MIT computer scientists have developed a program that can predict how objects will move with the same accuracy as humans, reports Mary Beth Griggs for Popular Science. The researchers hope to eventually be able to program the system to “make predictions in the natural world even faster than we can.”
An AI system created by MIT researchers can predict how physical objects move through the world with human-like accuracy, reports Curt Woodward for BetaBoston. “Where humans learn to make such judgments intuitively, we essentially had to teach the system each of these properties,” explains postdoc Ilker Yildirim.
In an article for The Boston Globe’s special section about the 2015 Bostonians of the Year, Sharon Begley writes about the work of Prof. Feng Zhang. Begley writes that Zhang, "is one of the world’s most creative and influential biological engineers, able to see possibilities where others don’t.”
Lindsay Holmes writes for The Huffington Post about Koko, an application developed by MIT researchers to help users fight stress by crowdsourcing their questions and worries. “We want to take the same principles that keep our eyes glued to Facebook and Instagram 24 hours a day and redirect them to promote well-being,” explains founder Robert Morris.
MIT researchers have identified a link between reduced neurotransmitter activity and the symptoms of autism, reports Carolyn Gregoire for The Huffington Post. The findings “may pave the way for new methods of treating and diagnosing” autism.
MIT researchers have identified the region of the brain that perceives music, reports Emily Reynolds for Wired. The researchers found that one area of the brain “responded most to music, another to speech, and the other four to different acoustic properties such as pitch and frequency.”
Huffington Post reporter Lila Shapiro speaks with Robert Desimone, director of the McGovern Institute, about the use of the CRISPR gene-editing technique to treat neurological diseases. “CRISPR’s impact is potentially across the board,” says Desimone. “It went from nothing just a few years ago to being a tool that’s in everyone’s toolbox.”
A new learning program developed by researchers from MIT, NYU and the University of Toronto imitates the way humans learn, according to EFE. The researchers aim to “reduce the difference in learning capability between humans and machines.”
Researchers from MIT, NYU and the University of Toronto have created a learning program that can grasp new concepts just like humans do, reports Will Dunham for Reuters. “Judges found the work produced by the computers to be virtually indistinguishable from that of human subjects,” explains Dunham.
A new advance in machine learning allows a computer program to recognize and draw handwritten characters based off a few examples, reports John Markoff for The New York Times. Markoff explains that the “improvements are noteworthy because so-called machine-vision systems are becoming commonplace in many aspects of life.”
Joel Achenbach reports for The Washington Post on the new program developed by researchers from MIT, NYU and the University of Toronto that can learn by example, a characteristic of human learning. Prof. Joshua Tenenbaum explains that the new system has made “a significant advance in capturing the way that people are thinking about these concepts.”
Los Angeles Times reporter Amina Khan writes that researchers have developed a program that learns to recognize and draw handwritten characters based off a few examples. Prof. Joshua Tenenbaum explains that the system, “can learn a large class of visual concepts in ways that are hard to distinguish from human learners.”
Kelly Servick writes for Science about Prof. Rosalind Picard’s work developing wearable technology that monitors and manages a user’s stress levels. “It’s one thing to study all this,” says Picard. “It’s another to build it into a form that people can start changing their lives around.”
Hilary Brueck writes for Fortune that researchers from MIT, NYU and the University of Toronto have developed a new technique that allows machines to learn in a more human-like manner. The new technique “comes one step closer to getting machines to learn new things in a one-shot manner, more like humans do.”
Researchers have developed a learning program that can recognize handwritten characters after seeing only a few examples, reports Emily Chung for CBC News. The program “could lead to computers that are much better at speech recognition — especially recognizing uncommon words — or classifying objects and behaviour for businesses or the military.”