Boston Herald reporter Jordan Graham writes that MIT researchers have developed a wearable device aimed at helping visually impaired users navigate their environments. The system is equipped with, “a 3-D camera, a vibration pack and an electronic braille screen that will tell users not just where things are — but what they are.”
Graduate student Joy Buolamwini speaks with Guardian reporter Ian Tucker about her work fighting algorithmic biases. Buolamwini explains that she is, “trying to identify bias, to point out cases where bias can occur so people can know what to look out for, but also develop tools where the creators of systems can check for a bias in their design.”
CSAIL researchers have developed a system that allows robots to teach one another learned skills, reports Grace Williams for FOX News. Williams explains that the system, “gives non-coders the ability to teach robots various tasks using information about manipulating objects in a single demonstration. These skills can then be passed along to other robots that move in different ways.”
Anthony Cuthbertson of Newsweek reports that PhD student Claudia Pérez D’Arpino has developed a system that allows robots to learn a skill and teach it to another robot. Armed with knowledge of how to perform a task, a 3-D interface demonstrates the tasks “allowing [the robot] to understand the motions it is being taught in the real world,” explains Cuthbertson.
This CNN video highlights a new system developed by CSAIL researchers that allows noncoders to teach robots to perform a task after a single demonstration. The new programming method also enables robots to learn from other robots, which could enable “a variety of robots to perform similar tasks.”
Wired reporter Matt Simon writes that CSAIL researchers have developed a new system that allows noncoders to be able to teach robots a wide range of tasks, and enables robots to transfer new skills to other robots. Simon notes that the development is a “glimpse into a future where, more and more, robots communicate without humans at all.”
NuTonomy, an MIT startup, will soon start testing self-driving cars in Boston’s Seaport District and Fort Point areas, writes Doug Newcomb for Forbes.
Using an algorithm and a 3-D scan of a human body, Prof. Carlo Ratti designed a foldable stool that can conform to different shapes, writes Margaret Rhodes for Wired. Allowing algorithms to determine the form of each hinge, “allows you to create shapes and functions that you otherwise wouldn’t be able to,” Ratti explains.
BBC News reporter Zoe Kleinman writes that graduate student Joy Buolamwini has developed an initiative aimed at tackling algorithmic bias. "If we are limited when it comes to being inclusive that's going to be reflected in the robots we develop or the tech that's incorporated within the robots,” says Buolamwini.
CSAIL researchers have developed software that allows users to design and virtually test drones, writes Alex Davies for Wired. Graduate student Tao Du explains that the software can help users “explore and try different shapes and different controllers.”
Prof. Daniela Rus speaks to the BBC’s Gareth Mitchell about the robots developed by CSAIL that can modify their behavior based on brain waves detected by a human operator. “We imagine operating prosthetic devices, a wheelchair, even autonomous vehicles,” says Prof. Rus.
A study co-authored by Prof. Carlo Ratti finds ride-sharing is feasible in different cities around the world, reports Eleanor Cummins for Popular Science. “The key thing is how this can transform our cities. Every car you remove from the road, you are removing pollution and traffic,” explains Ratti.
CSAIL researchers have developed a system that allows robots to correct their mistakes based on input from the brainwaves of human operators, reports Wired’s Matt Simon. “It’s a new way of controlling the robot,” explains Prof. Daniela Rus, “in the sense that we aim to have the robot adapt to what the human would like to do.”
Anthony Cuthbertson of Newsweek writes that CSAIL researchers have developed a system that allows robots to change their actions based on feedback from the brain waves of a human operator. “Imagine robots or smartphones that could immediately correct themselves when you realize they’re making a mistake,” says PhD candidate Joseph DelPreto.
A feedback system developed by CSAIL researchers allows humans to correct a robot’s mistakes using brain signals, writes Janet Burns for Forbes. The system could be used as a “communication method for those who can't use verbal means, such as immobilized or even 'locked in' victims of paralysis,” explains Burns.