Brainstorming energy-saving hacks on Satori, MIT’s new supercomputer
Three-day hackathon explores methods for making artificial intelligence faster and more sustainable.
Three-day hackathon explores methods for making artificial intelligence faster and more sustainable.
Doctoral candidate Natalie Lao wants to show that anyone can learn to use AI to make a better world.
As natural language processing techniques improve, suggestions are getting speedier and more relevant.
To help the region catch up, students organize summit to bring Latin policymakers and researchers to MIT.
New tool highlights what generative models leave out when reconstructing a scene.
MIT and IBM researchers offer a new method to train and run deep learning models more efficiently.
Commercial cloud service providers give artificial intelligence computing at MIT a boost.
Nearly $12 million machine will let MIT researchers run more ambitious AI models.
Two longtime friends explore how computer vision systems go awry.
A course that combines machine learning and health care explores the promise of applying artificial intelligence to medicine.
An MIT/IBM system could help artists and designers make quick tweaks to visuals while also helping researchers identify “fake” images.
General-purpose language works for computer vision, robotics, statistics, and more.
Researchers combine deep learning and symbolic reasoning for a more flexible way of teaching computers to program.
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.