Training robots to manipulate soft and deformable objects
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
Will continue initiatives in academics, mentoring, and DEIJ while building on legacy of academic and scientific excellence.
SuperUROP scholars apply deep learning to improve accuracy of climate models, profitably match computers in the cloud with customers, and more.
Her research focuses on more-efficient deep neural networks to process video, and more-efficient hardware to run applications.
Researchers propose a method for finding and fixing weaknesses in automated programming tools.
With technology new and old, instructors try to recreate the interactivity of their pre-Covid classroom.
Leveraging research done on campus, student-run MIT Driverless partners with industry collaborators to develop and test autonomous technologies in real-world racing scenarios.
New building will create a hub for computing research and education at MIT, including spaces designed to be inviting to members of the campus community and the public.
In two years, the MIT Quest for Intelligence has allowed hundreds of students to explore AI in its many applications.
Brain and cognitive sciences professor will lead the Institute’s interdisciplinary initiative to advance research in natural and artificial intelligence.
EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.
Researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors.
Adding a module that mimics part of the brain can prevent common errors made by computer vision models.
Working remotely this summer, students worked to better understand human intelligence and to advance machine learning applications.
Researchers train a model to reach human-level performance at recognizing abstract concepts in video.