Hal Hodson writes for New Scientist that MIT researchers have developed a system that allows virtual reality headsets to operate wirelessly. To solve the problem posed by sending vast amounts of data wirelessly, the researchers used a “different wireless technology called millimeter wave (mmWave), which is in a higher band of the frequency spectrum to that used by Wi-Fi.”
Researchers at MIT have created an algorithm that transforms faces and popular landmarks into scarier versions with impressionistic, sketchy qualities, according to the BBC News. To help teach the algorithm about the concept of scariness, the researchers are asking people vote for the scariest images.
Just in time for Halloween, MIT researchers have launched a website that uses algorithms to generate scary images based off of pictures of popular landmarks and public figures, reports Rebecca Hersher for NPR. The deep-learning algorithm creates “artistic images of high perceptual quality based on examples of images created by humans,” Hersher reports.
Alyssa Newcomb writes for NBC News about the Nightmare Machine, a new system developed by MIT researchers that generates scary images based off of familiar faces and locations. “The Nightmare Machine gets scarier with help from humans, who are asked to vote on which images are the scariest,” Newcomb explains.
Writing for The Huffington Post, Adi Gaskell highlights how CSAIL researchers have developed system to help robots work together successfully. Gaskell explains that the system allows three robots to “work successfully together to ensure items are delivered accurately in an unpredictable environment.”
CSAIL researchers have a developed a system that can predict human emotions by using wireless signals to monitor breathing and heartbeats, writes Edd Gent in a Scientific American article. "The idea is that you can enable machines to recognize our emotions so they can interact with us at much deeper levels," says graduate student Fadel Adib.
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.”
Howard Shrobe, head of the Cybersecurity@CSAIL initiative, discusses the possibility of creating a computer system that can’t be hacked in a CNBC article. “What we need to think about are the architectural principles that would govern secure designs,” writes Shrobe. “Memory safety errors are a key part of well over 50 percent of the vulnerabilities.”
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."
Researchers from MIT and IBM are joining forces to develop systems that enable machines to recognize images and sounds as people do, reports Hiawatha Bray for The Boston Globe. James DiCarlo, head of the Department of Brain and Cognitive Sciences, notes that as researchers build systems that can interpret events, “we learn ways our own brains might be doing that.”
Daniel Akst of The Wall Street Journal writes that by bouncing electromagnetic waves off of pages, MIT researchers have developed a way to read closed books. The system could potentially be used also be used to count stacks of money and detect counterfeit currency, Akst explains.