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 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.
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.
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.
In this video for USA Today, Sean Dowling highlights Pic2Recipe, the artificial intelligence system developed by CSAIL researchers that can predict recipes based off images of food. The researchers hope the app could one day be used to help, “people track daily nutrition by seeing what’s in their food.”
Researchers at MIT have developed an algorithm that can identify recipes based on a photo, writes BBC News reporter Zoe Kleinman. The algorithm, which was trained using a database of over one million photos, could be developed to show “how a food is prepared and could also be adapted to provide nutritional information,” writes Kleinman.
MIT researchers have developed a new machine learning algorithm that can look at photos of food and suggest a recipe to create the pictured dish, reports Matt Reynolds for New Scientist. Reynolds explains that, “eventually people could use an improved version of the algorithm to help them track their diet throughout the day.”
CSAIL researchers have trained an AI system to look at images of food, predict the ingredients used, and even suggest recipes, writes Matt Burgess for Wired. The system could also analyze meals to determine their nutritional value or “manipulate an existing recipe to be healthier or to conform to certain dietary restrictions," explains graduate student Nick Hynes.
Boston Magazine reporter Jamie Ducharme writes that CSAIL researchers have developed a device that can measure walking speed using wireless signals. The device can “also measure stride length, which may come in handy when studying conditions that are characterized by small steps, such as Parkinson’s disease.”
A new system developed by MIT researchers can predict how a scene will unfold, similar to how humans can visually imagine the future, reports Ed Gent for Scientific American. Graduate student Carl Vondrick explains that the system is “an encouraging development in suggesting that computer scientists can imbue machines with much more advanced situational understanding."