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 operations ...

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 ...

Researchers from the USA and China have presented a new method for optimizing AI language models. The aim is for large language models (LLMs) to require significantly less memory and computing power ...

With AlphaTensor, DeepMind Technologies has presented an AI system that is supposed to independently find novel, efficient and provably correct algorithms for complex mathematical tasks. AlphaTensor ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.

The elementwise multiplication operator (#) produces a new matrix with elements that are the products of the corresponding elements of matrix1 and matrix2. In addition to multiplying conformable ...