Drag-and-drop data analytics
System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.
System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.
General-purpose language works for computer vision, robotics, statistics, and more.
By turning molecular structures into sounds, researchers gain insight into protein structures and create new variations.
MIT Machine Intelligence Community introduces students to nuts and bolts of machine learning.
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.
A new tool for predicting a person’s movement trajectory may help humans and robots work together in close proximity.
Streamlined system for creating and analyzing perovskite compounds may cut development time from 20 years to two.
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.
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.
In helping envision the MIT Schwarzman College of Computing, working group is focusing on ethical and societal questions.
Working group studies options for creating a new set of faculty hires for MIT’s new college.