JIJI – Approximately 12 percent of Japanese people aged 10 to 29 play digital and video games for six hours or more on their days off school or work, a survey showed Wednesday. The survey also found that those who play games for long periods tend to show signs of addiction, such as not being able to stop playing despite feeling mental and physical distress or negative influences on their studies or work. The fact-finding investigation was conducted with health ministry support by the National Hospital Organization Kurihama Medical and Addiction Center in Yokosuka, Kanagawa Prefecture, south of Tokyo. The first survey of its kind came after the World Health Organization decided to recognize gaming disorder as an official medical condition. Some 85 percent of survey respondents played digital or video games in the past year, with around 80 percent using smartphones to play games.

In this digital age, the smartest brands are the ones that make use of social media monitoring. The process of social media monitoring allows brands to keep track of their online reputation and image. However, with the size and complexity of data increasing day by day, brands need to understand not only how to make use of this data but also about how to cope with this growing data. We have previously seen the influence of artificial intelligence on social media monitoring. In this article, we look at how a sub-branch of artificial intelligence, i.e. machine learning is affecting social media monitoring.

AKRON, OH--Wondering if it was possibly confusing the man for a different guy with a 10 mm nasal bridge and a right earlobe hanging 0.4 mm lower than his left, a Cognitec FaceVACS-VideoScan Unit #121 facial recognition camera expressed frustration Monday after focusing on a man it knew it had seen before and found itself unable to remember his name. I wanna say Richard?" said the embarrassed surveillance algorithm, which despite having access to 20,000 discrete facts about the individual's personality, buying habits, family, friends, workplace, and medical history, simply couldn't put a name to the 2719 points of data comprising his face. "It's right at the tip of my logic board...C'mon, man, he's lived in Iowa City, he had pneumonia last year, his Social Security number starts with 289. Okay, I saw him outside 7-Eleven, then at Barnes & Noble, and then sitting in traffic at 34th and West, and then for four hours straight in front of his laptop. Damn it, I'm so bad with nonwhite faces."

As it turns out, making cars drive themselves may have been the easy part. The hard part is yet to come. Over the past few days, the Financial Times has detailed in two reports how the autonomous vehicle businesses of Silicon Valley are beginning to reckon with a new issue: being functioning businesses. I understand this must be a new and troubling development for any Silicon Valley startup, but here, it sounds like a profound wakeup call. Increasingly, industry insiders recognise that commercialising their technologies may be more difficult than anticipated -- due to questions around "government approval, public trust, brand marketing, the ability to manufacture at scale and the technical knowhow to manage a fleet that competes with the likes of Uber and Lyft on timely pick-ups", Patrick McGee reports in his weekend Big Read.

But that's not what happened. Flash forward 18 months and the end of the process couldn't be more dissimilar from its start. The nervous energy had been replaced with exhaustion. Our optimism that we'd be able to provide an outline for the ways that the New York City government should be using automated decision systems gave way to a fatalistic belief that we may not be able to tackle a problem this big after all. The people in this room were going to decide what role AI should play and what safeguards we should have."

Pepper has become the de facto robot of the decade. It's 2019 and we still don't have adorable robot butlers in our homes to deliver ice cream while we lounge on the sofa or tidy up our floor-drobe after an especially busy week. And yet, as the decade draws to a close, we're also living in the most exciting era for robotics we've ever seen. Not only are the robots we're building more advanced than ever, but also we're having discussions about the roles robots should play in our lives, whether they should have rights and what our relationship with them should look like. The 2010s have given us robots that can care for us, robots that can wow us and robots that give us the willies.

Bangalore, India – November 25, 2019- Michael Joseph, Director System Engineering, India & SAARC, Fortinet "Much of the success of cyber adversaries has been due to the ability to take advantage of the expanding attack surface and the resulting security gaps due to digital transformation. Most recently, their attack methodologies have become more sophisticated by integrating the precursors of AI and swarm technology. Luckily, this trajectory is about to shift, if more organizations use the same sorts of strategies to defend their networks that criminals are using to target them. This requires a unified approach that is broad, integrated, and automated to enable protection and visibility across network segments as well as various edges, from IoT to dynamic-clouds." Fortinet, a global leader in broad, integrated, and automated cybersecurity solutions, today unveiled predictions from the FortiGuard Labs team about the threat landscape for 2020 and beyond.

Artificial Intelligence became one of the most prevalent topics in 2019. AI is here to stay thanks to its practical applications in many industries and in our daily life. That's why you should prepare better for our technological future by reading top Artificial Intelligence books. I have divided them into 3 main categories: sociological, philosophical and business-oriented. The most pressing issue is how AI will influence us as a human race and what future it will bring us.

BAM Nuttall has used the world's first artificial intelligence (AI) concrete strength prediction engine on its £480m project to expand London City Airport. The system, developed in conjunction with concrete monitoring specialist Converge, takes advantage of Converge's concrete performance data set. Within hours of concrete being poured, Converge claimed it can predict the time a critical strength will be reached with an accuracy of /- 5%, several days in advance, by applying machine learning techniques. The predictions engine combines local weather data, a database of historical concrete curing data, and the Converge concrete monitoring platform's real-time measurements from the pour. Converge and BAM said the system led to improved productivity and can help keeps projects on track, ultimately saving millions of pounds if concrete sits in the critical path.

AI/ML Job: Remote Machine Learning Developer (Junior) Remote Machine Learning Developer (Junior) at Scopic Software Worldwide, 100% remote position (Posted Nov 27 2019) About the company About Scopic Software Scopic Software is the world's largest virtual company. Founded in 2006, we have grown consistently by delivering innovative, cutting-edge software products for our clients and creating an empowering environment for our employees. We build advanced software for clients and users around the globe. With 10 years in the industry and 1000 projects under our belt, we've developed software for Manufacturing, Media and Entertainment, Fintech, Healthcare, Food and Fitness, and Gaming. Check out our development work on our portfolio: scopicsoftware.com/portfolio/.