Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...

Researchers in China have developed a reconfigurable intelligent surface (RIS) that harvests energy from enemy radar.

Superconductors sit at the heart of some of the most ambitious technologies on the horizon, from lossless power grids to ...

Abstract: Image-goal navigation (ImageNav) tasks a robot with autonomously exploring an unknown environment and reaching a location that visually matches a given target image. While prior works ...

It’s not about robots in labs anymore someone just bought a thousand of them.” This has recently become the message that has resonated throughout the world’s robotics community, as received recently ...

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to language for AI because it’s relatively easy to learn and has a massive library of ...

The study, titled Reinforcement Learning for Monetary Policy Under Macroeconomic Uncertainty: Analyzing Tabular and Function ...

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.

1 School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA. 2 Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA. As cloud ...