Nary a soul is in sight in this picture-perfect image of automation. The machines do all the heavy lifting at this plant run by Asahi Breweries, Japan's top brewer. The human job is to make sure the machines do the work right, and to check on the quality the sensors are monitoring. The lines are up and running 96 percent," said Shinichi Uno, a manager at the plant. "Although machines make things, human beings oversee the machines." The debate over machines snatching jobs from people is muted in a country where birth rates have been sinking for decades, raising fears of a labor shortage. It would be hard to find a culture that celebrates robots more, evident in the popularity of companion robots for consumers, sold by the internet company SoftBank and Toyota Motor Corp. among others. Japan, which forged a big push toward robotics starting in the 1990s, leads the world in robots per 10,000 workers in the automobile sector -- 1,562, compared with 1,091 in the U.S. and 1,133 in Germany, ...

SoftBank Group Corp.'s humanoid robot Pepper has taken on various roles since its mass-market debut in 2015. The 1.2-meter tall robots with round white heads have been deployed to banks, sushi shops and nursing homes. Now, Pepper will don a Buddhist monk's robe. Kanagawa-based Nissei Eco Co. will offer Pepper -- billed as the world's first robot that can read emotions -- to chant Buddhist sutras at funerals, providing a cheaper alternative to human priests. The maker of molded plastic products, which has also been in the funeral business since 2000, recently launched a new venture targeting budget-minded customers interested in customizing funeral services.

Bill Gates has previously called for a tax on robots to balance the Government's income as jobs are lost to automation. He said the levy could help slow down the pace of change and provide money to hire additional employees in sectors that require people, such as health care. "Right now, the human worker who does, say, $50,000 worth of work in a factory, that income is taxed and you get income tax, social security tax, all those things," said Gates in February. "If a robot comes in to do the same thing, you'd think that we'd tax the robot at a similar level."

Welcome to the second installment of my mini-series, "Digital Health Around the World." As illustrated in the recent StartUp Health funding report, global digital health innovation and investment activity is accelerating, with many significant deals involving non-U.S.-based companies. The innovation trade winds are clearly blowing toward Asia, Europe and other parts of the world where difficult health infrastructure, outcomes, and demographic challenges are looming. Our second stop on this digital health world tour is Singapore. Singapore has a range of infrastructure and demographic challenges and opportunities that are attracting innovation activity (and investment).

People in Aomori Prefecture, especially in the western Tsugaru area, are known for their strong dialect, often leading outsiders to joke about needing a translator. But for health care professionals, the issue is no laughing matter. Misunderstanding patients could lead to incorrect medical decisions, and the longer it takes for doctors and nurses unfamiliar with the dialect to deal with patients, the longer the wait will be for others. In an effort to tackle the problem, Hirosaki University in Aomori and Tohoku Electric Power Co. this month started analyzing the voice data of 6,700 phone calls, covering 900 hours of calls the utility's customer center has fielded from across the Tohoku region. They have also started collecting conversation data from 12 residents in their 20s through 70s in the town of Ajigasawa located in the southwestern part of the prefecture.

Andrew Ng is one of the foremost thinkers on the topic of artificial intelligence. He founded and led the "Google Brain" project which developed massive-scale deep learning algorithms. In 2011, he led the development of Stanford University's main Massive Open Online Course (MOOC) platform. His course on Machine Learning would eventually reach an "enrollment" of over 100,000 students. That experience led Ng to co-found Coursera, a MOOC that partners with some of the top universities in the world to offer high quality online courses. Today, Coursera is the largest MOOC platform in the world.

Thompson sampling has impressive empirical performance for many multi-armed bandit problems. But current algorithms for Thompson sampling only work for the case of conjugate priors since these algorithms require to infer the posterior, which is often computationally intractable when the prior is not conjugate. In this paper, we propose a novel algorithm for Thompson sampling which only requires to draw samples from a tractable distribution, so our algorithm is efficient even when the prior is non-conjugate. To do this, we reformulate Thompson sampling as an optimization problem via the Gumbel-Max trick. After that we construct a set of random variables and our goal is to identify the one with highest mean. Finally, we solve it with techniques in best arm identification.

She joined as senior reporter in April 2014 having previously worked as assistant editor at Government Computing. This year has seen an artificial intelligence system beat professional poker players at a notoriously difficult game for machines to master. However this is just the latest round in the ongoing battle of human versus machine. In 2016 a system built by Google-owned AI company DeepMind called'AlphaGo' beat South Korean champion Lee Sedol at the fiendishly complex game'Go'. Sedol won just one game to AlphaGo's four across a five-match series.

The world was atwitter last week as President Trump crudely took North Korea to task over its nuclear program, a threat that has slowly but surely eclipsed the distractions of our imperialist wars in the Middle East. But according to tech mogul Elon Musk, humans face a far graver threat from something they use in their everyday lives and could be holding in their hands as they read these words: algorithmic artificial intelligence. Specifically, algorithmic AI that evolves into malevolent super-intelligent entities and seeks to end their meatbag parent species -- us. Late last week, Musk tweeted that AI is far more dangerous than North Korea, adding that he believes regulation will be necessary to contain the burgeoning technology. If you're not concerned about AI safety, you should be.

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.