CEO Satya Nadella's 1 billion security initiative yields fruit with the Azure Security Center, powered by the technology behind Azure Machine Learning. Microsoft CEO Satya Nadella late last year outlined the company's 1 billion investment in a new, holistic, operations-centric approach to addressing cybersecurity with the formation of its Enterprise Cybersecurity Group (ECG). Until this point, the Trustworthy Computing Initiative launched in 2002 by co-founder Bill Gates was largely at the center of the Microsoft security universe. That paved the way for the Security Development Lifecycle (SDL) -- the companywide blueprint for how all of Microsoft's software would be architected, built and maintained. Consequently, SDL is baked into the Microsoft delivery model, and new versions of products ranging from SQL Server to Windows are markedly more secure than the last.

Where MapReduce was about generating and processing data sets, TensorFlow is about harnessing them to build "smart" software programs that can do cool stuff. Machine learning already plays a role in applications ranging from Netflix recommendations to your Facebook feed to self-driving cars. In the years to come it will find an even broader range of applications--some ingenious, others inane. Google won't pocket a check when people use TensorFlow to build their own machine-learning software. But rest assured it will find fresh ways to profit from a world in which yet another of its core technologies has become ubiquitous.

In March 2001, futurist Ray Kurzweil published an essay arguing that humans found it hard to comprehend their own future. It was clear from history, he argued, that technological change is exponential -- even though most of us are unable to see it -- and that in a few decades, the world would be unrecognizably different. "We won't experience 100 years of progress in the 21st century -- it will be more like 20,000 years of progress (at today's rate)," he wrote, in'The Law of Accelerating Returns'. Fifteen years on, Kurzweil is a director of engineering at Google and his essay has acquired a cult following among futurists. Some of its predictions are outlandish or over-hyped -- but technology experts say that its basic tenets often hold.

Decades of research and billions of dollars have poured into developing artificial intelligence, which has crossed over from science fiction to gameshow novelty to the cusp of widespread business applications. Artificial intelligence is an area of computer science where computers are designed to think and operate much like a human brain, supported by advanced forms of computing and software. But it's only as smart as the amount of information fed into its memory banks. The more information, the smarter it gets. The greatest advancements have been demonstrated in the area of game playing, but AI is now showing its mettle in the business world. "People are starting to kick the tires, looking to see how it can help their business and the bottom line," said David Schubmehl, who follows the AI field for research firm IDC.

Economist Andrew McAfee concludes in his TedTalk "What will future jobs look like?" (already 3yrs old) that "The new'algorithm enabling' technology is here today, and banks could use it to fundamentally change the value proposition for their customers." "The future belongs to those that can recognize opportunities before they become obvious". Artificial intelligence, which encompasses these days all sorts of'algorithm enabling' technology, is creeping into our lives. Asset management and wealth management is no exception. Mentors at Fintech accelerators are advising entrepreneurs to drop the idea of creating the next Bloomberg and are suggesting a focus on AI finance.

Chip Somodevilla / GettyRobot parrots aren't the only reason to look over your shoulder. Artificial intelligence is going bananas right now. Google made headlines with it huge victory in the ancient game of Go a few weeks ago. And AI is entering into the marketplace at a historic rate, changing industries as complex as Wall Street in the process. If you get the feeling that we're at the start of a tidal wave, you might be right -- take it from Nvidia CEO Jen-Hsun Huang.

Twitter turned 10 years old this week. Associations, contrary to some dire predictions back then, have survived the past decade's rise of social media, in large part because not much actually changed about our basic desires for belonging, community, and collaboration. The tools are new, but it's still our fellow humans using them to connect. But what if, in the not-too-distant future, your association's target audience became less and less human? Perhaps then you might have some greater concern.

This blog discusses the applications of Monte-Carlo simulation methods by modeling real-world situations, explaining those using well known and often researched statistical distributions such as the Poisson distribution and then applying optimization models to solve a variety of business problems thus enabling managers to take decisions by moving beyond the usual methods and what-if scenario analysis. Very often business managers are faced with dealing with uncertainty in the real world, while they already know the decisions they need to make, provided such situations were a certainly. Such situations are a plenty – For instance: How many agents do we need in a call center? How much should I stock a particular product? How many doctors do we need in a hospital?

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Car traffic is a haphazard combination of moving bodies, flowing through channels and occasionally stopping to let other streams pass. If you think of traffic, not as people and goods in cars, but as a fluid, it makes no sense that cars spend so much time standing still. Yet traffic isn't a perfectly fluid system: it is made of multi-ton metal cars, piloted by people, and the consequences of imperfect movement range from damage to death. So we have traffic lights, and we have cars idling at traffic lights. But with autonomous cars, the future doesn't have to be that way.