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 ...

Over the past decades, roboticists have introduced a wide range of advanced systems that can move around in their surroundings and complete various tasks. Most of these robots can effectively collect ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

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

Why do artificial intelligence (AI) systems struggle to accurately grasp human intent despite being trained on vast amounts ...

A new meta-learning framework inspired by how babies explore the world could help robots adapt faster, handle objects safely, and interact more naturally with humans.

Wlodkowski and Ginsberg (2018) provide a framework for enhancing learner motivation through Culturally Responsive Teaching (CRT). This approach centers on creating four key conditions that support ...

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 ...

US researchers say a deep-learning framework provides the most detailed picture yet of how utility-scale solar uses land, revealing unexpected efficiency gaps and clearer pathways for agrivoltaics and ...

A generalizable ML framework predicts protein interactions with ligand-stabilized gold nanoclusters, supporting faster design ...