Welcome to the future: Step inside this toaster. On Monday, the autonomous vehicle company Zoox--acquired by Amazon over the summer for a reported $1.2 billion--rolled out its robotaxi. The design, which has been in development for six years, may look familiar. Almost every autonomous vehicle concept revealed over the past few years--by carmakers, engineers, ride-hailers, and startups--has been a neat, rectangular box. In this case, form equals function.

Understanding how Google's search works is a key to figuring out why so many companies find it nearly impossible to compete and, in fact, go out of their way to cater to its needs. Every search request provides Google with more data to make its search algorithm smarter. Google has performed so many more searches than any other search engine that it has established a huge advantage over rivals in understanding what consumers are looking for. That lead only continues to widen, since Google has a market share of about 90 percent. Google directs billions of users to locations across the internet, and websites, hungry for that traffic, create a different set of rules for the company.

Saiph Savage, director of the human-computer interaction lab at West Virginia University, advocates for the workers who put in the time to develop training data for artificial intelligence. Many of the most successful and widely used machine-learning models are trained with the help of thousands of low-paid gig workers. Millions of people around the world earn money on platforms like Amazon Mechanical Turk, which allow companies and researchers to outsource small tasks to online crowdworkers. According to one estimate, more than a million people in the US alone earn money each month by doing work on these platforms. Around 250,000 of them earn at least three-quarters of their income this way.

Boston Dynamics is widely recognized for pioneering the field of agile robots that are inspired by animals. The legged robots are built to remain balanced as they maneuver through rocky trails, up and down staircases or through narrow passages. Several videos of the company's robotic dog Spot, cat Cheetah and humanoid Atlas have gone viral, stoking admiration -- and terror -- across the Internet.

Many of the most successful and widely used machine learning models are trained with the help of thousands of low-paid gig workers. Millions of people around the world earn money on platforms like Amazon Mechanical Turk, which allow companies and researchers to outsource small tasks to online crowdworkers. According to one estimate, more than a million people in the US alone earn money each month by doing work on these platforms. Around 250,000 of them earn at least three quarters of their income this way. But despite many working for some of the richest AI labs in the world, they are paid below minimum wage and given no opportunities to develop their skills.

Director of civil rights group Big Brother Watch, Silkie Carlo, said: "To see a supposedly ethical company secretly using rights-abusive tech like facial recognition on its customers in the UK is deeply chilling.

Like humans, pigs have idiosyncratic faces, and new players in the Chinese pork market are taking notice, experimenting with increasingly sophisticated versions of facial recognition software for pigs. China is the world's largest exporter of pork, and is set to increase production next year by 9%. As the nation's pork farms grow in scale, more farmers are turning to AI systems like facial recognition technology – known as FRT – to continuously monitor, identify, and even feed their herds. This automated style of farming has the potential to be safer, cheaper and generally more effective: In 2018, pig farmers in China's Guangxi province trialling FRT found that it slashed costs, cut down on breeding time, and improved welfare outcomes for the pigs themselves. But it also has the potential to leave behind independent, small-scale farmers, who cannot afford to introduce this kind of technology to their operations.

Companies such as Cruise and competitor Zoox, acquired by Amazon this year, have set their sights on San Francisco, seeing the potential payoff of conquering a complex urban environment and the country's second-most densely populated major city, rather than starting small and gradually increasing their capabilities. But analysts have said self-driving vehicles will have to deploy unique skillsets for each of the environments where they are dispatched.

Robots can pick themselves up after a fall, even in an unfamiliar environment, thanks to an artificially intelligent controller that can adapt to new scenarios. It could make four-legged robots more useful in responding to natural disasters, such as earthquakes. Zhibin (Alex) Li at the University of Edinburgh, UK and his colleagues used an AI technique called deep reinforcement learning to teach four-legged robots a set of basic skills, such as trotting, steering and fall recovery. This involves the robots experimenting with different ways of moving and being rewarded with a numerical score for achieving a certain goal, such as standing up after a fall, and penalised for failing. This lets the AI recognise which actions are desired and repeat them in the similar situations in the future.

Joy Buolamwini from the MIT Media Lab says facial-recognition software has the highest error rates for darker-skinned females. New applications powered by artificial intelligence (AI) are being embraced by the public and private sectors. Their early uses hint at what's to come. In June 2020, IBM, Amazon and Microsoft announced that they were stepping back from facial-recognition software development amid concerns that it reinforces racial and gender bias. Amazon and Microsoft said they would stop selling facial-recognition software to police until new laws are passed in the United States to address potential human-rights abuses.