Popular Mechanics reporter David Grossman writes that MIT researchers have developed a new system that helps robots used in autism therapy better estimate how engaged a child is during an interaction. Grossman explains that, “using the personalized algorithm, the robot was able to correctly interpret a child's reaction 60 percent of the time.”
In an article for The New York Times, graduate student Joy Buolamwini writes about how AI systems can often reinforce existing racial biases and exclusions. Buolamwini writes that, “Everyday people should support lawmakers, activists and public-interest technologists in demanding transparency, equity and accountability in the use of artificial intelligence that governs our lives.”
A new system developed by MIT researchers analyzes radio signals that bounce off of human bodies to track their movement and posture from behind walls, write Saqib Shah for Fox News. Shah suggests that the system could allow military personal “to ‘see’ hidden enemies by wearing augmented reality headsets.”
CSAIL researchers have developed a new system that uses low-power radio waves to detect and track people behind walls, reports Matt Simon for Wired. The system, which can be used to detect signs of distress in elderly patients, also “distinguishes one person from another in the same way your fingerprint distinguishes you,” explains Prof. Dina Katabi.
CSAIL researchers have created a system that can sense a person’s movements through walls, writes John Biggs for TechCrunch. The system is primarily intended as a healthcare device and could help with “passive monitoring of a subject inside a room without cameras or other intrusions,” and could provide insight into disease progression, Biggs explains.
Fast Company reporter Melissa Locker writes that CSAIL researchers have developed a system that allows wireless devices to sense a person’s movement through walls. Locker explains that the technology was created as a way to help those who are elderly, as it could be used to “monitor diseases like Parkinson’s and multiple sclerosis and provide a better understanding of disease progression.”
In response to a reader’s question about self-driving cars, Mercury News reporter Gary Richards describes new technology in the works by MIT researchers to allow, “driverless cars to change lanes more like human drivers do.”
To prove that the data used to train machine learning algorithms can greatly influence its behavior, MIT researchers input gruesome and violent content into an AI algorithm, writes Benjamin Fearnow for Newsweek. The result is “Norman,” an AI system in which “empathy logic simply failed to turn on,” explains Fearnow.
In this video, BBC Click spotlights VirtualHome, a simulator developed by CSAIL researchers that could be used to teach robots to perform household chores. The researchers hope the system could one day allow for seamless human-robot collaboration by allowing robots to, “cooperate with [humans] in finishing their activity,” explains graduate student Xavier Puig.
CSAIL researchers have developed a new system that could be used to train machines to complete tasks, writes Patrick Lucas Austin for Gizmodo. The researchers hope the system could eventually be used to, “teach robots how to accomplish tasks simply by showing them actual instructional videos,” Austin explains.
MIT researchers have created a system that aims to teach robots how to perform household chores by breaking down activities into simple steps, reports Sean Captain for Fast Company. Captain explains that in order to simplify each chore, the researchers, “identified sub-tasks to describe thousands of duties in settings such as kitchens, dining rooms, and home offices.”
Wired reporter Matt Simon writes that CSAIL researchers have developed a new virtual system that could eventually be used to teach robots how to perform household chores. Researchers hope the system could one day help robots, “learn to anticipate future actions and be able to change the environment for the human,” explains PhD student Xavier Puig.
Using LiDAR sensors, MIT researchers have developed an autonomous vehicle navigation system for rural roads with “no detailed, three-dimensional map for the vehicle to reference,” reports Rob Verger of Popular Science. “The solution for urban mapping really doesn’t scale very well to a huge portion of the country,” explains graduate student Teddy Ort.
CSAIL researchers have developed a system that uses LIDAR and GPS to allow self-driving cars to navigate rural roads without detailed maps, writes Tracey Lindeman of Motherboard. Autonomous ride-hailing or car-sharing is important in rural communities because “the carless in these areas have few transportation options; many small communities don’t even have public buses,” notes Lindeman.
Eric Mack writes for Forbes about a new system from MIT researchers that uses GPS in conjunction with LIDAR and IMU sensors to power self-driving vehicle navigation. Graduate student Teddy Ort says the system “shows the potential of self-driving cars being able to actually handle roads beyond the small number that tech companies have mapped.”