential where more throughput isn't going to advance functionality much at all. The underlying problem, problem solving by training, is computationally ...