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.”
WCVB reporter Mike Wankum visits the Camera Culture Group at the MIT Media Lab to learn more about a device that uses photon imaging to see through dense fog. Wankum explains that the device can, “calculate how fog typically reflects laser light and then removes the fog from the equation, revealing an image hidden inside.”
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.
MIT researchers have developed a virtual reality environment in order to train drones, writes Logan Booker of Gizmodo. “It's a neat use of an emerging technology, one that makes a lot of sense when you think about it,” Booker concludes.
In an effort to determine how different data impacts the view of AI, Media Lab researchers used gruesome images to train a system, which ultimately created a psychopathic AI, writes BBC reporter Jane Wakefield. "It highlights the idea that the data we use to train AI is reflected in the way the AI perceives the world and how it behaves," says Prof. Iyad Rahwan.
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.
MIT researchers have developed a virtual reality system that can train drones to fly faster while also avoiding obstacles, reports Lauren Barack for Salon. Barack explains that the “researchers are programming the drones so they think they're in a living room or bedroom while they fly. They virtually see obstacles around them, but those impediments aren't really there.”
MIT researchers have developed an algorithm that can accurately determine how many taxis a city needs, providing a way to reduce the number of cars on the road, according to Xinhua. “Using the new algorithm, they found the fleet size of cab-hailing service in New York could be cut down by about 30 percent in an optimal scenario.”
MIT researchers are using virtual reality to train autonomous drones to fly in a variety of environments, writes Steven Melendez for Fast Company. Future tests may train the drone to fly safely around humans “as if they were in the same area, enabling it to practice sharing a space without actually endangering any human lives,” Melendez notes.