Climate & Sustainability Researchers run high-performing large language model on the energy needed to power a lightbulb UC Santa Cruz researchers show that it is possible to eliminate the most ...

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.

By using this method, the amount of multiplication required for matrix operations can be significantly reduced, so the paper states that it ``opens the door to new hardware designs for large-scale ...

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

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network ...

Researchers are developing language models that can manage without memory-intensive matrix multiplications and still compete with modern transformers.

DeepMind’s paper also pointed out that AlphaTensor discovers a richer space of matrix multiplication algorithms than previously thought — up to thousands for each size.