Artificial intelligence grows more demanding every year. Modern models learn and operate by pushing huge volumes of data through repeated matrix operations that sit at the heart of every neural ...

There has been an ever-growing demand for artificial intelligence and fifth-generation communications globally, resulting in very large computing power and memory requirements. The slowing down or ...

Researchers in China published a paper describing a theoretical model for photonic computing that used light particles instead of electrons for faster processing. The team developed “parallel optical ...

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 ...

Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...

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 ...