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Displaying 1 - 15 of 53 news clips related to this topic.


CNN reporter Ivana Kottasová writes that a new study co-authored by MIT researchers finds there has been a significant drop in CFC emissions and a resumption in the recovery of the ozone layer. Prof. Ronald Prinn, director of the Center for Global Change Science at MIT, said that the results were “tremendously encouraging,” adding that “global monitoring networks really caught this spike in time, and subsequent actions have lowered emissions before they became a real threat to recovery of the ozone layer.”


Paul Carter of BBC’s Click highlights CSAIL research to teach a robot how to feel an object just by looking at it. This will ultimately help the robot “grip better when lifting things like the handle of a mug,” says Carter.


Using a tactile sensor and web camera, MIT researchers developed an AI system that allows robots to predict what something feels like just by looking at it, reports David Williams for CNN. “This technology could be used to help robots figure out the best way to hold an object just by looking at it,” explains Williams.


Forbes contributor Charles Towers-Clark explores how CSAIL researchers have developed a database of tactile and visual information that could be used to allow robots to infer how different objects look and feel. “This breakthrough could lead to far more sensitive and practical robotic arms that could improve any number of delicate or mission-critical operations,” Towers-Clark writes.


MIT researchers have created a new system that enables robots to identify objects using tactile information, reports Darrell Etherington for TechCrunch. “This type of AI also could be used to help robots operate more efficiently and effectively in low-light environments without requiring advanced sensors,” Etherington explains.

Fast Company

Fast Company reporter Michael Grothaus writes that CSAIL researchers have developed a new system that allows robots to determine what objects look like by touching them. “The breakthrough could ultimately help robots become better at manipulating objects,” Grothaus explains.

WCAI Radio

Prof. Muriel Médard speaks with WCAI’s Living Lab Radio about the potential impact of 5G technologies on a number of industries. “If one can count on reliable services that allow remote operation of certain aspects of our work lives,” Médard explains, “that's where you change the way people work quite a bit.”

Technology Review

Technology Review reporter Will Knight spotlights how MIT researchers have developed a new chip that is many times more efficient than silicon chips and could help bring AI to a multitude of devices where power is limited. “We need new hardware because Moore’s law has slowed down,” explains Prof. Vivienne Sze.

Boston Globe

Using video to processes shadows, MIT researchers have developed an algorithm that can see around corners, writes Alyssa Meyers for The Boston Globe. “When you first think about this, you might think it’s crazy or impossible, but we’ve shown that it’s not if you can understand the physics of how light propagates,” says lead author and MIT graduate Katie Bouman.


CSAIL researchers have developed a system that detects objects and people hidden around blind corners, writes Anthony Cuthbertson for Newsweek. “We show that walls and other obstructions with edges can be exploited as naturally occurring ‘cameras’ that reveal the hidden scenes beyond them,” says lead author and MIT graduate Katherine Bouman.

New Scientist

MIT researchers have developed a new system that can spot moving objects hidden from view by corners, reports Douglas Heaven for New Scientist. “A lot of our work involves finding hidden signals you wouldn’t think would be there,” explains lead author and MIT graduate Katie Bouman. 


Wired reporter Matt Simon writes that MIT researchers have developed a new system that analyzes the light at the edges of walls to see around corners. Simon notes that the technology could be used to improve self-driving cars, autonomous wheelchairs, health care robots and more.  


Prof. Mohammad Alizadeh and his colleagues "have developed a way to approach network monitoring that provides flexibility in data collection while still keeping both the circuit complexity of the router and the number of external servers low," writes Amy Wallace for UPI


CSAIL researchers have developed an artificial intelligence system that can reduce video buffering, writes Kevin Murnane for Forbes. The system, “adapts on the fly to current network and buffers conditions,” enabling smoother streaming than other methods.   


CSAIL researchers have developed an artificial neural network that generates recipes from pictures of food, reports Laurel Dalrymple for NPR. The researchers input recipes into an AI system, which learned patterns “connections between the ingredients in the recipes and the photos of food,” explains Dalrymple.