Researchers have published research detailing their development of an AI framework to detect defects in additively ...

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 ...

EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

(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 ...

Effective task allocation has become a critical challenge for multi-robot systems operating in dynamic environments like search and rescue. Traditional methods, often based on static data and ...

Researchers from Carnegie Mellon University and partner institutions have introduced a complementarity framework for human–AI teamwork, focusing on distributing reasoning, memory, and attention ...

Contemporary academic institutions face many challenges when planning new technology or applications like hybrid learning. Overcoming resistance to change and fostering an environment that embraces ...

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 ...

Designing effective instruction starts with clarity about what you want students to learn and choosing the right methods to help them get there. The Seven Ways of Learning framework provides a ...