A new design tool uses UV and RGB lights to change the color and textures of everyday objects. The system could enable surfaces to display dynamic patterns, such as health data and fashion designs.

Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.

Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.

Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.

Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.

By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.

A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.

Collaborative multi-university team will pursue new AI-enhanced design tools and high-throughput testing methods for next-generation turbomachinery.

A new study of bubbles on electrode surfaces could help improve the efficiency of electrochemical processes that produce fuels, chemicals, and materials.

MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.