MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

Augmenting citizen science with computer vision for fish monitoring

MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.

MIT and Hasso Plattner Institute establish collaborative hub for AI and creativity

Jointly led by the MIT Morningside Academy for Design, MIT Schwarzman College of Computing, and the Hasso Plattner Institute in Potsdam, the hub will foster a dynamic community where computing, creativity, and human-centered innovation meet.

A better method for identifying overconfident large language models

This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.

Generative AI improves a wireless vision system that sees through obstructions

With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.

MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact

Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.

Can AI help predict which heart-failure patients will worsen within a year?

Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.

3 Questions: On the future of AI and the mathematical and physical sciences

Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.

New MIT class uses anthropology to improve chatbots

MIT computer science students design AI chatbots to help young users become more social, and socially confident.

A better method for planning complex visual tasks

A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.

Improving AI models’ ability to explain their predictions

A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.