The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.
With Style2Fab, makers can rapidly customize models of 3D-printable objects, such as assistive devices, without hampering their functionality.
The machine-learning method works on most mobile devices and could be expanded to assess other motor disorders outside of the doctor’s office.
Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.
The system could improve image quality in video streaming or help autonomous vehicles identify road hazards in real-time.
“Lightning” system connects photons to the electronic components of computers using a novel abstraction, creating the first photonic computing prototype to serve real-time machine-learning inference requests.
A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.
MIT Plasma Science and Fusion Center will receive DoE support to improve access to fusion data and increase workforce diversity.
The MIT and Accenture Convergence Initiative for Industry and Technology selects three new research projects to support.