Researchers from MIT CSAIL have developed an algorithm that allows drones to navigate obstacle courses, reports Kelsey Atherton for Popular Science. “As drones move away from simple remote-controlled toys and become more autonomous flying tools, programs like these will keep them flying safely through unfamiliar terrain,” explains Atherton.
MIT researchers have developed an algorithm that could reduce how long planes wait before takeoff, reports Lee Moran for The Huffington Post. The formula allows air traffic controllers to use data on weather conditions and runway traffic to “hold airplanes at the gate, which would help avoid congestion.”
Cade Metz writes for Wired that MIT researchers have developed a system that allows robots to predict how objects will move. Postdoc Ilker Yildirim explains that in order for a robot to be able to assist with household tasks like washing the dishes, it must “deeply understand its physical environments.”
MIT researchers have developed a microscope that can generate close to real-time images on nanoscale processes, reports Kevin Hartnett for The Boston Globe. The microscope allows “microscopic worlds that had appeared static suddenly leap into motion,” Hartnett explains.
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.
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.”
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.”
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.”
In this video, CBS Boston’s Bree Sison reports on MIT startup Affectiva, which is developing technology that can identify human emotions and could help with mental health. Rana el Kaliouby, Affectiva CSO and co-founder, explains that the technology could “tell you something is off, or flag it to a friend or doctor. Or maybe it could customize a digit experience to help you.”
In an article for Optics.org, Matthew Peach writes that MIT researchers have developed a technique that exploits the polarization of light to improve the quality of 3-D imaging. The technique “could lead to high-quality 3-D cameras integrated into cellphones, and perhaps to the ability to photograph an object and then use a 3-D printer to produce a replica.”
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.