Indian law enforcement is starting to place huge importance on facial recognition technology. Delhi police, looking into identifying people involved in civil unrest in northern India in the past few years, said that they would consider 80 percent accuracy and above as a "positive" match, according to documents obtained by the Internet Freedom Foundation through a public records request. Facial recognition's arrival in India's capital region marks the expansion of Indian law enforcement officials using facial recognition data as evidence for potential prosecution, ringing alarm bells among privacy and civil liberties experts. There are also concerns about the 80 percent accuracy threshold, which critics say is arbitrary and far too low, given the potential consequences for those marked as a match. India's lack of a comprehensive data protection law makes matters even more concerning.

Resilience is the new holy grail in wireless communication systems. Complex radio environments and malicious attacks using intelligent jamming contribute to unreliable communication systems. Early approaches to deal with such problems were based on frequency hopping, scrambling, chirping, and cognitive radio-based concepts, among others. Physical-layer security was increased using known codes and pseudorandom number sequences. However, these approaches are not up to modern standards; they do not improve resilience and are rather easy to attack by means of intelligent jamming.

The Seeker's software allows players to customize how they practice with it. Athletes can catch balls from close to the machine to improve hand-eye coordination. They can also program the robot to throw a ball at a specific spot on the field, or simulate more lifelike conditions by over or under-throwing a ball. Players wear a pager-like tag which allows the robot to track their location on the field, and throw a ball accurately within inches.

Second, the "race" narrative feels like a cudgel to persuade the public or elected officials to move faster with rules and regulations, justify loose ones or expose people to unnecessary risks to "win." The Wall Street Journal reported last week about concerns that the autonomous trucking company TuSimple was taking safety risks with people's lives "in a rush to deliver driverless trucks to market." The Journal reported that a truck fitted with TuSimple technology veered suddenly on an Arizona interstate last spring and careered into a concrete barricade. TuSimple told The Journal that no one was hurt and that safety was its top priority. Apple's autonomous test cars have smacked into curbs near the company's Bay Area headquarters, and earlier this year one nearly crashed into a jogger who had the right of way crossing the street, The Information reported last month.

Thatcham Research, the motor insurers' automotive research centre, welcomed the government's ambition but warned "complete clarity around the driver's legal responsibilities" was needed, along with transparency on how the technology is marketed, "how the dealer describes systems when handing over the keys and how the self-driving system itself communicates with the driver".

In the 1940s, sociologists Kenneth and Mamie Clark placed white and Black dolls in front of young children and asked them to do things like pick the doll that "looks bad" or "is a nice color." The doll test was invented to better understand the evil consequences of separate and unequal treatment on the self-esteem of Black children in the United States. Lawyers from the NAACP used the results to successfully argue in favor of the desegregation of US schools. Now AI researchers say robots may need to undergo similar tests to ensure they treat all people fairly. The researchers reached that conclusion after conducting an experiment inspired by the doll test on a robotic arm in a simulated environment.

Late last week, Google research scientist Fei Xia sat in the center of a bright, open-plan kitchen and typed a command into a laptop connected to a one-armed, wheeled robot resembling a large floor lamp. The robot promptly zoomed over to a nearby countertop, gingerly picked up a bag of multigrain chips with a large plastic pincer, and wheeled over to Xia to offer up a snack. The most impressive thing about that demonstration, held in Google's robotics lab in Mountain View, California, was that no human coder had programmed the robot to understand what to do in response to Xia's command. Its control software had learned how to translate a spoken phrase into a sequence of physical actions using millions of pages of text scraped from the web. That means a person doesn't have to use specific preapproved wording to issue commands, as can be necessary with virtual assistants such as Alexa or Siri.

Nathan Copeland considers himself a cyborg. The 36-year-old has lived with a brain-computer interface for more than seven years and three months. As of today--August 17--that's the longest anyone has had an implant like this. An electrode array the size of a pencil eraser, surgically installed in his motor cortex, translates his neural impulses into commands that allow him to control external devices: a computer, video games, and a robotic arm he can move with just his thoughts. A car accident in 2004 left Copeland paralyzed from the chest down, unable to move or feel his limbs.

Biological robots made of human tracheal cells can promote the repair of wounded neural tissue in the lab. While the research is still in an early stage, the findings suggest that the robots could one day treat the cellular damage that can occur after a stroke or with paralysis. In 2020, Michael Levin at Tufts University in Massachusetts and his colleagues created living robots out of frog cells, called xenobots.