The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...