Uncommon Courses is an occasional series from The Conversation U.S. highlighting unconventional approaches to teaching.

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

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 ...

The language capabilities of today's artificial intelligence systems are astonishing. We can now engage in natural ...

Throughout their everyday lives, humans are typically required to make a wide range of decisions, which can impact their well ...

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

GREmLN leverages a graph-based architecture to represent gene-gene interactions to predict cell behavior for therapeutic ...

Researchers have created over 400 distinct types of human nerve cells in vitro, vastly expanding the diversity available for ...

The brain doesn't merely register time—it structures it, according to new research from the Kavli Institute for Systems ...

The latest generative AI models such as OpenAI's ChatGPT-4 and Google's Gemini 2.5 require not only high memory bandwidth but also large memory capacity. This is why generative AI cloud operating ...

Complex networks articles from across Nature Portfolio Complex networks are networks that feature patterns of connection between their elements that are neither purely regular nor purely random.

Network models articles from across Nature Portfolio Network models are a computer architecture, implementable in either hardware or software, meant to simulate biological populations of ...