By watching TV shows and video clips, CSAIL researchers show that artificially intelligent systems can learn and predict human behavior, writes Tim Moynihan for Wired. Researchers say these findings could lead to analyzing hospital video feeds to alert emergency responders or allow robots to respond.
CSAIL researchers used videos of popular TV shows to train an algorithm to predict how two people will greet one another. “[T]he algorithm got it right more than 43 percent of the time, as compared to the shoddier 36 percent accuracy achieved by algorithms without the TV training,” notes Janet Burns in Forbes.
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.
In an article for Wired, Tim Moynihan writes that a team of CSAIL researchers has created a machine-learning system that can produce sound effects for silent videos. The researchers hope that the system could be used to “help robots identify the materials and physical properties of an object by analyzing the sounds it makes.”
Writing for the Financial Times, Clive Cookson reports that MIT researchers have developed an artificial intelligence system capable of producing realistic sounds for silent movies. Cookson explains that another application for the system could be “to help robots understand objects’ physical properties and interact better with their surroundings."
Washington Post reporter Matt McFarland writes that MIT researchers have created an algorithm that can produce realistic sounds. “The findings are an example of the power of deep learning,” explains McFarland. “With deep learning, a computer system learns to recognize patterns in huge piles of data and applies what it learns in useful ways.”
Popular Science reporter Mary Beth Griggs writes that MIT researchers have developed an algorithm that can learn how to predict sound. The algorithm “can watch a silent movie and create sounds that go along with the motions on screen. It's so good, it even fooled people into thinking they were actual, recorded sounds from the environment.”
Prof. Andrew Lo writes for The Wall Street Journal that robo advisors could prove helpful to investors if they are able to assist with managing emotions. “Instead of artificial intelligence, we should first conquer artificial emotion—by constructing algorithms that accurately capture human behavior, we can build countermeasures to protect us from ourselves."
Boston.com reporter Sanjay Salomon writes about how “Duckietown,” a model city developed by MIT researchers, could help make self-driving cars a reality. “We realized if you scale down autonomous driving to something very small there’s lots of research to do on a smaller scale with none of the logistical challenges of real autonomous vehicle research,” explains postdoc Liam Paull.
Professors Edward Boyden and Max Tegmark are honored as “Game Changers” in a Boston Globe special section dedicated to highlighting people and organizations for their work. The Globe features Boyden’s work developing tools to better understand the brain, and Tegmark’s involvement in the Future of Life Institute.
WBUR’s Bruce Gellerman speaks with Prof. Carlo Ratti and research scientist Bryan Reimer about the potential impact of driverless cars on everything from traffic to the economy. Reimer says using autonomous vehicles will change, “how we move. It changes how packages are moved. It changes how we behave. It changes the future of old age. It changes everything.”
Popular Science reporter Mary Beth Griggs writes that in an MIT course students developed a fleet of duckie-adorned self-driving taxis for a village called “Duckietown.” “Each of the robot taxis is equipped with only a single camera, and makes its way around the roads without any preprogrammed maps."
MIT researchers have developed an artificial intelligence platform that uses input from human analysts to predict cyber-attacks, reports Brian Mastroianni for CBS News. “We realized, finding the actual attacks involved a mix of supervised and unsupervised machine-learning,” explains research scientist Kalyan Veeramachaneni.