Recent research has employed chemical reaction networks (CRNs), which harness biochemical processes for computations that translate interactions involving biochemical species into graphical form.

A new study utilizes compact neural networks to uncover the underlying mechanisms behind human decision-making. Scientists have long studied how people and animals make decisions, often looking at how ...

Mechanistic interpretability is emerging as a strategic advantage for businesses looking to deploy AI responsibly.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

Discover how Google DeepMind is using video games and generative AI to train advanced artificial intelligence for real-world applications.

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

"We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture ... to test ...

New research highlights how astrocytes, long considered mere support cells, actively shape brain network dynamics.

Long overlooked and underestimated, glial cells—non-neuronal cells that support, protect and communicate with neurons—are ...

The dynamic neural network (DNN), in contrast to the static counterpart, offers numerous advantages, such as improved accuracy, efficiency, and interpretability. These benefits stem from the network’s ...

Neuromorphic computing, as a novel approach to processing information by mimicking biological neural networks, has gradually demonstrated significant ...

Using the analogy of the interconnected neural pathways in the brain, network leadership is about harnessing connections to ...