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 ...

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 ...

For instance, one study presented a blocked matrix multiplication implementation that leverages the Intel AVX-512 extensions, achieving remarkable performance on the Intel Knights Landing (KNL ...

Example Of Muliplying Two 2x2 Matrixes AlphaTensor is an AI model based on AlphaZero which is tasked with discovering algorithms to solve arbitrary matrix multiplication problems.

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 ...

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 ...

Matrix multiplication is a fundamental operation in machine learning, and is one of the most time-consuming, due to the extensive use of multiply-add instructions.

A simple matrix formula is given for the observed information matrix when the EM algorithm is applied to categorical data with missing values. The formula requires only the design matrices, a matrix ...

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, ...

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