Bringing meaning into technology deployment
The MIT Ethics of Computing Research Symposium showcases projects at the intersection of technology, ethics, and social responsibility.
The MIT Ethics of Computing Research Symposium showcases projects at the intersection of technology, ethics, and social responsibility.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
The system automatically learns to adapt to unknown disturbances such as gusting winds.
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.
The approach could help animators to create realistic 3D characters or engineers to design elastic products.
Researchers developed an algorithm that lets a robot “think ahead” and consider thousands of potential motion plans simultaneously.
A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.
SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans.
The fellowships recognize doctoral students who have “the extraordinary creativity and principled leadership necessary to tackle problems others can’t solve.”
PhD student Sarah Alnegheimish wants to make machine learning systems accessible.
Through collaborations with organizations like BREIT in Peru, the MIT Institute for Data, Systems, and Society is upskilling hundreds of learners around the world in data science and machine learning.
Ground-level ozone in North America and Western Europe may become less sensitive to cutting NOx emissions. The opposite may occur in Northeast Asia.
This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.