A robotic dog that can cope with new scenarios is an important stop in artificial intelligence.

Most image-recognition systems are trained using large databases that contain millions of photos of everyday objects, from snakes to shakes to shoes. With repeated exposure, AIs learn to tell one type of object from another. Now researchers in Japan have shown that AIs can start learning to recognize everyday objects by being trained on computer-generated fractals instead. It's a weird idea but it could be a big deal. Generating training data automatically is an exciting trend in machine learning.

After listening to early adopters, Boston Dynamics gave its robot dog a hardware boost and extended WiFi capabilities. It can be controlled remotely using the company's new web browser-based interface, Scout. It's the first Boston Dynamics device equipped with self-charging capabilities and a dock, which means it can be deployed for longer-term missions "with little to no human interaction," Boston Dynamics said. The previous version of Spot had around 90 minutes of battery life before requiring a manual charge.

The idea of chatbots based on dead people raises several ethical questions surrounding privacy. People only share so much on social media, so algorithms relying on that would be flawed. Humans are also highly complex and influenced by experiences that aren't always shared via text messages. Microsoft's patent suggests that the company could use crowdsourced data to fill in any gaps. In other words, the resulting chatbot could end up saying things the person never said.

Artificial intelligence is hardly confined by international borders, as businesses, universities, and governments tap a global pool of ideas, algorithms, and talent. Yet the AI programs that result from this global gold rush can still reflect deep cultural divides. New research shows how government censorship affects AI algorithms--and can influence the applications built with those algorithms. Margaret Roberts, a political science professor at UC San Diego, and Eddie Yang, a PhD student there, examined AI language algorithms trained on two sources: the Chinese-language version of Wikipedia, which is blocked within China; and Baidu Baike, a similar site operated by China's dominant search engine, Baidu, that is subject to government censorship. Baidu did not respond to a request for comment.

The facial recognition app Clearview AI is not welcome in Canada and the company that developed it should delete Canadians' faces from its database, the country's privacy commissioner said on Wednesday. "What Clearview does is mass surveillance, and it is illegal," Commissioner Daniel Therrien said at a news conference. He forcefully denounced the company as putting all of society "continually in a police lineup." Though the Canadian government does not have legal authority to enforce photo removal, the position -- the strongest one an individual country has taken against the company -- was clear: "This is completely unacceptable." Clearview scraped more than three billion photos from social media networks and other public websites in order to build a facial recognition app that is now used by over 2,400 U.S. law enforcement agencies, according to the company.

The optimization of reactions used to synthesize target compounds is pivotal to chemical research and discovery, whether in developing a route for manufacturing a life-saving medicine1 or unlocking the potential of a new material2. But reaction optimization requires iterative experiments to balance the often conflicting effects of numerous coupled variables, and frequently involves finding the sweet spot among thousands of possible sets of experimental conditions. Expert synthetic chemists currently navigate this expansive experimental void using simplified model reactions, heuristic approaches and intuition derived from observation of experimental data3. Writing in Nature, Shields et al.4 report machine-learning software that can optimize diverse classes of reaction with fewer iterations, on average, than are needed by humans. Machine learning has emerged as a useful tool for various aspects of chemical synthesis, because it is ideally suited to extrapolating predictive models that are used to solve synthetic problems by recognizing patterns in multidimensional data sets5.

So many robots work at Changi General Hospital in Singapore that until recently it wasn't uncommon to find two delivery bots sitting in a hallway or outside an elevator in a standoff. Such impasses used to happen "several times a day," says Selina Seah, who directs the hospital's Center for Healthcare Assistive and Robotics Technologies. Unsure how to move around another object, or human passersby, the robots would simply freeze, each waiting for the other to move first. "The humans would have to actually go down and pull them apart," she says. Seah says Changi has about 50 robots, from eight manufacturers.

Apple is facing our face-masked future. This week, the company started testing some new software for the iPhone that will let device owners unlock the handset while wearing a face covering. There's a catch though, one that lines up with Apple's strategy of locking people in to different Apple products and highlights how challenging it can be to develop accurate facial recognition technology: The new face-unlock feature requires an Apple Watch. The first developer beta of iOS 14.5 includes updates to app tracking controls and Siri alongside the face-mask function. App-makers typically get early access to the newest version of iOS in order to launch or retool their apps well in advance of the formal software release. The fully-baked version of the software is expected to be made available to the general public this spring.

In this Article, a funding statement was inadvertently omitted from the Acknowledgements section. The following sentence should be added at the end of the Acknowledgements: 'This work was supported by NIH grant R01 EY011488 (D.F.), NIH grant K99 EY031137 (B.S.), the Max Planck Florida Institute for Neuroscience, and the Max Planck Society.' The original Article has been corrected online.