Can robots learn from machine dreams?
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
A new design tool uses UV and RGB lights to change the color and textures of everyday objects. The system could enable surfaces to display dynamic patterns, such as health data and fashion designs.
Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.
The MIT Human Insight Collaborative will elevate the human-centered disciplines and unite the Institute’s top scholars to help solve the world’s biggest challenges.
Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.
Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.
By emulating a magnetic field on a superconducting quantum computer, researchers can probe complex properties of materials.
The new Tayebati Postdoctoral Fellowship Program will support leading postdocs to bring cutting-edge AI to bear on research in scientific discovery or music.
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.
“MouthIO” is an in-mouth device that users can digitally design and 3D print with integrated sensors and actuators to capture health data and interact with a computer or phone.
By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.