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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.
Prof. Anantha Chandrakasan, dean of the School of Engineering, speaks with Meera Vankipuram of The Times of India about his research, his areas of focus as dean and what sets MIT apart. Chandrakasan explains that at MIT, there is an “emphasis on translating research into solutions that have a positive impact on the world.”
During this NECN segment, Boston Business Journal reporter Kelly O’Brien discusses the new wireless sleep detection device developed by CSAIL researchers. The algorithm developed by the research team can translate radio waves emitted by the device “into usable information about where a person is in their sleep cycle,” explains O’Brien.
TechCrunch reporter Brian Heater spotlights a new device developed by MIT researchers that can wirelessly monitor sleep. “Thanks to new AI technology, the system is now able to translate subtle movement into meaningful information about the subject’s sleep patterns, including sleep stages (light/deep/R.E.M.), movement and breathing rate."
MIT researchers have developed a new device that can track sleep patterns using radio waves, reports Alyssa Meyers for The Boston Globe. The researchers plan to “use the device to study how Parkinson’s disease affects sleep,” Meyers explains, adding that it could also be helpful with, “studying Alzheimer’s disease, insomnia, sleep apnea, and epilepsy.”
Wired reporter Liz Stinson writes that researchers from MIT and Google have developed a new algorithm that can automatically retouch images on a mobile phone. “The neural network identifies exactly how to make it look better—increase contrast a smidge, tone down brightness, whatever—and apply the changes in under 20 milliseconds,” Stinson explains.
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.
A team of researchers from MIT and Princeton participating in the Amazon Robotics Challenge are using GelSight technology to give robots a sense of touch, reports Tom Simonite for Wired. Simonite explains that the, “rubbery membranes on the robot’s fingers are tracked from the inside by tiny cameras as they are deformed by objects it touches.”
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.”
MIT researchers have developed a new way to grow liver tissue, writes Jamie Ducharme for Boston Magazine. “These minuscule structures expanded to 50 times their starting size,” Ducharme explains, “and performed normal liver functions like metabolism regulation, bile production, and detoxification.”
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 engineered an expandable liver from human liver cells that can grow up to 50 times its original size, reports Lindsay Kalter for the Boston Herald. In the future, the researchers would like to make the expandable livers smarter, “by embedding sensors in them to tell us how they are doing,” explains Prof. Sangeeta Bhatia.
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.
MIT researchers have developed a new way to engineer liver tissue that involves implanting tiny “seeds” of liver tissue, which expand to perform normal liver functions, reports Robert Preidt for U.S. News & World Report. The technique could one day “help reduce long wait lists for liver transplants.”