Seeing sounds
Mariano Salcedo, a master’s student in the new Music Technology and Computation Graduate Program, is designing an AI to visualize and express music and other sounds.
Mariano Salcedo, a master’s student in the new Music Technology and Computation Graduate Program, is designing an AI to visualize and express music and other sounds.
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.
MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.
The Institute also ranks second in seven subject areas.
The portable “ChromoLCD” device combines LCD and LED lighting to customize high-quality designs onto things like shirts and whiteboards.
With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.
This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.
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.
One year in, MIT’s hands-on 6-5 (Electrical Engineering With Computing) degree program is already one of the most popular majors among first-year students.
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.
Light-emitting structures that curl off the chip surface could enable advanced displays, high-speed optical communications, and larger-scale quantum computers.
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.