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Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research School of Engineering

New technique makes AI models leaner and faster while they’re still learning

Researchers use control theory to shed unnecessary complexity from AI models during training, cutting compute costs without sacrificing performance.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Electronics machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability

Helping data centers deliver higher performance with less hardware

Researchers developed a system that intelligently balances workloads to improve the efficiency of flash storage hardware in a data center.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment machine learning Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant National Science Foundation (NSF) Oceanography and ocean engineering Research School of Engineering Undergraduate Research Opportunities Program (UROP) Video Volunteering, outreach, public service Water

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.

Artificial Intelligence Data Health Care Institute for Medical Engineering and Science (IMES) Medicine Research School of Engineering Technology and society

How to create “humble” AI

An MIT-led team is designing artificial intelligence systems for medical diagnosis that are more collaborative and forthcoming about uncertainty.

Artificial Intelligence Awards, honors and fellowships Business and management Data Faculty MIT Sloan School of Management Office of Open Learning Operations research Provost Special events and guest speakers

On algorithms, life, and learning

Operations research expert Dimitris Bertsimas delivered the annual Killian Lecture, providing a look at the past and future of his work.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Electronics Imaging machine learning Media Lab MIT Schwarzman College of Computing National Science Foundation (NSF) Research Robotics School of Architecture and Planning School of Engineering sensors Wireless

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.

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Harvard-MIT Health Sciences and Technology Health Care Health sciences and technology Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing Research Research Laboratory of Electronics School of Engineering

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.

Algorithms Artificial Intelligence Astronomy and astrophysics chemistry Computer science and technology Data Faculty IDSS Interview Laboratory for Nuclear Science machine learning Materials science and engineering Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Physics Research School of Science

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.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Research School of Engineering

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.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Energy machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research Research Laboratory of Electronics School of Engineering

New method could increase LLM training efficiency

By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.