An artificial-intelligence approach known as AlphaTensor found exact matrix-multiplication algorithms that are more efficient than those previously known for many matrix sizes. The technique ...

DeepMind breaks 50-year math record using AI; new record falls a week later AlphaTensor discovers better algorithms for matrix math, inspiring another improvement from afar.

Can artificial intelligence (AI) create its own algorithms to speed up matrix multiplication, one of machine learning’s most fundamental tasks? Today, in a paper published in Nature, DeepMind ...

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

What do encrypted messages, recognizing speech commands and running simulations to predict the weather have in common? They all rely on matrix multiplication for accurate calculations. DeepMind, an ...

Matrix multiplication is a fundamental operation in machine learning, and is one of the most time-consuming, due to the extensive use of multiply-add instructions.

Perfecting that algorithm has been the key to breakthroughs in matrix multiplication efficiency over the past century—even before computers entered the picture.

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.

The algorithm minimizes the number of multiplications for matrix multiplication without commutativity for the special cases p = 1 or 2, n = 1, 2, ⋯ and p = 3, n = 3. It is shown that commutativity ...