Finding a good read among billions of choices
As natural language processing techniques improve, suggestions are getting speedier and more relevant.
Students push to speed up artificial intelligence adoption in Latin America
To help the region catch up, students organize summit to bring Latin policymakers and researchers to MIT.
Visualizing an AI model’s blind spots
New tool highlights what generative models leave out when reconstructing a scene.
Faster video recognition for the smartphone era
MIT and IBM researchers offer a new method to train and run deep learning models more efficiently.
What a little more computing power can do
Commercial cloud service providers give artificial intelligence computing at MIT a boost.
IBM gives artificial intelligence computing at MIT a lift
Nearly $12 million machine will let MIT researchers run more ambitious AI models.
Why did my classifier just mistake a turtle for a rifle?
Two longtime friends explore how computer vision systems go awry.
Want to know what software-driven health care looks like? This class offers some clues.
A course that combines machine learning and health care explores the promise of applying artificial intelligence to medicine.
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.
New AI programming language goes beyond deep learning
General-purpose language works for computer vision, robotics, statistics, and more.
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.
Q&A: Phillip Isola on the art and science of generative models
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Teaching language models grammar really does make them smarter
Researchers submit deep learning models to a set of psychology tests to see which ones grasp key linguistic rules.
Smarter training of neural networks
MIT CSAIL project shows the neural nets we typically train contain smaller “subnetworks” that can learn just as well, and often faster.
Improving security as artificial intelligence moves to smartphones
Researchers unveil a tool for making compressed deep learning models less vulnerable to attack.