Anyone exploring technological advances in artificial intelligence (AI) will inevitably encounter spiking neural networks (SNNs) — the next step toward energy‑efficient real‑time AI. The difference ...

A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers at Sandia National Lab. Abstract “The finite element method (FEM) is one of ...

The growing energy use of AI has gotten a lot of people working on ways to make it less power hungry. One option is to develop processors that are a better match to the sort of computational needs of ...

Innatera says its new chip, Pulsar, can lower latency to as little as one-one-hundredth that of conventional processors and consume only one-five-hundredth the power they use for artificial ...

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...