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MIT researchers have created an algorithm that can identify what traits make an image memorable, reports Matt McFarland for The Washington Post. The algorithm could prove useful in developing educational tools as “textbooks and teaching aids could start to use visual aids that have been proven to stick in our heads,” McFarland 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.”
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.”
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.”
Prof. Scott Aaronson speaks with New Scientist reporter Jacob Aron about Google’s D-Wave quantum computer. “This is certainly the most impressive demonstration so far of the D-Wave machine’s capabilities,” says Aaronson. “And yet, it remains totally unclear whether you can get to what I’d consider ‘true quantum speedup’ using D-Wave’s architecture.”
Emma Woollacott reports for Forbes on Vuvuzela, a text-messaging system that MIT researchers developed to encrypt the metadata and content of messages. “Vuvuzela uses multiple servers instead of one, to give each message multiple layers of encryption,” writes Woollacott.
Writing for The Boston Globe, Nancy Shohet West highlights Prof. Erik Demaine and Martin Demaine’s paper sculptures, which are on display at the Concord Center for the Visual Arts. “We started getting interested a number of years ago in curve creases and what was possible mathematically,” explains Prof. Demaine. “We started making models and then turned those into sculpture.”