From one brain scan, more information for medical artificial intelligence
System helps machine-learning models glean training information for diagnosing and treating brain conditions.
System helps machine-learning models glean training information for diagnosing and treating brain conditions.
System automatically writes optimized algorithms to encrypt data in Google Chrome browsers and web applications.
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
Lincoln Laboratory's technique to protect commodity software from cyberattacks has transitioned to industry and will soon be available as part of a security suite.
Program creates a new hub for pedagogy and research in time-based media.
Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.
Working groups identify key ideas for new college; period of community feedback continues.
Fleet of “roboats” could collect garbage or self-assemble into floating structures in Amsterdam’s many canals.
Speakers — all women — discuss everything from gravitational waves to robot nurses.
Interactive tool lets users see and control how automated model searches work.
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.
Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.
In helping envision the MIT Schwarzman College of Computing, working group is focusing on ethical and societal questions.