TU Wien researchers tested six frontier LLMs by leaving them without any tasks or instructions. Some models built structured ...

Researchers at Seoul National University and Kyung Hee University report a framework to control collective motions, such as ring, clumps, mill, flock, by training a physics-informed AI to learn the ...

As the global energy landscape rapidly transforms, the integration of distributed energy resources (DERs)—such as photovoltaic (PV) systems, energy storage ...

Young workers should develop their "learning skills" so they can adapt to the job market's needs, Cambridge professor Thomas ...

In January I wrote a piece titled “ 5 Physics Equations Everyone Should Know .” Lots of you weighed in with your own ...

High-entropy materials (HEMs) have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability, enhanced ionic conductivity, ...

Amid high expectations for quantum technology, a new paper in Science reports a proven quantum advantage. In an experiment, ...

New research program seeks ‘energy-aware’ ML that balances performance with power draw It's notoriously difficult to consistently measure the energy usage of AI models, but DARPA wants to put an end ...

Learn how Tongyi DeepResearch combines cutting-edge reasoning and open-source flexibility to transform advanced research ...

The development of low-cost high-entropy alloys is promising to address the demands of expanding industrial applications. In the present research, Co-free FeNiCr medium-entropy alloys were prepared by ...

Abstract: The challenge of the exploration-exploitation dilemma persists in off-policy reinforcement learning (RL) algorithms, impeding the improvement of policy performance and sample efficiency. To ...

Abstract: In this paper, we investigate a cooperative edge caching problem in the fog radio access networks (F-RANs). In order to obtain the globally optimal caching strategy that minimizes the ...