Science

A new framework uses AI agents to automate and accelerate the process of materials discovery through computational experiments.

Researchers have developed a novel neural network framework that separates stable visual processing from dynamic adaptation, offering a more accurate and efficient approach to understanding how the brain interprets the world.

A new framework automatically generates diverse robotic tasks and datasets, enabling policies trained in simulation to perform reliably in the real world.

Researchers demonstrate a community-driven framework for ethically integrating artificial intelligence into Hawaiian language assessment, balancing psychometric rigor with cultural preservation.

A new pilot study explores whether tailoring an exoskeleton’s movement to an individual’s natural gait significantly improves the user experience during rehabilitation training.

A new study confirms the reliable performance of artificial intelligence models in assessing prostate cancer biopsies from a Middle Eastern cohort, offering a path towards more equitable healthcare access.

Researchers have developed a novel imitation learning framework that enables robots to more effectively learn complex manipulation tasks by aligning observations and actions in a consistent 3D space.

A new analysis reveals that current medical imaging AI competitions often fail to assess algorithms fairly due to biased datasets and limited data access.

New research details a deep learning system enabling autonomous drones to reliably navigate the complex and challenging environments of dense forests.

Researchers have developed a rigorous, testable framework to move beyond intuitive notions of explainability and formally verify why AI models make the decisions they do.