For the second time, scientists have detected gravitational waves produced by the collision of two black holes, reports Irene Klotz for Reuters. “We are starting to get a glimpse of the kind of new astrophysical information that can only come from gravitational-wave detectors,” says David Shoemaker, who leads Advanced LIGO.
In an article for New Scientist, Lisa Grossman writes that for the second time the Laser Interferometer Gravitational Wave Observatory (LIGO) has detected gravitational waves. “This gives us confidence,” says MIT research scientist Salvatore Vitale. “It was not just a lucky accident. Seeing a second one tells us clearly that there is a population of black holes there.”
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.”
TIME reporter Jeffrey Kluger writes that MIT researchers have designed an algorithm to produce an image of a black hole. Kluger explains that the algorithm will allow researchers “visualize the event horizon that surrounds the black hole at the center of our own galaxy.”
MIT graduate student Katie Bouman speaks with Ben Johnson of Marketplace about the algorithm she and her colleagues developed to allow people “to see the first image of a black hole.” Johnson notes the algorithm has uses beyond space exploration and could also potentially be used for MRI imaging.
MIT researchers have developed a new algorithm to compile data gathered by the Event Horizon Telescope and create an image of a black hole, reports James Griffiths for CNN. The algorithm will “fill in the gaps and filter out the interference and noise caused by our own atmosphere,” Griffiths explains.
Washington Post reporter Brian Fung writes that MIT researchers have developed an algorithm to create images of black holes by compiling data from radio telescopes around the world. Fung writes that the algorithm “could give us the first true images of a celestial phenomenon that, for decades, we've left to artists to imagine and describe with pictures.”
An algorithm developed by MIT researchers could help produce the first image of a black hole, reports Ryan Mandelbaum for Popular Science. Mandelbaum explains that the algorithm gathers data from radio telescopes around the globe and then uses “other images from space as references to craft a sort of mosaic that best matches the data from the telescopes.”
Boston Globe reporters J.D. Capelouto and Olivia Arnold write that MIT researchers have developed an algorithm aimed at producing images of black holes. MIT graduate student Katie Bouman notes that while there are predictions of what a black hole might look like, “it’s great to actually be able to probe it and…construct those images.”
A new analysis by MIT researchers verifies the difficulty of the popular video game “Super Mario Brothers.” MIT researchers found that the game’s challenges belong to the “PSPACE” category of equations, “requiring exponential time to both solve, and to prove algorithmically,” G. Clay Whittaker of Popular Science explains.
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.
Wired reporter Brian Barrett writes that MIT researchers have developed a new system to help detect cyber-attacks. Barrett explains that the system, “reviews data…and pinpoints anything suspicious. A human takes it from there, checking for signs of a breach. The one-two punch identifies 86 percent of attacks while sparing analysts the tedium of chasing bogus leads.”
Prof. Emilio Frazzoli speaks with Nicole Dungca of The Boston Globe about his new startup nuTonomy, which is developing a fleet of driverless taxis for Singapore. Frazzoli explains that he feels the biggest impact of autonomous vehicles is in “really changing the way we think of personal mobility, or mobility, in general.”