Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.

Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.

With support from the Stone Foundation, the center will advance cutting-edge research and inform policy.

The CausVid generative AI tool uses a diffusion model to teach an autoregressive (frame-by-frame) system to rapidly produce stable, high-resolution videos.

“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

A new book coauthored by MIT’s Dimitris Bertsimas explores how analytics is driving decisions and outcomes in health care.

New type of “state-space model” leverages principles of harmonic oscillators.

A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.

New phase will support continued exploration of ideas and solutions in fields ranging from AI to nanotech to climate — with emphasis on educational exchanges and entrepreneurship.

Using diagrams to represent interactions in multipart systems can provide a faster way to design software improvements.