The neural networks infer two basic types of local interaction rules: distance-based rules that set spacing, velocity-based rules that align headings, as well as their combination. The team also ...

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 network ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

Neuro-symbolic AI — combining data-driven learning with rule-based reasoning — could accelerate safe, transparent use of autonomous equipment on complex jobsites.

It might be futile to try making machines that are fully human. Our abilities have been refined through a lengthy evolution.