The move didn't make sense to the humans packed into the sixth floor of Seoul's Four Seasons hotel. But the Google machine saw it quite differently. The machine knew the move wouldn't make sense to all those humans. And yet it played the move anyway, because this machine has seen so many moves that no human ever has. In the second game of this week's historic Go match between Lee Sedol, one of the world's top players, and AlphaGo, an artificially intelligent computing system built by a small team of Google researchers, this surprisingly skillful machine made a move that flummoxed everyone from the throngs of reporters and photographers to the match commentators to, yes, Lee Sedol himself.

Apple has come under fire for its use of conflict minerals in iPhones (so have many other device manufacturers, to be fair) before, and the company has just introduced how it aims to reduce its environmental impact. It comes by the way of Liam, a robot that disassembles old iPhones into their core components. The tungsten from the device's alert module will become a cutting tool for example, while the silver contained therein is used for solar panels -- possibly including the ones powering Cupertino's Thailand operations. With the disposable nature of electronics, seeing moves like this is entirely welcome.

Lawrence Wintermeyer, CEO of Innovate Finance, expects to see more innovators trying to tap into the unbanked and unrepresented consumer market. He said: "The firm Pockit, for example, gives customers an account and card that they can use to manage their money and make payments. Users can deposit money into their account at thousands of locations across the UK or have their salaries or benefits paid into their account. Pockit users also get cash back deals on the high street and online." So-called "challenger banks" are popping up and Monese is the latest to make waves.

Artificial intelligence (AI) advocates within enterprise IT teams must focus their efforts on solving "real business problems" if they are to convince the board to support the technology. That was the key message from BGL Group's insight and technology manager, who was speaking at Computing's Big Data and Analytics Summit 2016 this morning. Mike Maddock began by spelling out the differences between the public's perception of AI, and what it can now realistically achieve for the enterprise. He described Gartner's recent prediction that, by 2020, five per cent of financial transactions across the world will be carried out by AI, as a "bold claim". He also cast doubt on the usefulness of hypothesis-driven AI, as epitomised IBM's Watson, which achieved fame after its victory in the US gameshow Jeopardy.

Google DeepMind AI program AlphaGo defeated human Go world champion, Lee Sedol, in a five game series. The victory draws the week-long Challenge Series tournament in South Korea to a conclusion. This win marks a major milestone for artificial intelligence research, as Go is a fairly simple game, but has proven to be infamously difficult for computers to master due to the vast number of potential moves. Many Go players say the game primarily relies on intuition as a strategy. The victory is also significant, as it marks the first time in history that an AI program beat one of the best Go players in the world.

China has been the power engine of global economic growth since the Chinese Communist Party embraced free market economics some 30 years ago. What leveraged China's momentous success has been its people, or - to be more precise - the enormous number of cheap labour that migrated from the rural areas to the cities, some of which had to be built from scratch in order to accommodate millions of new residents. Low wages, foreign investment and open markets made China the manufacturing powerhouse of the world. But things have changed since those halcyon days of easy growth. Labour supply in China has become increasingly scarcer, a fact reflected in the almost exponential rise of wages since the beginning of the 2000s.

Deep in the heart of Imperial College, London, a computer is learning how to play Pac-Man. Like many humans, it struggles to get the hang of the classic 1980s video game at first. With time though, experience helps it decide which manoeuvres will allow it to evade the clutches of a relentless gang of animated ghosts. This is just one of dozens of artificial intelligence (AI) projects slowly transforming the UK into the global hub for a technology that elicits fascination and fear in equal measure. The point of teaching a computer to master Pac-Man is to help it "think" and learn like a human.

Your son is hanging out with friends behind the VR theatre when someone pulls a knife: they're being robbed. He hits a panic button on his phone, and a nearby drone is instantly dispatched. Less than 30 seconds later it's in the alley, sirens wailing and lights flashing, recording everything to be transmitted to the police. The technology for that scenario exists today. Add a dash of image recognition, or take it another step and put a taser (or a miniaturized version of the heat ray) on the device, and you have the automation of emergency response services.

With flashy AI technology like IBM's Watson and Google's driverless cars stealing headlines and outperforming their human competitors, it's clear that our economy is bracing for a fundamental shift in how we perform work. What's less obvious, however, is exactly what the workplace of the future will look like. A pair of Oxford researchers recently estimated that 47 percent of the total U.S. employment is at risk of being eliminated. On the other end of the spectrum, Mercedes announced it is trading out some of its production robots for human labor -- the machines could not keep up with the increasing options for customization. While these two camps continue to argue, in this article we'll explore three robotic trends that the prevailing media have missed in their coverage of the future of jobs -- trends that will hold true if we continue this automation trajectory.

If you have always wanted a cat, but can't choose between a plump and lazy tabby or a playful and slinky Siamese, a new online service could help. Experts have come up with an algorithm to match cats looking for a home with would-be doting owners, based on their personality. PawsLikeMe has been likened to eHarmony and hopes to make people's choices'more than fur deep' so less cats will need re-homing again. The Orlando Florida-based initiative built an algorithm to match dogs with new owners last year and since then, two million people in the US have used the'first ever human-to-pet matching algorithm' to find a furry friend. It claims to be 90 per cent accurate in predicting people-to-pet compatibility. Now it's raising money on Indiegogo to collect enough funds to roll out a version for cats.