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 ...

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

Researchers at MIT's Computer Science & Artificial Intelligence Lab (CSAIL) have open-sourced Multiply-ADDitioN-lESS (MADDNESS), an algorithm that speeds up machine learning using approximate matrix m ...

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 ...

The standard “back-propagation” training technique for deep neural networks requires matrix multiplication, an ideal workload for GPUs. With SLIDE, Shrivastava, Chen and Medini turned neural network ...

The company revealed on 5 October that its AI software had beaten a record that had stood for more than 50 years for the matrix multiplication problem – a common operation in all sorts of ...

Oct 06, 2022 11:20:00 The strongest shogi AI reaches new ground, DeepMind's AI 'AlphaTensor' succeeds in improving the matrix multiplication algorithm that has been stagnant for over 50 years ...