Postdoc Matthew Peterson speaks with WGBH reporter Edgar Herwick about why humans make eye contact. Peterson explains that humans are not good at judging where they are looking when talking to others, adding that the information we use is “highly concentrated in the eye region. So even if we're not looking at the eyes directly, we're using the eyes."
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.
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.
MIT researchers have developed a device that allows humans to guide robots using brainwaves, reports Clive Cookson for the Financial Times. The prototype brain-computer interface “enables a human observer to transmit an immediate error message to a robot, telling it to fix a mistake when it does something wrong.”
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.
Wall Street Journal reporter Daniel Akst writes that MIT researchers have developed a way to “tap into the insight of the expert minority within a crowd—a minority whose views would otherwise be swamped in a simple majority vote or poll.” The technique significantly enhanced “the wisdom of crowds, reducing errors by more than 20%.”
Boston Herald reporter Jordan Graham writes that the McGovern Institute has established a new center focused on autism research, thanks to a gift from Lisa Yang and Hock Tan ’75 SM ’75. Graham explains that the center will “focus on trying to make significant jumps through new technologies such as gene editing with CRISPR/Cas9.”
Boston Herald reporter Lindsay Kalter writes that Prof. Ed Boyden is working on a new effort to develop technologies that would allow doctors to explore tumors using virtual reality. Boyden explains that he and his colleagues hope to use virtual reality to explore “what a tumor’s weaknesses are, and what makes it thrive.”
MIT is launching a center for autism research at the McGovern Institute with $20 million in funding from MIT alumnus Hock Tan and Lisa Yang, writes Barb Darrow for Fortune. Darrow writes that Yang told Fortune she was "greatly impressed by both the collegiality and focus of the institute's researchers.”
An algorithm developed by MIT researchers helps extract the correct answer from a large group of people even when the majority of people answer incorrectly, writes Erin Ross for Nature. While previous assumptions viewed the average opinion of a crowd as correct, the algorithm identifies “specialists with special knowledge, like doctors,” explains Prof. Dražen Prelec.
Scientific American reporter Simon Makin writes that MIT researchers have developed a new approach to extract correct answers from a crowd. “The new method performed better than majority or confidence-based methods alone, reducing errors by between 21 and 35 percent,” Makin explains.
Appearing on WCVB-TV’s Chronicle, Provost Marty Schmidt explains why Kendall Square is a hub for innovation, highlighting how the region brings together organizations working on everything from computer science and biotech to brain and cognitive sciences. Schmidt explains that Kendall Square’s innovation ecosystem means research “coming out of MIT (can) be immediately translated to impact.”