Google’s AlphaEvolve AI, its latest coding agent for algorithm discovery, has improved on a 56-year-old algorithm for matrix multiplication. “Provided with a minimal code skeleton for a computer ...

For decades, Strassen’s algorithm was the gold standard for ... This could lead to more advanced LLMs, which rely heavily on matrix multiplication to function. According to DeepMind, these ...

The system designed a novel gradient-based optimization procedure that discovered multiple new matrix multiplication algorithms. One discovery toppled a mathematical record that had stood for 56 ...

One of the standout features of nvmath-python is its ability to fuse epilog operations with matrix multiplication. Epilogs are operations that can be integrated with mathematical computations such as ...

“Matrix multiplication (MatMul) typically dominates the overall computational cost of large language models (LLMs). This cost only grows as LLMs scale to larger embedding dimensions and context ...

Matrix multiplication (MatMul) is a fundamental operation in most neural networks, primarily because GPUs are highly optimized for these computations. Despite its critical role in deep learning, ...

Photonic innovation: researchers in the US have created an optical metamaterial that can perform vector–matrix multiplication. (Courtesy: iStock/Henrik5000) A new silicon photonics platform that can ...

The O(parameter count) complexity in the algorithms mean that you have to make the matrices exponentially bigger to get incremental improvement.

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 day for a variety ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in ...