Predicting the future is an imprecise art. But after years of crying wolf, one thing is becoming clear: automation is set to change the world of work forever. "It's not easy to measure automation precisely, but anecdotal and economic evidence indicate we have every reason to believe it will move faster and faster," says Martin Ford, global thought leader on automation at work and author of Rise of the Robots: Technology and the threat of a jobless future. Ford, who will be speaking at the upcoming Creative Innovation Conference, first became interested in an automated future while running a small software company in the 1990s. Back then, software still came on CD ROMs that were shipped to customers – a job that, while tech based, still required a human touch.

Japanese Prime Minister Shinzo Abe, dressed as Super Mario, holds a red ball during the closing ceremony of the Rio 2016 Olympic Games in Rio de Janeiro. Japanese PM Shinzo Abe's show-stopping appearance at today's closing ceremony in Rio, dressed as iconic game character Super Mario, already sets the tone for what lies in store. Japan is known internationally for its technological innovations, so Tokyo 2020 organizers are aiming to launch ambitious tech projects that will boost the economy and wow crowds. Tourists staying next to the Olympic Village in Tokyo's Odaiba neighborhood can choose, for example, to hang out with robot helpers of all sizes and sorts that offer up tips on the best transport, food and entertainment options in Tokyo. And that won't be the only place they'll encounter their robotic counterparts.

Aptonomy Inc. has developed drone technology that could make prison breaks, robberies or malicious intrusions of any kind impossible for mere mortals. Dubbing it a kind of "flying security guard," the company has built its systems on top of a drone often used by movie-makers, the DJI S-1000, a camera-carrying octocopter. To that skeleton, Aptonomy adds a new flight controller, and second computer to power day- and night-vision cameras, bright lights, and loudspeakers, among other things. And more importantly than the hardware features, Aptonomy has developed artificial intelligence and navigational systems that allow its drones to fly low and fast, avoiding obstacles in structure-dense environments, and detecting human activity or faces in the area, autonomously. A user can open up a browser, get onto the Aptonomy interface, click on a point on a map to send out a drone to a particular location, then watch that flight in real time, or review a recording of it later.

One of the best things about Chromebooks is that they're built to last. Thanks to automatic security and feature updates from Google, along with a lightweight browser-based operating system, longtime users may find that their laptops run as well, if not better, than they did on day one. But despite Chromebooks' theoretical longevity, it's possible for Google to cut their lives short. Per the company's End of Life policy, Chromebooks and other Chrome OS devices are only entitled to five years of feature and security updates. After that, Google doesn't guarantee that these systems will run safely or properly.

When we reviewed the Amazon Echo last year, we hailed it as the best home-based voice-controlled product at the consumer level. It's become even more versatile and powerful since then. It can control your home's smart lighting, lock your smart lock, play music, provide weather forecasts, order a pizza, and more. This affordable, always-on personal assistant can manage not only your home, but much of your digital life. It's so useful, we predicted many folks would want more than one Echo in their home.

This tutorial aims to provide an introduction to machine learning and scikit-learn "from the ground up". We will start with core concepts of machine learning, some example uses of machine learning, and how to implement them using scikit-learn. Going in detail through the characteristics of several methods, we will discuss how to pick an algorithm for your application, how to set its parameters, and how to evaluate performance.

This tutorial aims to provide an introduction to machine learning and scikit-learn "from the ground up". We will start with core concepts of machine learning, some example uses of machine learning, and how to implement them using scikit-learn. Going in detail through the characteristics of several methods, we will discuss how to pick an algorithm for your application, how to set its parameters, and how to evaluate performance.

How Artificial Intelligence Could Help Transform The Oil Industry (oilprice.com) There's another way to transform the oil industry. Give up, you old white bald guys. Electric is here, get used to it.

Last month, some people tweeting about Pokémon Go became unwitting subjects in an experiment that could presage a worrying new kind of online attack. Industry researchers trained machine-learning software to write tweets like a human to reply to some people using the hashtag #Pokemon, in a demonstration of how advances in software that understands language could be used to trick people online. Roughly a third of people targeted by the software clicked on a benign link sent along by the software to test how convincing it was. That's much higher than the 5 to 10 percent success rate typical for automated "phishing" messages aimed at tricking people into clicking links to deliver malware or steal passwords, says John Seymour, a senior data scientist at security company ZeroFOX. The machine-learning system comes close to the roughly 40 percent success rate of "spearphishing" messages handcrafted to trick a specific person, he says.