There are places people leave and places people go. Naples might be Italy's third-biggest city, but it is losing those some of those people all the time. The city was once one of the industrial engines of Italy -- a history still evident from the husks and dirt of factories in parts of its centre -- and its promenades still hold some of the splendid grandeur of a city known for its contribution to the arts, travel, literature, food, football and crime. But in recent years, like many cities built on industry and manufacturing, some of that glory has faded away. And its young people have left, too -- giving Naples that sense of being a place you start, not where you end.

Alec Ross knows Trump country well. The former Obama administration staffer hails from the heart of coal country in Charleston, West Virginia. He grew up alongside the very people that President Trump likes to say Washington has left behind. As with Trump, Ross believes that government needs to do a better job lifting up these "forgotten men and women." Unlike Trump, Ross believes accomplishing that goal has little to do with sealing off the borders or reviving the coal industry at the expense of the world's climate.

This is a follow up to an article Per wrote last year, Machine Learning in a Week, on how he kickstarted his way into machine learning (ml) by devoting five days to the subject. Follow him on Medium and check out his archive. My interest in ml stems back to 2014 when I started reading articles about it on Hacker News. I simply found the idea of teaching machines stuff by looking at data appealing. At the time I wasn't even a professional developer, but a hobby coder who'd done a couple of small projects.

Swinburne University of Technology and the University of Melbourne are partnering with CA Technologies for a three year project to advance service virtualisation. Backed too by an Australian Research Council grant, the researchers will seek to find a method of using machine learning to automatically derive a service virtualisation model. "By using machine learning, development teams can write software without needing all the other systems within their environment. This will ultimately increase software development speed and reliability," CA explained in a statement. They will also look at ways of modelling a whole network of services, which takes into account their interdependencies.

There's something undeniably special in the way Meera Phillips looks at you when you speak. It's as if your words are the only words that will ever matter, whether you're talking about something silly or something serious. The 15-year-old knows the value of hearing what people say. That's because she's used to not being heard. Meera is nonverbal, living with a rare condition called schizencephaly that impacts her ability to speak.

"This challenge will pose a representative question to be answered by respondents using a completely automated system to sift through text reports and generate a finished intelligence product," the release stated on Tuesday. The purse consists of a top prize of $100,000 and multiple prizes of $30,000 for submissions from teams of high school students, the release explained. Entrants with the highest ranked submissions will be required to submit their source codes, the release noted.

This is the second part in a series where we analyze thousands of articles from tech news sites in order to get insights and trends about startups. So, if a sample mentions an IoT pacemaker startup, it should get the IoT tag in addition to the Health tag. Tagging the data was a similar process to the previous classifier, except that this time we took special care in tagging every sample with all the relevant categories. At this point, we are ready to repeat the same experiment we did in the previous post: classifying 100 articles and seeing what happens.

Backed by purpose-built HPC systems designed for maximum performance, HPE announces a comprehensive GPU-based solutions portfolio tailored to a new frontier of AI and deep learning capabilities. Explosive data growth and a rising demand for real-time analytics are making high performance computing (HPC) technologies increasingly vital to success. Organizations across all industries are seeking the next generation of IT solutions to facilitate scientific research, enhance national security, ensure economic stability, and empower innovation to face the challenges of today and tomorrow. HPC solutions are key to quickly answering some of the world's most daunting questions. From Tesla's self-driving car to quantum computing, artificial intelligence (AI) is enabling unparalleled compute capabilities and outmatching humans at many cognitive tasks.

Silicon Valley is Mike Judge and Alec Berg's biting comedy about the American tech industry, now in its fourth season. Every week, we'll be taking one idea, scene, or joke and explain how it ties to the real Silicon Valley and speaks to an issue at the heart of the industry and its ever-lasting goal to change the world -- and make boatloads of money in the process. In the fictional tech industry of HBO's Silicon Valley, the soul-crushing mundanity of grunt work is often treated as a punchline. Like many sitcoms about careerism and the slog of American professional life, it's considered an insult to have to do boring, seemingly meaningless tasks just because some higher power demands it. But on last night's episode, Silicon Valley highlighted a rather pernicious aspect of the tech industry that's currently serving as the foundation of modern artificial intelligence, shining a spotlight on a type of human labor often overlooked when we discuss the marvels of automation.

To whet your appetite further, we suggest you check out what a classical machine learning problem looks like in TensorFlow. In the land of neural networks the most "classic" classical problem is the MNIST handwritten digit classification. We offer two introductions here, one for machine learning newbies, and one for pros. If you've already trained dozens of MNIST models in other software packages, please take the red pill. If you've never even heard of MNIST, definitely take the blue pill.