Undergraduates explore practical applications of artificial intelligence
SuperUROP scholars apply deep learning to improve accuracy of climate models, profitably match computers in the cloud with customers, and more.
MIT Quest for Intelligence
Q&A: Vivienne Sze on crossing the hardware-software divide for efficient artificial intelligence
Her research focuses on more-efficient deep neural networks to process video, and more-efficient hardware to run applications.
Toward deep-learning models that can reason about code more like humans
Researchers propose a method for finding and fixing weaknesses in automated programming tools.
Retrofitting MIT’s deep learning “boot camp” for the virtual world
With technology new and old, instructors try to recreate the interactivity of their pre-Covid classroom.
Driving on the cutting edge of autonomous vehicle tech
Leveraging research done on campus, student-run MIT Driverless partners with industry collaborators to develop and test autonomous technologies in real-world racing scenarios.
Design progresses for MIT Schwarzman College of Computing building on Vassar Street
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.
An intro to the fast-paced world of artificial intelligence
In two years, the MIT Quest for Intelligence has allowed hundreds of students to explore AI in its many applications.
James DiCarlo named director of the MIT Quest for Intelligence
Brain and cognitive sciences professor will lead the Institute’s interdisciplinary initiative to advance research in natural and artificial intelligence.
Professor Antonio Torralba elected 2021 AAAI Fellow
EECS faculty head of artificial intelligence and decision making honored for significant and extended contributions to the field of AI.
Want cheaper nuclear energy? Turn the design process into a game
Researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors.
Neuroscientists find a way to make object-recognition models perform better
Adding a module that mimics part of the brain can prevent common errors made by computer vision models.
MIT undergraduates pursue research opportunities through the pandemic
Working remotely this summer, students worked to better understand human intelligence and to advance machine learning applications.
Toward a machine learning model that can reason about everyday actions
Researchers train a model to reach human-level performance at recognizing abstract concepts in video.
Face-specific brain area responds to faces even in people born blind
Study finds that the fusiform face area is active when blind people touch 3D models of faces.
Rewriting the rules of machine-generated art
An artificial intelligence tool lets users edit generative adversarial network models with simple copy-and-paste commands.