Popular Science reporter Mary Beth Griggs writes that in an MIT course students developed a fleet of duckie-adorned self-driving taxis for a village called “Duckietown.” “Each of the robot taxis is equipped with only a single camera, and makes its way around the roads without any preprogrammed maps."
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 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.”
Alvar Saenz-Otero, director of the Space Systems Laboratory, speaks with WGBH Radio’s Edgar Herwick about the problem of space debris. Otero and his team are “refining a system that would enable a spacecraft to match the spin of a piece of space junk, capture it, and haul it out of orbit.”
Richard Waters of The Financial Times reports that Toyota is funding new research centers at MIT and Stanford to research technologies that could enable computer-assisted driving. Waters explains that the goal behind the new centers is to give “drivers the choice one day of handing over full control to the AI ‘brains’ in their vehicles.”
Toyota has announced that it is funding new research centers at MIT and at Stanford dedicated to developing “intelligent” cars, reports John Markoff for The New York Times. “We see this as basic computer science, A.I. and robotics that will make a difference in transportation,” explains Prof. Daniela Rus.
A new center at MIT, a collaborative effort with Toyota, will be focused on broadening artificial intelligence technologies for cars, writes Eric Adams for Popular Science. Prof. Daniela Rus explains that the MIT center will dedicated to “helping reduce traffic casualties, and potentially even helping us develop a vehicle incapable of getting into a collision.”
Toyota is partnering with MIT and Stanford to research autonomous-vehicle technology, reports Marco della Cava for USA Today. “Toyota will use its MIT and Stanford investment dollars to develop on-board systems that will improve an automobile's ability to make smart driving decisions in split seconds when the driver is either unaware or too slow.”
Nidhi Subbaraman of BetaBoston reports on how MIT researchers have developed a fleet of self-driving golf carts. “The group road-tested a fleet of self-driving golf carts at a park in Singapore over six days,” writes Subbaraman.
Kelsey Atherton reports for Popular Science that MIT researcher have developed and tested a self-driving golf cart in a public garden in Singapore. Atherton writes that one potential use for the self-driving golf carts is a shared vehicle system where the carts would “drive people to their destination, and then either return or seek new riders.”