The confluence of medicine and artificial intelligence stands to create truly high-performance, specialized care for patients, with enhanced precision diagnosis and personalized disease management.

MIT researchers have now designed a sharp-tipped robot finger equipped with tactile sensing to meet the challenge of identifying buried objects. In experiments, the aptly named Digger Finger was able to dig through granular media such as sand and rice, and it correctly sensed the shapes of submerged items it encountered.

Robotic arm equipped with a hairbrush helps with brushing tasks and could be an asset in assistive-care settings. 

A study from MIT shows how coronavirus skeptics have marshalled data visualizations online to argue against public health orthodoxy about the benefits of mask mandates. Such “counter-visualizations” are often quite sophisticated, using datasets from official sources and state-of-the-art visualization methods.

Antonio Torralba, faculty head of Artificial Intelligence and Decision Making within the Department of Electrical Engineering and Computer Science (EECS) and the Thomas and Gerd Perkins Professor of Electrical Engineering and Computer Science, has been selected as a 2021 Fellow by the Association for the Advancement of Artificial Intelligence (AAAI).

A team led by researchers from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) has developed an approach that they say can make texturing even less tedious, to the point where you can snap a pic of something you see in a store, and then go recreate the material on your home laptop

In a new paper, a team led by MIT computer scientists trained a neural network to learn NASCAR-style driving maneuvers purely from looking at a sequence of images taken from a two-person racing game. The network begins without knowing anything about cars, roads, or driving - and yet ultimately becomes able to do complex moves like overtaking an opponent on a turn and even forcing other cars off the road.