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 ...

Sparse matrices underpin a vast range of scientific and engineering applications, from finite element analysis and computational fluid dynamics to graph processing and machine learning. By encoding ...

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 ...

Optical computing uses photons instead of electrons to perform computations, which can significantly increase the speed and energy efficiency of computations by overcoming the inherent limitations of ...

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 ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...