The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.
Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.
The fellowship funds graduate studies at Stanford University.
Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.
The MIT Energy Initiative’s Spring Symposium highlights the vast potential of offshore turbines in decarbonizing the grid.
The HUMANS nanowafer, an MIT Space Exploration Initiative student-led project, will travel to the ISS this month, and later to the moon, carrying messages in more than 64 languages from over 80 countries.
The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.
The 2023 competition featured three-minute talks on cutting-edge research from across MIT in an engaging, live competition.
A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.
SoftZoo is a soft robot co-design platform that can test optimal shapes and sizes for robotic performance in different environments.
Ahead of the Institute’s presidential inauguration, panelists describe advances in their research and how these discoveries are being deployed to benefit the public.
Professor Emerita Nancy Hopkins and journalist Kate Zernike discuss the past, present, and future of women at MIT and beyond.
Faculty and researchers across MIT’s School of Engineering receive many awards in recognition of their scholarship, service, and overall excellence.
A campus summit with the leader and his delegation centered around dialogue on biotechnology and innovation ecosystems.
A new low-temperature growth and fabrication technology allows the integration of 2D materials directly onto a silicon circuit, which could lead to denser and more powerful chips.