Matrix multiplication requires that the number of columns (p) in the left matrix (A) equal the number of rows (p) in the right matrix (B). Otherwise, this algorithm won’t work.

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, ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

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

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 this way, researchers have discovered new algorithms that multiply n-by-n matrices using fewer than the standard n 3 multiplication steps for many small matrix sizes. But algorithms that outperform ...

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 ...