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.
Tom Buerkle of Reuters writes about “Adaptive Markets: Financial Evolution at the Speed of Thought,” a new book written by Prof. Andrew Lo, which argues that it is possible for investors to beat the market. Markets seem unpredictable because traders are human and “make decisions using short cuts” rather than weighing all options, explains Buerkle.
In an article for Scientific American about the future of robotics, Prof. Emeritus Rodney Brooks highlights Prof. Dina Katabi’s work developing devices that use wireless signals to detect a person’s emotions.
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 report released by MIT startup Cambridge Mobile Telematics (CMT) shows that one in four drivers were using a smartphone just before an accident occurred, reports The Boston Globe’s Matt Rocheleau. Prof. Samuel Madden, founder and chief scientist at CMT, explains that the study shows “people are using their phones a lot, and that’s playing a role in the accidents.”
Daniel Akst of The Wall Street Journal writes about the wearable device developed by CSAIL researchers that can detect the emotional tone of a conversation. The researchers “are pushing the boundaries by training a computer to take account of such a wide range of factors in making judgments about emotion,” writes Akst.
Science Friday reporter Ira Flatow and Motherboard reporter Daniel Oberhaus discuss a wearable device developed by CSAIL researchers that can detect the emotional tone of a conversation. Oberhaus explains that the researchers hope the device could one day be “applied with much finer emotional granularity, to the point where you can tell if the story was exciting or funny.”
Wall Street Journal reporter Daniel Akst writes that MIT researchers have developed a way to “tap into the insight of the expert minority within a crowd—a minority whose views would otherwise be swamped in a simple majority vote or poll.” The technique significantly enhanced “the wisdom of crowds, reducing errors by more than 20%.”
BBC reporter Lorelei Mihala highlights DriveWell, an app developed by Profs. Hari Balakrishnan and Sam Madden, aimed at addressing the problem of distracted driving. “We wanted to show that smartphones could be used to make drivers better,” says Balakrishnan.
Boston Herald reporter Jordan Graham writes that the McGovern Institute has established a new center focused on autism research, thanks to a gift from Lisa Yang and Hock Tan ’75 SM ’75. Graham explains that the center will “focus on trying to make significant jumps through new technologies such as gene editing with CRISPR/Cas9.”
MIT is launching a center for autism research at the McGovern Institute with $20 million in funding from MIT alumnus Hock Tan and Lisa Yang, writes Barb Darrow for Fortune. Darrow writes that Yang told Fortune she was "greatly impressed by both the collegiality and focus of the institute's researchers.”
CSAIL researchers have developed a wearable AI system that allows users to detect the tone of a conversation in real-time, reports Janet Burns for Forbes. Using two algorithms to analyze data, the researchers were able to “classify each five-second chunk of conversation as positive, neutral, or negative,” explains Burns.
Dan Misener of CBC News writes that a wearable device developed by MIT researchers detects the tone of conversation by listening to the interaction and measuring the physiological responses of the user. “All of that data is fed into a neural network that's been trained to identify certain cues,” explains Misener.