A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher. Artificial neurons—the fundamental building blocks of deep neural networks—have survived almost ...

We’re told neural networks ‘learn’ the way humans do. A neuroscientist explains why that’s not the case — and why AI can't think like us yet.

Neuroscientists are finding that deep-learning networks, often criticized as “black boxes,” can be good models for the organization of living brains.

A simulation that uses machine learning predicts neural-circuit function in the fly brain from the connectivity between neurons.

These networks could be powerful and lightweight, so people could use them with smaller electronic devices. And in time, we could have neural networks operating nearly everywhere.

Such networks are being used in chemistry and drug discovery as well, for example to predict the binding affinities of proteins and ligands based on their structures. In combination with a technique ...

Research from the University of Texas regarding neural networks suggests an exciting path for uniting deep learning and symbolic reasoning AI.