Enabling small language models to solve complex reasoning tasks
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
MIT neuroscientists find a surprising parallel in the ways humans and new AI models solve complex problems.
Industry leaders agree collaboration is key to advancing critical technologies.
Professors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.
Media Lab PhD student Kimaya Lecamwasam researches how music can shape well-being.
Department of Mathematics researchers David Roe and Andrew Sutherland seek to advance automated theorem proving; four additional MIT alumni also awarded.
At the inaugural MIT Generative AI Impact Consortium Symposium, researchers and business leaders discussed potential advancements centered on this powerful technology.
The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.