Boston Herald reporter Jordan Graham writes about the MIT team working to develop a Hyperloop transportation system. “The Hyperloop would be a system of near-vacuum tubes that sends levitating pods from one place to another at 760 miles per hour,” Graham explains.
MIT researchers have developed an algorithm that can predict the memorability of images with human-like accuracy, reports Adrienne Lafrance for The Atlantic. The researchers explained that their work demonstrates that “predicting human cognitive abilities is within reach for the field of computer vision.”
Scott Eisen of the Associated Press explores a new motion-tracking device developed by MIT researchers that can detect movement using wireless signals. "It's a sensor that can monitor people and allow you to control devices just by pointing at them," explains graduate student Fadel Adib.
Boston.com reporter Megan McGinnes writes that MIT researchers are developing software that can predict how well people will remember certain images. Users of the new software “can feed images into the database, which are then overlaid with a heat map to show regions of the photo viewers are most likely to remember.”
CSAIL researchers have developed an algorithm that can predict the memorability of an image with near-human accuracy, reports Curt Woodward for BetaBoston. Woodward explains that “the technology could be used to make learning materials more memorable and advertising pitches more effective.”
Prof. Donald Sadoway speaks with Miles O’Brien of the PBS NewsHour about how designing better batteries could help make renewable energy more feasible. “The issue is that we don’t have a battery technology that can meet the rigorous performance requirements of the grid, namely, super low-cost and super long service lifetime,” explains Sadoway.
Dana Guth reports for Boston Magazine on a new bandage developed by Prof. Xuanhe Zhao that can deliver medication directly to a wound. “The bandage is filled with tiny pathways, so that drugs can flow through its gel-like material, providing relief for burns and other minor skin conditions,” writes Guth.
Boston Herald reporter Jessica Van Sack writes that Grove, an MIT startup dedicated to enabling people to grow their own produce, will award five of its indoor garden/fish tank systems to local schools. “When you have a full ecological system, it becomes more than just planting seeds and watching them grow,” explains co-founder Gabe Blanchet.
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.”
BetaBoston reporter Elizabeth Preston writes that MIT graduate students are explaining complex aerospace engineering topics to a class of fifth grader students in Georgia. Teacher Alana Davis says of the MIT students that, “I don’t think they realize what a difference they’re making in these kids’ lives.”
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.”
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.”