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.
Scott Clement of The Washington Post writes that researchers at the Laboratory for Social Machines have found that while the majority of Twitter conversation concerning the presidential campaign has centered around Donald Trump over the past week and a half, “battlegrounds differed in what particular issues or themes they focused on.”
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.”
Dr. Mallika Marshall reports for CBS Boston that MIT researchers have created a robot that helps maternity nurses make scheduling and placement decisions. “What we found was that the suggestions of the robot were accepted 90 percent of the time, which was very exciting for us,” explains Prof. Julie Shah.
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.
A new device developed by MIT researchers can read the pages of a book without opening the cover, reports Nsikan Akpan for the PBS NewsHour. The tool may “unlock the secrets of old books or ancient texts too fragile to be disturbed by human touch.”
MIT researchers have developed a system that uses terahertz waves to read the pages of a closed book, reports Michael Casey for the AP. Research scientist Barmak Heshmat explains that the system works better than X-rays, as “it can contrast between the blank paper and the part that has ink.”
Writing for CBS News, Charles Choi explores a system developed by MIT researchers that can identify letters in a closed book. The system could be used to examine ancient books or to “scan through large amounts of documents without having to mechanically separate the pages, which could be useful for libraries, banks and others,” says research scientist Barmak Heshmat.
Salon reporter Scott Eric Kaufman writes that MIT researchers have created a system that can read the pages of a closed book and could be used to examine manuscripts too fragile to handle. “The system works by shooting pulses of radiation from a terahertz camera and measuring how long it takes for them to bounce back."
MIT researchers have developed a new computational imaging technique that can read closed books, reports G. Clay Whittaker for Popular Science. The technique could be useful for “rare book research, where opening a book may be impossible due to damage, or not worth the risk of damage.”
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.
Gabrielle DiBenedetto writes for Boston Magazine that researchers from MIT CSAIL have developed a robot that can help nurses schedule tasks. DiBenedetto writes that the robot “learns how to perform the scheduling job similarly to how a human would: through observation.”
CSAIL researchers recently presented an algorithm that teaches computers to predict sounds, writes Kevin Hartnett for The Boston Globe. The ability to predict sounds will help robots successfully navigate the world and “make sense of what’s in front of them and figure out how to proceed,” writes Hartnett.