UVC can be harmful to the skin and eyes, which is why the robot, which looks like a bunch of fluorescent lights standing up on a moving base, is being tested by Frasers Property Retail after the mall's closing time.

Stuart Russell has a rule. "I won't do an interview until you agree not to put a Terminator on it," says the renowned British computer scientist, sitting in a spare room at his home in Berkeley, California. "The media is very fond of putting a Terminator on anything to do with artificial intelligence." The request is a tad ironic. Russell, after all, was the man behind Slaughterbots, a dystopian short film he released in 2017 with the Future of Life Institute.

Up to 20 million manufacturing jobs around the world could be done by robots over the next decade, according to recent analysis. Oxford Economics' report seems to back up the fear that advances in automation and artificial intelligence on the factory floor are a threat to the security of traditional manufacturing jobs. But what does a robot in the workplace really mean? What could the impact be on Scotland's manufacturing and engineering companies, and what can they do to develop their business models and workforce to prepare for change? In industry, the term "robots" is used to describe everything from "pick and place" machines and robotic welders, to software applications (bots) that can perform an automated task such as placing an order with a supplier when stocks run low.

Automated surveillance is going to become increasingly common as companies and researchers find new ways to use machine learning to analyze live video footage. A new project from scientists in the UK and India shows one possible use for this technology: identifying violent behavior in crowds with the help of camera-equipped drones. In a paper titled "Eye in the Sky," the researchers describe their system. It uses a simple Parrot AR quadcopter (which costs around $200) to transmit video footage over a mobile internet connection for real-time analysis. An algorithm trained using deep learning estimates the poses of humans in the video and matches them to postures the researchers have designated as "violent."

A few weeks ago, for the first time ever, a computer beat the world champion of Go, one of the most complex games known to man. This was another watershed moment in the progress of artificial intelligence. To give you an idea how complex Go is, there are 2.082 10 170 possible board configurations. That is 2 with 170 zeroes after it. Chances are your brain cannot even conceive of a number that large (but a computer can). Or to give you an idea of how big of a number that is, there are only 10 80 atoms in the universe -- that is, one followed by 80 zeroes. The reason this is such a big deal is that Go is so complicated that in order to beat a top human player, a machine would have to learn how to think creatively, improvising and adapting to the situation at hand without being able to calculate every possible outcome; i.e., there has to be some serious artificial intelligence going on -- like real, creative intelligence.

The idea that computers will soon steal our jobs is an article of faith among many of the world's most powerful people. The argument goes like this: breakthroughs in robotics and artificial intelligence will make it possible to automate various kinds of labour. Self-driving cars will replace taxi and truck drivers; software will replace lawyers and accountants. We'll end up with a world where machines do almost all of the work. Over the last few years, a growing chorus of pundits, academics and executives have made this scenario seem inevitable – and imminent. There are many reasons to be sceptical of their claims.

A few weeks ago, for the first time ever, a computer beat the world champion of Go, one of the most complex games known to man. This was another watershed moment in the progress of artificial intelligence. To give you an idea how complex Go is, there are 2.082 10 170 possible board configurations. That is 2 with 170 zeroes after it. Chances are your brain cannot even conceive of a number that large (but a computer can). Or to give you an idea of how big of a number that is, there are only 10 80 atoms in the universe -- that is, one followed by 79 zeroes.