Motional did not say how many cars had participated in the Las Vegas tests, but said in its statement that "multiple" autonomous vehicles had been used on routes that included public roads and closed courses. During the tests, the vehicles sensed and responded to human-driven vehicles, cyclists and pedestrians, the company said. Some tests were completed with a safety operator in the car; others were completed without one.

Boston Dynamics has racked up hundreds of millions of YouTube views with viral clips of its futuristic, legged robots dancing together, doing parkour, and working in a warehouse. A group of meme-spinning pranksters now wants to present a more dystopian view of the company's robotic tech. They added a paintball gun to Spot, the company's doglike machine, and plan to let others control it inside a mocked-up art gallery via the internet later this week. The project, called Spot's Rampage, is the work of MSCHF (pronounced "mischief," of course), an internet collective that regularly carries out meme-worthy pranks. Previous MSCHF stunts include creating an app that awarded $25,000 to whomever could hold a button down for the longest; selling "Jesus Shoes" sneakers with real holy water in the soles (Drake bought a pair); developing an astrology-based stock-picking app; and cutting up and selling individual spots from a Damian Hirst painting.

The software takes the "probe image", typically a face captured on CCTV or from a mobile phone, and measures the facial features - our biometric data. It then compares that with all custody images on the database shared by Gwent and South Wales Police.

Dr Gebru, a leading Artificial Intelligence ethics researcher, says she was fired late last year after sending an internal email that accused Google of "silencing marginalised voices". However, Google claims she left the company.

Google has fired one of its top artificial intelligence researchers, Margaret Mitchell, escalating internal turmoil at the company following the departure of Timnit Gebru, another leading figure on Google's AI ethics team. Mitchell, who announced her firing on Twitter, did not immediately respond to requests for comment. In a statement to Reuters, Google said the firing followed a weeks-long investigation that found she moved electronic files outside the company. Google said Mitchell violated the company's code of conduct and security policies. Google's ethics in artificial intelligence research unit has been under scrutiny since December's dismissal of Gebru, a prominent Black researcher in Silicon Valley.

With every new generation of consoles and components, video games grow closer and closer to replicating reality. From the glistening sweat on star athletes' faces in sports franchises like "Madden" and "NBA 2K," to the soft swaying of grass in samurai thriller "Ghost of Tsushima," game-makers are always leveraging the latest in granular detail to sell the immersive power of the medium. Tristan Cooper, who owns the Twitter account "Can You Pet the Dog?," never set out to create a social media juggernaut. Rather, he was just trying to point out what he felt was a common quirk of many high-profile games: While many featured dogs, wolves and other furry creatures as hostile foes of the protagonist, those that did feature cuddly animal friends rarely let you pet them. Cooper says the account was particularly inspired by his early experience with online shooter "The Division 2." "'The Division 2′s' apocalyptic streets were rife with frightened dogs that you could not console or help in any way," he wrote in an email to The Washington Post.

Swift for TensorFlow, a Google-led project to integrate the TensorFlow machine learning library and Apple's Swift language, is no longer in active development. Nevertheless, parts of the effort live on, including language-differentiated programming for Swift. The GitHub repo for the project notes it is now in archive mode and will not receive further updates. The project, the repo notes, was positioned as a new way to develop machine learning models. "Swift for TensorFlow was an experiment in the next-generation platform for machine learning, incorporating the latest research across machine learning, compilers, differentiable programming, systems design, and beyond."

Consider this scene from the 2014 film, Ex Machina: A young nerd, Caleb, is in a dim room with a scantily clad femmebot, Kyoko. Nathan, a brilliant roboticist, drunkenly stumbles in and brusquely tells Caleb to dance with the Kyoko-bot. To kick things off, Nathan presses a wall-mounted panel and the room lights shift suddenly to an ominous red, while Oliver Cheatham's disco classic "Get Down Saturday Night" starts to play. Kyoko--who seems to have done this before--wordlessly begins to dance, and Nathan joins his robotic creation in an intricately choreographed bit of pelvic thrusting. The scene suggests that Nathan imbued his robot creation with disco functionality, but how did he choreograph the dance on Kyoko, and why?

In April, as COVID-19 cases exploded across the U.S. and local officials scrambled for solutions, a police department in Connecticut tried a new way to monitor the spread of the virus. One morning, as masked shoppers lined up 6 feet apart outside Trader Joe's in Westport, the police department flew a drone overhead to observe their social distancing and detect potential coronavirus symptoms, such as high temperature and increased heart rate. According to internal emails, the captain flying the mission wanted to "take advantage" of the store's line. But the store had no heads-up about the flight, and neither did the customers on their grocery runs, even though the drone technology managed to track figures both inside and outside. The drone program was unveiled a week later when the department announced its "Flatten the Curve Pilot Program" in collaboration with the Canadian drone company Draganfly, which was due to last through the summer. But less than 48 hours later after the program's public unveiling, the police department was forced to dump it amid intense backlash from Westport residents.

Deborah Raji, a fellow at nonprofit Mozilla, and Genevieve Fried, who advises members of the US Congress on algorithmic accountability, examined over 130 facial-recognition data sets compiled over 43 years. They found that researchers, driven by the exploding data requirements of deep learning, gradually abandoned asking for people's consent. This has led more and more of people's personal photos to be incorporated into systems of surveillance without their knowledge. It has also led to far messier data sets: they may unintentionally include photos of minors, use racist and sexist labels, or have inconsistent quality and lighting. The trend could help explain the growing number of cases in which facial-recognition systems have failed with troubling consequences, such as the false arrests of two Black men in the Detroit area last year.