Wired reporter Tom Simonite highlights how Prof. Daniela Rus is developing technology that enables a car’s computer to take control from human drivers to help prevent accidents. “Eventually everyone will get to autonomy, but the technology’s not ready yet,” explains Rus. “This is an intermediate step we can take to make driving safer in the meantime.”
A study from the AgeLab found that most people would not buy a completely driverless car. “Respondents said they're uncomfortable with the loss of control and don't trust the technology. They also don't feel self-driving cars are safe,” writes Zeninjor Enwemeka for WBUR.
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.”
Anant Agarwal, president of edX, and Kalyan Veeramachaneni, a principal research scientist at LIDS, are featured on Fast Company’s 2017 list of the “Most Creative People in Business.” Agarwal is celebrated for “mastering online education,” and Veeramachaneni for developing a system that enables humans and AI to work together to detect possible security threats.
New Scientist reporter Timothy Revell writes that a new study by Prof. Iyad Rahwan shows that automation will have a larger impact on jobs in smaller cities. Rahwan and his colleagues found that “towns and small cities have a smaller proportion of jobs that will be resilient to automation than larger urban centers.”
Researchers at CSAIL have developed a new system to train robots called C-LEARN, which imbues “a robot with a knowledge base of simple steps that it can intelligently apply when learning a new task,” writes Matthew Hutson for Science.
Prof. Regina Barzilay’s research group is working with MGH to use artificial intelligence and machine learning to improve cancer diagnoses, reports CNBC’s Meg Tirrell. The group also hopes to allow doctors to use “the huge quantities of data available on patients to make more personalized treatment decisions,” explains Tirrell.
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.”
Boston Globe columnist Scott Kirsner speaks with Professors Regina Barzilay and Tommi Jaakkola about their Introduction to Machine Learning class. Jaakkola explains that the course connects “the more theoretical, algorithmic stuff students are learning to actual data and problems.”
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.
MIT researchers have developed a new low-power chip that could make voice control practical for simple electronic devices, reports Tim Moynihan for Wired. While other speech-processing platforms use the cloud to process voice commands, “the MIT chip handles much more of that processing itself.”
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.