South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

Microsoft Research has developed a new reinforcement learning framework that trains large language models for complex reasoning tasks at a fraction of the usual computational cost. The framework, ...

How should students use AI in the classroom? This question keeps coming up in every conversation about AI in education. And most of the answers fall into two unhelpful camps: ban it completely or let ...

(a) An illustrative map for Crack-Net, including the initial features, looping solver for data generation, model training, and prediction performance. (b) The Crack-Net architecture, which utilizes ...

As the use of Unmanned Aerial Vehicles (UAVs) expands across various fields, there is growing interest in leveraging Federated Learning (FL) to enhance the efficiency of UAV networks. However, ...

Physical learning environments (PLEs)—including classrooms, schools, and networks of facilities—play a critical role in shaping educational outcomes. The World Bank’s RIGHT+ framework offers guidance ...