Seeing sounds
Mariano Salcedo ’25, 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.
Source: MIT News
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Mariano Salcedo ’25, 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.
Source: MIT News
An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.
Source: MIT News
This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.
Source: MIT News
MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.
Source: MIT News
By moving their hands and fingers, users can direct a robot to play piano or shoot a basketball, or they can manipulate objects in a virtual environment.
Source: MIT News
An MIT-led team is designing artificial intelligence systems for medical diagnosis that are more collaborative and forthcoming about uncertainty.
Source: MIT News
Sojun Park, a postdoc at the Center for International Studies, has learned much from his research on intellectual property as well as his interactions with students and mentors at MIT.
Source: MIT News
Operations research expert Dimitris Bertsimas delivered the annual Killian Lecture, providing a look at the past and future of his work.
Source: MIT News
Conference speakers discussed the unfolding trajectory of AI and the benefits of shaping technology to meet people’s needs.
Source: MIT News
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-cent
Source: MIT News
With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.
Source: MIT News
This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.
Source: MIT News
At MIT, former U.S. ambassador to China Nicholas Burns highlights climate change as an area for diplomatic engagement, while exploring areas including China's emphasis on STEM education.
Source: MIT News
Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.
Source: MIT News
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.
Source: MIT News
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.
Source: MIT News
MIT computer science students design AI chatbots to help young users become more social, and socially confident.
Source: MIT News
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Source: MIT News
Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.
Source: MIT News
From early motion-sensing platforms to environmental monitoring, the professor and head of the Program in Media Arts and Sciences has turned decades of cross-disciplinary research into real-world impact.
Source: MIT News
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
Source: MIT News
The approach could help engineers tackle extremely complex design problems, from power grid optimization to vehicle design.
Source: MIT News
Lincoln Laboratory intern Ivy Mahncke developed and tested algorithms to help human divers and robots navigate underwater.
Source: MIT News
By leveraging idle computing time, researchers can double the speed of model training while preserving accuracy.
Source: MIT News