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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.”
Emily Reynolds reports for Wired that NASA has awarded an R5 “Valkyrie” humanoid robot to a team led by Prof. Russ Tedrake. Reynolds explains that the team “will develop algorithms to make the robot more dexterous” so that they could potentially take the place of humans during extreme space missions.
A team led by Prof. Russ Tedrake has been awarded one of NASA’s R5 “Valkyrie” robots to develop software that could allow humanoid machines to assist astronauts in space, reports Rachel Feltman for The Washington Post. Feltman writes that Tedrake’s team was awarded the robot based on its strong performance in the DARPA Robotics Challenge.
NASA has awarded two humanoid robots to research groups at MIT and Northeastern, reports Brian Mastroianni for CBS News. The robots “are seen as potential tools to aid astronauts in future Mars expeditions,” writes Mastroianni. “They could potentially assist or even replace humans in extreme environments.”
Olga Khvan reports for Boston Magazine that a team from MIT has been awarded a humanoid robot for research and development. “The R5—nicknamed Valkyrie—is a humanoid robot designed to assist during human missions to Mars by completing disaster-relief maneuvers,” writes Khvan.
A team led by Prof. Russ Tedrake has been awarded a humanoid robot from NASA to develop software for future space missions, reports Hiawatha Bray for BetaBoston. NASA is “interested in modifications that would let the machines assist human astronauts during long-duration space missions,” writes Bray.
In this video, Jim Drury of Reuters examines the new system developed by MIT researchers that enables drones to map and successfully navigate a new landscape.
In this video, BBC News reporter Stephen Beckett speaks with Prof. Dina Katabi about a new system her group developed that can track people through walls using wireless signals. “It’s using these very low-power signals, sending them, and observing the reflection of the body through the wall,” explains Prof. Dina Katabi.
Washington Post reporter Matt McFarland writes about graduate student Andrew Barry’s work developing a system that allows drones to successfully navigate obstacles. McFarland writes, “the work is significant because it shows a drone avoiding obstacles in an area that hasn’t been previously mapped.”