These neural networks know what they’re doing
A certain type of artificial intelligence agent can learn the cause-and-effect basis of a navigation task during training.
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A certain type of artificial intelligence agent can learn the cause-and-effect basis of a navigation task during training.
A deep model was trained on historical crash data, road maps, satellite imagery, and GPS to enable high-resolution crash maps that could lead to safer roads.
Researchers find blind and sighted readers have sharply different takes on what content is most useful to include in a chart caption.
Secure AI Labs, founded by alumna Anne Kim and MIT Professor Manolis Kellis, anonymizes data for AI researchers.
Awards support high-risk, high-reward biomedical and behavioral research.
MIT App Inventor’s “Appathon” joins programmers from around the world to imagine a better future and start building it one app at a time.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
An AI-enhanced system enables doctors to spend less time searching for clinical information and more time treating patients.
An electrical impedance tomography toolkit lets users design and fabricate health and motion sensing devices.
MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.
Advance incorporates sensing directly into an object’s material, with applications for assistive technology and “intelligent” furniture.
MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.
ARROW, a reconfigurable fiber optics network developed at MIT, aims to take on the end of Moore’s law.
MIT offers over 120 undergraduate classes related to sustainability, a sign of growing student and faculty interest in the environmental impacts of their fields.