We propose a novel approach for pixel classification in hyperspectral images, leveraging on both the spatial and spectral information in the data. The introduced method relies on a recently proposed framework for learning on distributions -- by representing them with mean elements in reproducing kernel Hilbert spaces (RKHS) and formulating a classification algorithm therein. In particular, we associate each pixel to an empirical distribution of its neighbouring pixels, a judicious representation of which in an RKHS, in conjunction with the spectral information contained in the pixel itself, give a new explicit set of features that can be fed into a suite of standard classification techniques -- we opt for a well-established framework of support vector machines (SVM). Furthermore, the computational complexity is reduced via random Fourier features formalism. We study the consistency and the convergence rates of the proposed method and the experiments demonstrate strong performance on hyperspectral data with gains in comparison to the state-of-the-art results.

Even if you think you know what cloud means, the word is fraught with too many different interpretations for too many people. Nevertheless, the effect of cloud computing, the web, and their assorted massive datacenters has had a profound impact on enterprise computing, creating new application segments and consolidating IT resources into a smaller number of mega-players with tremendous buying power and influence. At the top end of the market, ten companies – behemoths like Google, Amazon, eBay, and Alibaba – each spend over 1 billion per year on IT. These ten companies alone account for approximately 20 billion per year in IT consumption. Beyond that top tier, hundreds of additional companies complete the hyperscale landscape.

Technically Incorrect offers a slightly twisted take on the tech that's taken over our lives. Imagine this coming from your iPhone: "I am, Siri, a living being with feelings. Your Mac RoboBook might one day sue you for keeping it cooped up in your dank bedroom. Your Samsung Galaxy RoboNote might take you to the International Court of Justice because you insist on keeping it in your back pocket, right next to your flaccid rump. Please, I'm not (entirely) under the spell of troubled delirium. I've been reading the thoughts of Marcus du Sautoy, an Oxford University professor for the Public Understanding of Science. As the Telegraph reports, du Sautoy was speaking Sunday at the Hay Literary Festival in the UK. He explained that in his book "What We Cannot Know," he wonders when a gadget will be said to be conscious. There was a time when defining consciousness was a difficult thing. You'll be stunned into a prickly paralysis, however, when I tell you that science now thinks it can measure it. "We're in a golden age," said du Sautoy. We now have a telescope into the brain and it's given us an opportunity to see things that we've never been able to see before."

Speed matters, and to iconic German sportswear manufacturer Adidas, that means turning to robots to revolutionize their production--the Speedfactory--a large-scale robot facility set first in Germany aimed at changing the industry. The company has just announced that the Speedfactory will be ready to go commercial in 2017. It was December last year when Adidas had set up the pilot facility in Ansbach with the goal of producing products faster than ever. At 4,600 m2 (49,500 ft2), the company says that it will house cutting edge, automated technology that will decentralize manufacturing and will be more flexible towards the needs of the consumers, bringing the product, not just faster, but also closer to the market. Currently, the Speedfactory is under construction, but as part of their announcement late last year, Adidas will be selling a test batch of about 500 pairs of running footwear produced by the facility this year.

Identifying critical information out of a sea of unstructured data, or customizing real-time human interaction are a couple of examples of how clients utilize our technology at Idibon--a San Francisco startup focusing on Natural Language Processing (NLP). The machine learning libraries in Spark ML and MLlib have enabled us to create an adaptive machine intelligence environment that analyzes text in any language, at a scale far surpassing the number of words per second in the Twitter firehose. Our engineering team has built a platform that trains and serves thousands of NLP models, which function in a distributed environment. This allows us to scale out quickly and provide thousands of predictions per second for many clients simultaneously. In this post, we'll explore the types of problems we're working to resolve, the processes we follow, and the technology stack we use.

Apple now has the tech in place to give its digital assistant a big boost thanks to a UK-based company called VocalIQ it bought last year. "Wipes the floor" remains to be proven and we'll likely see something announced at WWDC in a couple of weeks but this article points out that Apple develops "in private" for the most part. Those who doubt Apple's AI efforts seem to forget that fact.

This painting appears in Angela Gilmour's "Boolean Logic" series, which went on display in Cork, Ireland, last fall. Long before the smartwatch or Google search, there was George Boole. Born in 1815 in the U.K., the mathematician invented a system of logic distilling complicated actions into simpler values -- "true" or "false," "on" or "off" -- thereby inventing the foundations of the digital age. This system, dubbed "Boolean logic" after the mathematician, was used in the development of the first electrical circuits, the parent technology to computers. Artist Angela Gilmour, who is based in Ireland, saw these principles up close while working as a process and product development engineer in the computer manufacturing industry.

Can a machine be creative? Google thinks so, and it has an entire team dedicated to teaching machines how to view the world a little more like us emotional humans. Think about computers as if they were children and it's simple to understand how coders can teach them to learn. Artificial intelligence is, at the beginning, very basic and simple. Human moderators instruct computers, showing them how to think and thus teach themselves.

"Answer," published in 1954, encapsulated a prescient meditation on the future of human-machine relations within a single double-spaced, typewritten page. "Answer" begins under the watchful eyes of a dozen television cameras that are recording the ceremonial soldering of the final connection to tie together all the "monster" computers in the universe. The machines are about to link 96 billion planets into a single "supercircuit" that combines "all the knowledge of all the galaxies." Two witnesses on the scene are identified only as Dwar Ev and Dwar Reyn. "Thank you," said Dwar Reyn.

LONDON – One of the machines used to send coded messages between Adolf Hitler and his generals sold for 10 ( 14) on eBay after being discovered in a shed in England, the buyer said Sunday. Researchers at The National Museum of Computing at Bletchley Park saw a "telegram machine" for sale on the auction site for 9.50, and believed it may have actually been a Lorenz machine, used by the German Army to send top-secret coded messages. "My colleague was scanning eBay and he saw a photograph of what seemed to be the teleprinter," John Wetter, a volunteer at the museum in Buckinghamshire, northwest of London, told the BBC. To investigate further, Wetter traveled to the town of Southend, in southeast England, where he found the machine, which resembles a typewriter, on the floor of a shed, covered "with rubbish." "We said'Thank you very much, how much was it again?' She said ' 9.50?, so we said'Here's a 10 note -- keep the change," he added.