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 ...

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 ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural ...

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

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Many of today’s leading AI systems are recurrent neural networks . This deep-learning method uses past information to improve performance on current and future inputs, But AI memory problem ...

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.