Second round of seed grants awarded to MIT scholars studying the impact and applications of generative AI
The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.
The 16 finalists — representing every school at MIT — will explore generative AI’s impact on privacy, art, drug discovery, aging, and more.
Screen-reader users can upload a dataset and create customized data representations that combine visualization, textual description, and sonification.
With help from a large language model, MIT engineers enabled robots to self-correct after missteps and carry on with their chores.
Researchers demonstrate a technique that can be used to probe a model to see what it knows about new subjects.
Global Semiconductor Alliance’s Women’s Leadership Initiative provides inspiration and guidance to MIT students.
Novel method makes tools like Stable Diffusion and DALL-E-3 faster by simplifying the image-generating process to a single step while maintaining or enhancing image quality.
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
At the MIT Quantum Hackathon, a community tackles quantum computing challenges.
MIT CSAIL postdoc Nauman Dawalatabad explores ethical considerations, challenges in spear-phishing defense, and the optimistic future of AI-created voices across various sectors.
A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination.
In class 2.679 (Electronics for Mechanical Systems II) a hands-on approach provides the skills engineers use to create and solve problems.
Northeast Microelectronics Coalition Hub funding will expand the reach of the Northeast Microelectronics Internship Program for first- and second-year college students.
By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.
Faster and more accurate than some alternatives, this approach could be useful for robots that interact with humans or work in tight spaces.
Professor Ernest Fraenkel has decoded fundamental aspects of Huntington’s disease and glioblastoma, and is now using computation to better understand amyotrophic lateral sclerosis.