Jeff Bezos might be the world's biggest Star Trek fan. At one point, the Amazon founder and CEO wanted to call his e-commerce platform makeitso.com, in reference to Captain Jean-Luc Picard's catchphrase. In 2016, after years of begging Paramount Pictures, Bezos made a cameo as an alien Starfleet official in Star Trek Beyond. So, when Amazon set out to build the AI assistant Alexa, Bezos envisioned finally realising the Star Trek computer - a benign, omniscient assistant, available everywhere. "We really did think of it as the Star Trek computer, where it was ambient and you could simply say: 'Computer, beam me up,'" says Mike George, Amazon's vice president of Echo, Alexa and Appstore. Clad in a black v-neck jumper and jeans, the 20-year Amazon veteran has a booming laugh and a vague resemblance to both Bezos and Picard. George bounds into the office, all unwavering eye contact, full-body laughs and wrist-crunching high fives, his preferred form of greeting. I meet him, and most of the Alexa executive team, on an upper floor of Amazon's skyscraper, Day 1, in the Denny Triangle in downtown Seattle. From here, on a blue-sky morning, the Space Needle is dwarfed by the snow-capped mountains beyond. Both seem like inconsequential theatrical set pieces to the Amazon empire below.

The moon isn't nearly as exciting as it used to be. Once we convinced ourselves that it was mostly just a big dead pile of rock (which didn't take long), interest and the funding that comes with it moved to Mars and beyond. The biggest thing that the moon has going for it is that it's relatively close to us: Spacecraft can get there in just a few days, and it takes only a couple of seconds for a signal to get there from here. The European Space Agency has been trying to encourage a hybrid approach to lunar usefulness, combining science with business (like mining and tourism) to help promote exploration in general. In partnership with the SpaceTech program at the Graz University of Technology in Austria, ESA is encouraging startups to develop ways of making money on the moon.

There are over 6500 articles about AI/ML/DL written on medium, and if you would want to read them all, you would need to spend a full month reading 14 hours a day. So … this is why we have data and machines that can do this for us. After downloading 6 million posts from medium.com in the winter of 2016, i was able to filter just the posts that are tagged with either AI/ML or Deep Learning, and sort them by the number of recommends. In total, i got 6,546 articles, written by 3,528 users. All of this articles have a total of 153,567 recommends.

Computer scientists at University of Southampton are testing an artificially intelligent tool for predicting Premier League football results. The machine learning algorithm has managed to beat BBC football commentator Mark Lawrenson's predictions for two seasons in a row. The team now wants fantasy football fans to try to beat it. The algorithm could also help the players generate better teams, the researchers said. Fantasy football is a game in which users assemble an imaginary team of real-life footballers and score points based on the players' actual statistical performance during the season.

Demis Hassabis started playing chess at age four and soon blossomed into a child prodigy. At age eight, success on the chessboard led him to ponder two questions that have obsessed him ever since: first, how does the brain learn to master complex tasks; and second, could computers ever do the same? Now 38, Hassabis puzzles over those questions for Google, having sold his little-known London-based startup, DeepMind, to the search company earlier this year for a reported 400 million pounds ($650 million at the time). Google snapped up DeepMind shortly after it demonstrated software capable of teaching itself to play classic video games to a super-human level (see "Is Google Cornering the Market on Deep Learning?"). At the TED conference in Vancouver this year, Google CEO Larry Page gushed about Hassabis and called his company's technology "one of the most exciting things I've seen in a long time."

Tesla CEO Elon Musk has been warning about the risks of artificial intelligence and machine learning for some time now. The billionaire has said that developments in robotics will lead to disruption in the job market. Boston-area economists concluded earlier this year that human wages decline when robots are introduced. Jobs that are repetitive and can be taken over by AI like manual testing, infrastructure management, BPO and system maintenance will likely decline over the next five years. Some tech jobs could see the biggest impact from AI.

As PSD2 comes into effect, banks must adapt or prepare to be disrupted, says Paul Bowen, Banking Lead, Avanade Europe. "They all want to eat our lunch. Every single one of them", Jamie Dimon, Chief Executive of JP Morgan, stated in 2015, referring to the growing threat of Silicon Valley businesses to banks. And as the Second Payment Services Directive (PSD2) is coming into play early next year, his warning is becoming ever more significant. With the advent of PSD2 and Open Banking initiatives, the regulatory barriers that have kept non-bank competitors at bay are falling.

For decades, cable has roped in millions of customers like me with the promise of hundreds of channels and thousands of shows. But in my 15-plus years as a subscriber, there's one thing I've watched most: my bill. Every month I pay it, and every month I think of cutting the cord. The reason is that there's never anything good on--unless you're a fan of The Shawshank Redemption (which is probably on two channels at once), or one of the 19 shows based on storage units. Years of this feeling has brought people like me to a slow boil and caused them to pull the plug on their pay television.

One of the biggest challenges facing any insurance provider is the very real risk of insurance fraud. In 2014, UK insurers uncovered 130,000 fraudulent claims worth £1.32 billion across all insurance products. This danger shows no sign of slowing either, with professional and opportunistic insurance fraud numbers still on the rise. So, how can insurers effectively analyse data help to combat insurance fraud? A major insurance company has proactively combatted fraud before a fraudulent claim is filed or before they would even offer the customer a policy.