MIT researchers develop an efficient way to train more reliable AI agents
The technique could make AI systems better at complex tasks that involve variability.
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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.
Four from MIT named 2025 Rhodes Scholars
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
A launchpad for entrepreneurship in aerospace
The Certificate in Aerospace Innovation gives students the tools and confidence to be aerospace entrepreneurs during an inflection point in the industry.
Bridging Talents and Opportunities Forum connects high school and college students with STEAM leaders and resources
Event at MIT featured an array of national and international speakers including a Nobel laureate, leaders in industry, and in entertainment.
Finding a sweet spot between radical and relevant
As he invents programmable materials and self-organizing systems, Skylar Tibbits is pushing design boundaries while also solving real-world problems.
Brains, fashion, alien life, and more: Highlights from the Cambridge Science Festival
Organized by the MIT Museum, the 2024 celebration of science, technology, and culture was the largest in its history, with over 50,000 visitors at 300 events.
A faster, better way to train general-purpose robots
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.
Combining next-token prediction and video diffusion in computer vision and robotics
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.
How AI is improving simulations with smarter sampling techniques
MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.
AI pareidolia: Can machines spot faces in inanimate objects?
New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.
Helping robots zero in on the objects that matter
A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.
MIT students combat climate anxiety through extracurricular teams
The MIT Electric Vehicle Team, Sustainable Engine Team, Solar Electric Vehicle Team, Motorsports Team, First Nations Launch Team, and Arcturus are each doing their part to improve the health of our planet.
First AI + Education Summit is an international push for “AI fluency”
The three-day, hands-on conference hosted by the MIT RAISE Initiative welcomed youths and adults from nearly 30 countries.
Engineering and matters of the heart
Professor Ellen Roche is creating the next generation of medical devices to help repair hearts, lungs, and other tissues.