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 ...

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 ...

Distributed computing has markedly advanced the efficiency and reliability of complex numerical tasks, particularly matrix multiplication, which is central to numerous computational applications from ...

Researchers at Harvard University and DNA Script developed an ionic circuit comprising hundreds of ionic transistors for neural net computing. While ions in water move slower than electrons in ...

The deep neural network models that power today’s most demanding machine-learning applications are pushing the limits of traditional electronic computing hardware, according to scientists working on a ...