Verge reporter Rachel Becker writes that MIT researchers have developed a robotic cheetah that can run up the stairs and navigate without the use of cameras. Becker explains that the Cheetah 3 robot navigates its environment by touch, which could allow it to, “venture where humans can’t — like deep inside power plants for inspections.”
Forbes contributor Frederick Daso writes about a new MIT startup called Alba that is aimed at helping families in Latin America find qualified caregivers for children and the elderly. Daso explains that leveraging the “social networks of both the family and the prospective babysitter allows Alba to provide a babysitter for any parent.”
This BBC Click segment highlights the artificial intelligence system developed by CSAIL researchers that can monitor people’s movements through walls. Prof. Dina Katabi explains that the device helps preserve the privacy of those being monitored by separating and encrypting, “any identifiable information from the measurement.”
Fast Company reporter Steven Melendez writes that CSAIL researchers have created a new system that allows a robot to detect human brainwave patterns so it knows when it made a mistake. Melendez explains that, “Teaching robots to understand human nonverbal cues and signals could make them safer and more efficient at working with people.”
MIT researchers have developed a system that “lets a person control a robotic arm with brainwaves and subtle hand gestures,” reports Jesus Diaz for Co.Design. According to Prof. Daniela Rus, the goal is “to develop robotic systems that are a more natural and intuitive extension of us.”
Engadget reporter Jon Fingas writes that MIT researchers have developed a tiny computer chip small enough to fit on a honeybee-sized drone that can help the drone navigate. The technology could eventually be applied to, “smart pills that navigate to where they're needed, or virtually any vehicle that may need to last for a very long time on one battery charge.”
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.”
By measuring how radio waves bounce off of human bodies, MIT researchers have developed a system that can track movements from behind a wall, writes Andrew Liszewski for Gizmodo. The researchers are working to improve on the current stick figure icons by “generating 3D representations that include subtle and small movements,” writes Liszewski.
Researchers led by Prof. Dina Katabi have developed a system to track people’s movements from behind a wall, writes Kaleigh Rogers of Motherboard. Earlier versions were unable to track precise movements, but the system can now interpret signals bouncing off bodies and “translate it into the movement of 14 different key points on the body, including the head, elbows, and knees.”
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.