Teaching AI models what they don’t know
A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.
A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.
With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.
SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans.
Courses on developing AI models for health care need to focus more on identifying and addressing bias, says Leo Anthony Celi.
Researchers redesign a compact RNA-guided enzyme from bacteria, making it an efficient editor of human DNA.
PhD student Sarah Alnegheimish wants to make machine learning systems accessible.
This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.
Researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling or autonomous vehicles.
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.