Artificial intelligence predicts patients’ race from their medical images
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
Living better with algorithms
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
Can artificial intelligence overcome the challenges of the health care system?
MIT and Mass General Brigham researchers and physicians connect in person to bring AI into mainstream health care.
Technique protects privacy when making online recommendations
Researchers devise an efficient protocol to keep a user’s private information secure when algorithms use it to recommend products, songs, or shows.
Peter Shor receives 2022-2023 Killian Award
The MIT professor is honored for extraordinary accomplishments in mathematics, computer science, and quantum physics.
Q&A: Chris Rackauckas on the equations at the heart of practically everything
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
How can we reduce the carbon footprint of global computing?
Workshop hosted by MIT’s Climate and Sustainability Consortium, MIT-IBM Watson AI Lab, and the MIT Schwarzman College of Computing highlights how new approaches to computing can save energy and help the planet.
Machine learning, harnessed to extreme computing, aids fusion energy development
Linking techniques from machine learning with advanced numerical simulations, MIT researchers take an important step in state-of-the-art predictions for fusion plasmas.
Estimating the informativeness of data
MIT researchers can now estimate how much information data are likely to contain, in a more accurate and scalable way than previous methods.
A new state of the art for unsupervised computer vision
MIT CSAIL scientists created an algorithm to solve one of the hardest tasks in computer vision: assigning a label to every pixel in the world, without human supervision.
Learning to think critically about machine learning
A multidisciplinary team of graduate students helps infuse ethical computing content into MIT’s largest machine learning course.
MIT’s FutureMakers programs help kids get their minds around — and hands on — AI
The programs are designed to foster an understanding of how artificial intelligence technologies work, including their social implications.
Manipulating the future
A new robotic manipulation course provides a broad survey of state-of-the-art robotics, equipping students to identify and solve the field’s biggest problems.
Robots dress humans without the full picture
MIT researchers design a robot that has a trick or two up its sleeve.
Generating new molecules with graph grammar
An efficient machine-learning method uses chemical knowledge to create a learnable grammar with production rules to build synthesizable monomers and polymers.