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 method can physically restore original paintings using digitally constructed films, which can be removed if desired.
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.
Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.
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.
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.
This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.
Researchers are developing algorithms to predict failures when automation meets the real world in areas like air traffic scheduling or autonomous vehicles.
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.