To encourage safer driving in Boston, Mayor Martin Walsh has announced a competition that uses a smartphone app developed by MIT startup Cambridge Telematics to reward driver performance, reports Dante Ramos for The Boston Globe. The app gives motorists “star ratings if they stay off their phones; drive at reasonable speeds; and brake, accelerate, and turn carefully.”
CSAIL researcher have created a device that uses changes in heart beat and breathing to detect emotions, writes Forbes’ Kevin Murnane. The heart of the system,” writes Murnane, “is the algorithm that extracts the heartbeat from the RF signal. It’s an impressive achievement that solves a difficult problem.”
A device created by CSAIL researchers can detect emotions by wirelessly measuring heartbeats, according to the Associated Press. The device is “87 percent accurate in using heartrate and what it’s already learned about a person to recognize joy, pleasure, sadness or anger.”
CSAIL researchers have developed a device that can determine a person’s mood using wireless signals, write Jordan Graham and Donna Goodison for The Boston Herald. “We view this work as the next step in helping develop computers that can better understand us at an emotional level,” explains Mingmin Zhao.
CSAIL researchers have developed a device that can determine emotion by analyzing reflections from wireless signals bounced off the human body, writes Mary Beth Griggs for Popular Science. “Because it can measure heart rate, it might also be a less invasive way for doctors to monitor patient's heartbeats, potentially watching for conditions like arrhythmias,” writes Griggs.
Matt McFarland writes for CNN that CSAIL researchers have developed a non-invasive device that uses radio waves to detect human emotion. "Imagine if the machines around you can understand when you are stressed or your emotional state is negative,” explains Prof. Dina Katabi."[It could] try to detect depression."
In a study of students offered $100 in bitcoin, MIT researchers found that early users were more likely to not use new technology if there were delays in accessing it, writes Kevin Lewis for The Boston Globe. The researchers found early adopters, “were more likely to cash out of their bitcoin if they had been delayed in getting it.”
MIT researchers have developed a new algorithm to create videos from still images, writes G. Clay Whittaker for Popular Science. “The system "learns" types of videos (beach, baby, golf swing...) and, starting from still images, replicates the movements that are most commonly seen in those videos,” Whittaker explains.
Writing for The New York Times, Katie Hafner highlights how MIT researchers have identified a region of the brain that they believe could be responsible for producing feelings of loneliness. Hafner explains that “the region, known as the dorsal raphe nucleus, or D.R.N., is best known for its link to depression.”
In an article for The Boston Globe, Kevin Hartnett explores a study co-authored by Prof. Danny Fox that examines why children confuse the words “and” and “or.” The researchers found that “children may conduct exactly the same logical process as adults, but arrive at different conclusions because they run that process over a narrower set of alternative sentences.”
Inside Higher Ed reporter Colleen Flaherty writes that researchers from MIT and around the world are publicly defending the late Prof. Suzanne Corkin’s work with patient H.M. in response to a highly critical publication. When “so many scholars rise to defend the reputation of a deceased colleague,” says Arthur Caplan, head of NYU’s Division of Bioethics, “that speaks volumes both about her and the problems that exist in the book.”
Mary Beth Griggs writes for Popular Science that CSAIL researchers have created an algorithm that can predict human interaction. Griggs explains that the algorithm could “lead to artificial intelligence that is better able to react to humans or even security cameras that could alert authorities when people are in need of help.”
Dan Misener writes for CBC News that CSAIL researchers have developed an algorithm that can predict interactions between two people. PhD student Carl Vondrick explains that the algorithm is "learning, for example, that when someone's hand is outstretched, that means a handshake is going to come."
CSAIL researchers have trained a deep-learning program to predict interactions between two people, writes Hope King for CNN. “Ultimately, MIT's research could help develop robots for emergency response, helping the robot assess a person's actions to determine if they are injured or in danger,” King explains.
CBC News reporter Paul Cote Jay writes about a new study co-authored by MIT researchers that examines why children often have trouble distinguishing the words “or” from “and.” Jay explains that the researchers found that while adults and children go through a similar process to interpret statements, “children are just missing one step.”