The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.

The new approach “nudges” existing climate simulations closer to future reality.

Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.

With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.

Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.

FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.

Joining three teams backed by a total of $75 million, MIT researchers will tackle some of cancer’s toughest challenges.

Software allows scientists to model shapeshifting proteins in native cellular environments.

By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.

MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.