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

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.

Photonic accelerators have been widely designed to accelerate some specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for ...

Engheta and colleagues have now set their sights on vector–matrix multiplication, which is a vital operation for the artificial neural networks used in some artificial intelligence systems. The team ...

AlphaTensor: AI system speeds up matrix multiplication with new algorithm With Deep Reinforcement Learning, DeepMind has discovered an algorithm no human thought of.

Click to expand... So you know enough to deny the possibility of: "Matrix multiplication advancement could lead to faster, more efficient AI models" It's pretty vague, but it is hardly nonsense.

It is compatible across many different compilers, languages, operating systems, linking, and threading models. In particular, the Intel MKL DGEMM function for matrix-matrix multiplication is highly ...

The matrix multiplication infix operator (*) produces a new matrix by performing matrix multiplication. The first matrix must have the same number of columns as the second matrix has rows.