Science

New research demonstrates how equipping AI with causal reasoning capabilities dramatically improves the reliability and accuracy of medical evidence synthesis.

This review explores the development and application of movement primitives, a powerful technique enabling robots to learn complex skills from human demonstrations.

As large language models evolve, the focus is shifting toward creating AI systems capable of independent planning, action, and problem-solving.

Researchers have developed a new system where robots use visual sketches to plan and execute complex, long-duration tasks with improved reliability and interpretability.

A new approach uses artificial intelligence to automate and refine the complex process of modeling combustion, accelerating scientific progress.

Researchers have developed a deep reinforcement learning framework that enables teams of robots to efficiently and robustly explore unfamiliar environments.

Researchers have developed a new artificial intelligence architecture that models cellular processes by integrating genomic, transcriptomic, and proteomic data in a biologically inspired manner.

A new study explores how interactive, AI-powered robots are helping non-Chinese speaking students overcome language barriers and build confidence in Cantonese.

A new unified artificial intelligence model demonstrates the power of cross-disciplinary learning, achieving top results in diverse fields from weather prediction to medical image analysis.

New research details a framework for human-robot teams to collaborate on complex assembly tasks, bridging the gap between visual understanding and coordinated action.