Machine learning for everyone
A new EECS course on applications of machine learning teaches students from a variety of disciplines about one of today’s hottest topics.
Teaching artificial intelligence to create visuals with more common sense
An MIT/IBM system could help artists and designers make quick tweaks to visuals while also helping researchers identify “fake” images.
Drag-and-drop data analytics
System lets nonspecialists use machine-learning models to make predictions for medical research, sales, and more.
New AI programming language goes beyond deep learning
General-purpose language works for computer vision, robotics, statistics, and more.
Translating proteins into music, and back
By turning molecular structures into sounds, researchers gain insight into protein structures and create new variations.
Want to learn how to train an artificial intelligence model? Ask a friend.
MIT Machine Intelligence Community introduces students to nuts and bolts of machine learning.
From one brain scan, more information for medical artificial intelligence
System helps machine-learning models glean training information for diagnosing and treating brain conditions.
Teaching artificial intelligence to connect senses like vision and touch
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
Toward artificial intelligence that learns to write code
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
Algorithm tells robots where nearby humans are headed
A new tool for predicting a person’s movement trajectory may help humans and robots work together in close proximity.
How to speed up the discovery of new solar cell materials
Streamlined system for creating and analyzing perovskite compounds may cut development time from 20 years to two.
Chip design drastically reduces energy needed to compute with light
Simulations suggest photonic chip could run optical neural networks 10 million times more efficiently than its electrical counterparts.
Preliminary reports examine options for MIT Schwarzman College of Computing
Working groups identify key ideas for new college; period of community feedback continues.
A 3-D printer powered by machine vision and artificial intelligence
MIT startup Inkbit is overcoming traditional constraints to 3-D printing by giving its machines “eyes and brains.”
Cracking open the black box of automated machine learning
Interactive tool lets users see and control how automated model searches work.