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.
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.
A multidisciplinary team of graduate students helps infuse ethical computing content into MIT’s largest machine learning course.
The programs are designed to foster an understanding of how artificial intelligence technologies work, including their social implications.
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.
MIT researchers design a robot that has a trick or two up its sleeve.
An efficient machine-learning method uses chemical knowledge to create a learnable grammar with production rules to build synthesizable monomers and polymers.
Brent Minchew leads two proposals to better understand glacial physics and predict sea-level rise as part of MIT's Climate Grand Challenges competition.
Associate professor and principal investigator with the MIT Schwarzman College of Computing’s Science Hub discusses the future of robotics and the importance of industry-academia collaborations.
“Privid” could help officials gather secure public health data or enable transportation departments to monitor the density and flow of pedestrians, without learning personal information about people.
Researchers design a user-friendly interface that helps nonexperts make forecasts using data collected over time.
Researchers have developed a technique for making quantum computing more resilient to noise, which boosts performance.
CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.
The AI-Guided Ultrasound Intervention Device is a lifesaving technology that helps a range of users deliver complex medical interventions at the point of injury.
MLK Visiting Professor S. Craig Watkins looks beyond algorithm bias to an AI future where models more effectively deal with systemic inequality.
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.