This could lead to more advanced LLMs, which rely heavily on matrix multiplication to function. According to DeepMind, these feats are just the tip of the iceberg for AlphaEvolve.

MatMul Matrix multiplication is a fundamental operation in deep learning, where it is used to combine data and weights in neural networks.

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 ...

Matrix multiplication advancement could lead to faster, more efficient AI models At the heart of AI, matrix math has just seen its biggest boost "in more than a decade.” ...

Multiplication facts typically describe the answers to multiplication sums up to 10x10. They are called “facts” as it is expected they can be easily and quickly recalled.

neural networks AI Reveals New Possibilities in Matrix Multiplication Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old math ...

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 ...

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 ...

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 ...

With Deep Reinforcement Learning, DeepMind has discovered an algorithm no human thought of. It is supposed to significantly accelerate matrix multiplication.