MIT CSAIL researchers develop advanced machine-learning models that outperform current methods in detecting pancreatic ductal adenocarcinoma.

A multimodal system uses models trained on language, vision, and action data to help robots develop and execute plans for household, construction, and manufacturing tasks.

MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.

MIT researchers introduce a method that uses artificial intelligence to automate the explanation of complex neural networks.

This new method draws on 200-year-old geometric foundations to give artists control over the appearance of animated characters.

MIT researchers develop a customized onboarding process that helps a human learn when a model’s advice is trustworthy.

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

MIT CSAIL researchers established new connections between combinatorial and continuous optimization, which can find global solutions for complex motion-planning puzzles.

Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.

By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.