The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.

A new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.

A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

Study finds non-experts deferred to LLM-based diagnostic assistance, even when it was wrong, while clinicians caught AI errors.

An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.

Researchers developed an automated framework that helps AI models generate CAD programs more accurately and efficiently.

Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.

“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.

MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.