A Google artificial intelligence program has beaten the European champion of the board game Go. The Chinese game is viewed as a much tougher challenge than chess for computers because there are many more ways a Go match can play out. The tech company's DeepMind division said its software had beaten its human rival five games to nil. One independent expert called it a breakthrough for AI with potentially far-reaching consequences. The achievement was announced to coincide with the publication of a paper, in the scientific journal Nature, detailing the techniques used.

I absolutely love where I'm at and grateful to be the steward of this brand and interesting niche space. Well, I don't reflect on achievements too often, quite honestly. Rather, I'm always striving to grow as a person and professional. But in the past year, I've experienced more growth in my skill-sets than ever before. I'm a self-taught web developer and have been growing my expertise in product development, UX and other facets of design.

It's a good trait to have for this particular demo. He's showing Tech Insider the capabilities of Hound, a free voice assistant app that's being released publicly for iPhone and Android on Tuesday. "What is the population and capital for Japan and China and their areas in square miles and square kilometers and also tell me how many people live in India and what is the area code for Germany, France, and Italy," Mohajer breathlessly says into his Android phone. If you were to ask Siri or Google Now even half of that query, you'd get nothing in return. Mohajer is pulling out the stops to show off the power of Hound, a voice recognition assistant his company SoundHound has been quietly building for the last 9 years.

Henri Waelbroeck seems to fit the popular image of the scientist transplanted into the world of high finance and hedge fund trading, the sort of stereotype found in books like "The Fear Index" by Robert Harris. Waelbroeck, director of research at machine learning-enhanced trade execution system Portware, was previously a professor at the Institute of Nuclear Sciences at the National University of Mexico (UNAM). His areas of expertise include: complex systems science, quantum gravity theories, genetic algorithms, artificial neural networks, chaos theory. The impression Waelbroeck conveys is one of precision. He explains that algorithms have grown in complexity since being introduced to the world of trading around 2000. This has made it increasingly difficult for traders to understand each vendor's full algorithm platform and how to optimally select an algorithm for each particular trade that comes in from a portfolio manager.

Whenever I read articles about data science I feel like there is some important aspect missing: evaluating the performance and quality of a machine learning model. There is always a neat problem at hand that gets solved and the process of data acquisition, handling and model creation is discussed, but the evaluation aspect too often is very brief. But I truly believe it's the most important fact, when building a new model. Consequently, the first post on this blog will deal with a pretty useful evaluation technique: lift analysis. Machine learning covers a wide variety of problems like regression and clustering.

If you were tweeting and drinking between July 2013 to 2014, your tweets might have been used as part of an experiment by computer science students at the University of Rochester. Nabil Hossain and colleagues trained a computer to identify alcohol-related tweets and used the data to monitor alcohol-related activity in a particular area. The research could help with understanding and responding to public health issues, according to the authors of the study. The researchers collected more than 11,000 geotagged tweets from New York City and Monroe County, where Rochester is located, in the northern part of the state. They filtered all of the tweets that mentioned alcohol-related words such as beer, drunk, hangover, wasted or party (as well as variations such as "druuuuuunk").

Variable selection is an important aspect of model building which every analyst must learn. After all, it helps in building predictive models free from correlated variables, biases and unwanted noise. A lot of novice analysts assume that keeping all (or more) variables will result in the best model as you are not losing any information. Sadly, that is not true! How many times has it happened that removing a variable from model has increased your model accuracy?

Wall Street, venture capitalists, technology executives – all have important reasons to understand the growth and opportunity of artificial intelligence, but the inherent vagueness of the term makes any single valuation extremely difficult. Indeed, the term "artificial intelligence" is notorious for having a relatively amorphous definition, itself. In order to put together an executive brief for market size and projected growth of AI, I've molded this article around (a) AI-related industry market research forecasts, and (b) a limited number of reputable research sources for further insight into AI valuation and forecasting, in addition to select and relevant quotes. Bear in mind that different market research firms define "artificial intelligence." To make this summary article more useful, we've quickly broken down all reports by source, definition / meaning of "artificial intelligence", valuation, and timeline.

CAPE CANAVERAL, Fla. – Fresh supplies shipped out late Tuesday for the International Space Station, where the shelves finally are getting full after a string of failed deliveries. Launching beneath the light of a nearly full moon, the unmanned Atlas V rocket provided late-night sparkle as it headed north with its precious cargo and paralleled the East Coast on its way to orbit. Orbital ATK's Cygnus capsule holds nearly 8,000 pounds of food, equipment and scientific research for NASA, including a commercial-quality 3-D printer anyone can rent and experimental robotic grippers modeled after the thousands of sticky hairs on geckos' feet. There's also a fire experiment that will remain on the Cygnus. Researchers will ignite a large-scale blaze, in a contained box, to see how it spreads in weightlessness.

United Launch Alliance launched an Atlas V rocket from Cape Canaveral that is headed towards the International Space Station. An Atlas V rocket launch carrying a Cygnus spacecraft bound for the International Space Station lifts off from Cape Canaveral Air Force Station in Florida on March 22, 2016. CAPE CANAVERAL -- An unmanned Cygnus supply ship is headed for a Saturday morning rendezvous with the International Space Station after an 11:05 p.m. ET Tuesday blastoff from Cape Canaveral Air Force Station aboard an Atlas V rocket. The 194-foot United Launch Alliance rocket blazed into a night sky brightened by a nearly full moon, carrying the Orbital ATK Cygnus packed with 7,500 pounds of food, equipment and science experiments. "These resupply missions are critical," Kenny Todd, NASA's space station operations integration manager, said before the launch.