A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern some of the most complex dynamics found in nature and technology.

To create models that can identify the inner workings of complex biological systems, the researchers turned to a type of model known as a probabilistic graphical network. These models represent each ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

In a new paper from OpenAI, the company proposes a framework for analyzing AI systems' chain-of-thought reasoning to understand how, when, and why they misbehave.

The original version of this story appeared in Quanta Magazine. A few centuries ago, the swirling polychromatic chaos of Jupiter’s atmosphere spawned the immense vortex that we call the Great Red Spot ...

In a new study, scientists have investigated the pervasive low-rank hypothesis in complex systems, demonstrating that despite high-dimensional nonlinear dynamics, many real networks exhibit rapidly ...

The landscape of artificial intelligence is undergoing a significant transformation. As the capabilities of large language models grow, we are beginning to see a shift away from isolated ...

Today’s electronic systems are an increasingly complex combination of hardware and software components. They contain an ever-expanding range of functions, require more computing power, have to operate ...

Heavy machinery is entering a new phase where hydraulics, electronics and embedded software are engineered as one integrated system. Using model-based systems engineering (MBSE) as a framework to ...

3D illustration of a DNA molecule with sparkling effects symbolizing complexity and genetic diversity. Futuristic concept of genomics, precision medicine, and computational life sciences. If you’ve ...