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 ...

In DeepMind’s new algorithm, dubbed AlphaTensor, the inputs represent steps along the way to a valid matrix multiplication scheme. The first input to the neural network is the original matrix ...

Enter the Matrix. It may seem like an obscure problem, but matrix multiplication is a fundamental computational operation. It’s incorporated into a large proportion of the algorithms people use every ...

The algorithm is able to re-discover older matrix multiplication algorithms and improve upon its own to discover newer and faster algorithms. “AlphaTensor is the first AI system for discovering novel, ...

Matrix multiplication advancement could lead to faster, ... They break down large matrix problems into smaller segments and solve them concurrently using an algorithm.

Tensor for matrix multiplication and algorithms: here multiplication of 2 x 2 matrices. Entries equal to 1 are purple, 0 entries are semi-transparent.

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

In getting rid of matrix multiplication and running their algorithm on custom hardware, the researchers found that they could power a billion-parameter-scale language model on just 13 watts, about ...

Google DeepMind's AlphaEvolve AI system breaks a 56-year-old mathematical record by discovering a more efficient matrix multiplication algorithm that had eluded human mathematicians since Strassen ...