Tanmay Bakshi fell in love with computers at five, released his first iPhone app at nine, and now at just 13 years old is working with IBM on artificial intelligence. The Canadian teen has become a global force in programming and commands more than 20,000 subscribers on his YouTube channel that teaches computer coding. He is currently in Australia for the IBM Watson Summit, which brings together experts in artificial intelligence to discuss how the technology can help people and businesses in the future. "If you think about it, really anything would fascinate a five-year-old, especially a computer," Tanmay told News Breakfast. "Just looking at the colours change on screen or even displaying my name on screen, whatever it might be, as a five-year-old that really fascinated me."

Data Skeptic takes a different take on how we review data--thanks to some healthy skepticism, listeners come out with unusual information and knowledge. The show alternates between interviews with industry experts, and mini episodes wherein the host explains data science tidbits to his non data scientist wife. The tone of this show is simultaneously intellectual and a bit off beat. It's fun, and easier to follow than highly technical podcasts. If you need a series with nice production quality and clear, friendly radio voices, this may be the one.

We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was organized jointly by Amazon and Heidelberg University for the first time at the Second Conference on Machine Translation (WMT 2017). The goal of the task is to encourage research on learning machine translation from weak user feedback instead of human references or post-edits. On each of a sequence of rounds, a machine translation system is required to propose a translation for an input, and receives a real-valued estimate of the quality of the proposed translation for learning. This paper describes the shared task's learning and evaluation setup, using services hosted on Amazon Web Services (AWS), the data and evaluation metrics, and the results of various machine translation architectures and learning protocols.

More than 70% of Australians play video games, and I'm one of them. With its spread from computers to TVs to mobile phones, the global games industry is now worth over $100bn, with an Australian market alone worth $3bn. But the value of games goes beyond just money. Interactive entertainment and the "serious games" that share lessons and skills have psychological and social benefits. We play to bond with other players, to build communities, to learn, to experience worlds beyond our imagination, and – as in the Dionysian theatres of old – to enjoy a temporary catharsis and channel feelings that otherwise preoccupy us into something vicarious.

Do you believe AI and robots taking over jobs is, as Elon Musk recently put it, the "biggest risk that we face as a civilization?" There's probably a research-backed prediction that supports your view. We've ranked them here, in order from "certain doom" to "possible utopia," for your convenience. How they got there: Carl Benedikt Frey and Michael A. Osborne, researchers at Oxford University, asked machine-learning experts to assess whether a sample set of occupations were "automatable" or "not automatable," which helped to inform how the presence of "engineering bottlenecks" that couldn't be easily automated, such as creativity and social engineers, factored into whether an occupation could be automated. They created a machine-learning algorithm to estimate a probability of automation across each US occupation.

Editor's note: This tutorial series was started in September of 2014, with the 8 installments coming over the course of 2 years. I only mention this to put John's first paragraph into context, and to assure readers that this informative series of tutorials, including all of its code, is as relevant and up-to-date today as it was at the time it was written. This is great material, both for anyone taking Andrew Ng's MOOC and as a standalone resource. One of the pivotal moments in my professional development this year came when I discovered Coursera. I'd heard of the "MOOC" phenomenon but had not had the time to dive in and take a class.

Not all of your college fun will involve keggers or games of ultimate frisbee. As the weather gets colder, you might have difficulty tearing yourself out of your dorm, in which case your entertainment options are limited: Host an in-room dance party, Netflix and chill or settle in for a little gaming. In addition to our favorite consoles (no, we couldn't choose just one), we've selected a handful of accessories and must-have titles for our back-to-school guide. Enjoy, and may you do a better job making friends with rival fanboys in real life than you do online. Engadget is the original home for technology news and reviews.

Jul. 25, 2017 - Tech titans Mark Zuckerberg and Elon Musk recently slugged it out online over the possible threat artificial intelligence (AI) might one day pose to the human race, although you could be forgiven if you don't see why this seems like a pressing question. Thanks to AI, computers are learning to do a variety of tasks that have long eluded them -- everything from driving cars to detecting cancerous skin lesions to writing news stories. But Musk, the founder of Tesla Motors and SpaceX, worries that AI systems could soon surpass humans, potentially leading to our deliberate (or inadvertent) extinction. Two weeks ago, Musk warned U.S. governors to get educated and start considering ways to regulate AI in order to ward off the threat. "Once there is awareness, people will be extremely afraid," he said at the time.

Last week, Elon Musk dashed off 125 characters announcing a remarkably ambitious plan to send Amtrak to an early grave. "Just received verbal govt approval for The Boring Company to build an underground NY-Phil-Balt-DC Hyperloop. NY-DC in 29 mins," he proclaimed in a tweet. Sign up to get Backchannel's weekly newsletter. Yet something about this particular moonshot seemed off.

This spring, as part of their coursework, four Stanford University students found themselves in Coronado, California, doing pushups on the beach and charging into a 61-degree surf while overseen by Navy SEAL trainers. They performed this extraordinary homework to better understand the process of inculcating recruits into the elite corps of military frogmen and women. The end result of their (literal) immersion was a solution to an inefficiency in evaluating prospective SEALS: the time-consuming process of analyzing the mountains of comments made about each candidate. Tackling the problem like the internet entrepreneurs they hoped to become, the students created a mobile app to streamline the process. Their reward was thanks from a grateful military establishment--and college credit. Dan Raile is a freelance journalist based in San Francisco.