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.
CSAIL researchers have developed a system that allows robots to detect brain signals generated by human operators, writes Oscar Williams of Huffington Post. The researchers hope the new system could “pave the way for more seamless interactions between robots and humans.”
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.
New Scientist reporter Matt Reynolds writes that MIT researchers have developed a new brain-computer interface that enables people to correct robots’ mistakes using brain signals. “We’re taking baby steps towards having machines learn about us, and having them adjust to what we think,” explains Prof. Daniela Rus, director of CSAIL.