Popular Science reporter Dave Gershgorn writes that MIT researchers have developed a new system that cuts down on the amount of time it takes for webpages to load. The system allows browsers to download web pages "more effectively, saving up to 34 percent of load time.”
CSAIL researchers have developed a new system that allows websites to load 34 percent faster than with a standard web browser, reports Charlotte Wilder for Boston.com. Wilder writes that, “the researchers tried out their code on 200 different websites, including Weather.com and ESPN, and found the load time was significantly less across the board.”
Wired reporter Emily Reynolds writes that researchers from MIT CSAIL have developed a new communication system that is designed to help humans and robots work together in emergency situations. The new system reduces the needs for communication by 60 percent, reducing the potential for information overload.
Boston.com reporter Hilary Sargent writes that MIT researchers have developed a new device that could help guide the visually impaired. Sargent explains that a prototype system the researchers developed “is about the size of a binoculars case and is designed to be worn around someone’s neck.”
Boston Magazine reporter Kyle Clauss reports that researchers from MIT CSAIL have developed a drone that uses algorithms to detect obstacle-free regions in space. “Using free-space segments is a more ‘glass-half-full’ approach that works far better for drones in small, cluttered spaces,” says MIT alumnus Benoit Landry.
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.”