A shining city on a hill is a sight to behold. But you wouldn't admire it so much if the city stopped maintaining its roads, electrical blackouts grew more frequent, electricity grew intermittent, and those gorgeous buildings started to fade under thick coats of grime. Modern businesses are building their shiny new applications on a foundation of machine learning. For any organization that hopes to automate distillation of patterns in feeds of big data, natural language, streaming media, and Internet of things sensor data, there's no substitute for machine learning. But these data-analysis algorithms, like the glimmering city, will decay if no one is attending to their upkeep.

Google DeepMind has come out with its AlphaGo artificial intelligence that can crack trevigintillion (1072) possible positions in the game Go and beat a human champion. "It was the first time a computer program has ever beaten a professional Go player," Demis Hassabis from Google DeepMind wrote in a blog. What makes Go a hard task in AI is the magnitude of complexity in the game. "That's more than the number of atoms in the universe, and more than a googol times larger than chess," wrote Hassabis. Google DeepMind tested AlphaGo against a three-time European Go champion.

As pointed out in the chapter 10 of "The Elements of Statistical Learning", ANN and SVM (support vector machines) share similar pros and cons, e.g. However, in contrast to ANN usually suffering from local minima solutions, SVM is always able to converge globally. In addition, SVM is less prone to over-fitting given a good choice of free parameters, which usually can be identified through cross-validations. In the R package "e1071", tune() function can be used to search for SVM parameters but is extremely inefficient due to the sequential instead of parallel executions. In the code snippet below, a parallelism-based algorithm performs the grid search for SVM parameters through the K-fold cross validation.

Editor's Note: Don't miss our new free on-demand training course about how to create data pipeline applications using Apache Spark – learn more here. Decision trees are widely used for the machine learning tasks of classification and regression. In this blog post, I'll help you get started using Apache Spark's MLlib machine learning decision trees for classification. In general, machine learning may be broken down into two classes of algorithms: supervised and unsupervised. Supervised algorithms use labeled data in which both the input and output are provided to the algorithm.

There are lots of conversations about the lack of diversity in science and tech these days. But along with them, people constantly ask, "So what? There are lots of ways to answer that question, but perhaps the easiest way is this: because a homogenous team produces homogenous products for a very heterogeneous world. This column will explore the products, research programs, and conclusions that are made not because any designer or scientist or engineer sets out to discriminate, but because the "normal" user always looks exactly the same. The result is products and research that are biased by design. Facial recognition systems are all over the place: Facebook, airports, shopping malls. And they're poised to become nearly ubiquitous as everything from a security measure to a way to recognize frequent shoppers. For some people that will make certain interactions even more seamless. But because many facial recognition systems struggle with non-white faces, for others, facial recognition is ...

Geoffrey Hinton splits his time between Google and academia. Hinton, known as the godfather of "deep learning," said the most powerful machines are still about a million times smaller than the human brain. They only have the equivalent of around a billion synapses (the connections between the neurons in the brain), compared to 1,000 trillion in the human brain. But machines are becoming more sophisticated every year. When asked to predict how long it will take before machines possess human-level abilities, Hinton said: "More than five years. I refuse to say anything beyond five years because I don't think we can see much beyond five years."

A new Federal Government report has outlined the future of Australia's workforce and revealed growing demand for professionals in STEM industries. The report by CSIRO and the Australian Computer Society, titled Tomorrow's Digitally Enabled Workforce, identified six megatrends. The trends include continued advances in automation and artificial intelligence; jobs will be more flexible and agile due to digital technology; a requirement for entrepreneurial skills; and an increase in skills and education requirements for many professions. While the report found that 44% of Australian jobs would be impacted by these changes, Andrew Johnson, CEO of the Australian Computer Society and one of the report's authors, said there are numerous opportunities for engineers. 'The intent of this report is to look at a 15- to 20-year timeframe.

San Francisco-based startup Fove has developed eye-tracking for virtual reality -- that kernel of technology many feel is key for the illusion of becoming immersed in a setting. Or use a death stare to shoot down virtual spaceships. Watch a movie of a forest or a room and be able to look around wherever you want. "It allows you to go inside the world that's behind the display," said Yuka Kojima, Fove's co-founder and a rare female chief executive in male-dominated Japan Inc. Fove, which comes from "fovea," the part of the eye with the sharpest vision, from "field of view," and the word's similarity with "love," has devised a way to use tiny infrared sensors inside headset goggles to monitor the movements of a wearer's pupils. It's a small company, founded in 2014, with offices in Tokyo, San Francisco and Los Angeles, and employing just 17 people.

SAN FRANCISCO, March 21 (Reuters) - Andy Grove, the Silicon Valley elder statesman who made Intel into the world's top chipmaker and helped usher in the personal computer age, died on Tuesday at age 79, Intel said. The company did not describe the circumstances of his death but Grove, who endured the Nazi occupation of Hungary during World War Two, living under a fake name, and came to the United States to escape the chaos of Soviet rule, had suffered from Parkinson's. Grove was Intel's first hire after it was founded in 1968 and became the practical-minded member of a triumvirate that eventually led "Intel Inside" processors to be used in more than 80 percent of the world's personal computers. With his motto "only the paranoid survive," which became the title of his best-selling management book, Grove championed an innovative environment within Intel that became a blueprint for successful California startups. Grove, who was named man of the year by Time magazine in 1997, encouraged disagreement and insisted employees be vigilant of disruptions in industry and technology that could be major dangers - or opportunities - for Intel.

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