A universal condition of future U.S. armed interventions is the dizzying amount of data that American forces will have thrust upon them at, each level of war and in every dimension of combat. The single most important thing the U.S. military can do to adapt to the Information Age is to channel the impending torrent of information, from a multiplicity of data sources, to relevant decision makers in useful forms. The face of battle in this era will still be defined by blood and hardship, endured by small groups of people surviving their way to the next objective, but in a much more complex context. That complexity will be apparent, often paralyzing, when flooding through a cornucopia of sensor systems. Computers will help stem the tide, but distributed human innovation, in the space between information and knowledge, is the only force that can contextualize the flow.

I wasn't a major aficionado of Hot Wheels growing up, however growing up I still remember asking dad to get me one. It was small and I wasn't particularly wild about it, however it was one more car to play with. A couple of years back, the startup Anki inspired the crowd at an Apple event by flaunting some toy race cars with AI capacity. One wouldn't expect the toy-car monster Hot Wheels to kick back and let a little startup take its turf. Model cars and track dashing are the bread and spread of Hot Wheels, yet they may look somewhat long in the tooth contrasted with conspicuous console amusements like Need for Speed or CTR.

One day the AIs are going to look back on us the same way we look at fossil skeletons on the plains of Africa. An upright ape living in dust with crude language and tools, all set for extinction. Ex Machina, a Hollywood blockbuster made on a 15 million budget, tells the story of a programmer who is invited by his employer, the eccentric billionaire Nathan Bateman who built a fictional search engine called Blue Book, to administer the Turing test to an android with artificial intelligence, which essentially determines whether a computer can trick a human into believing she is having a conversation with another human. Everything in our online life is indexed. Every idle tweet, status update, or curious search query feeds the Google database.

ARMONK, NY - 08 Sep 2016: IBM (NYSE: IBM) today revealed a series of new servers designed to help propel cognitive workloads and to drive greater data center efficiency. Featuring a new chip, the Linux-based lineup incorporates innovations from the OpenPOWER community that deliver higher levels of performance and greater computing efficiency than available on any x86-based server. The three new systems are an expansion of IBM's Linux server portfolio comprised of IBM's specialized line of servers co-developed with fellow members of the OpenPOWER Foundation. The new servers join the Power Systems LC lineup that is designed to outperform x86-based servers on a variety of data-intensive workloads. Early testing with Tencent, one of the world's largest Internet service providers based in China, has shown that a large cluster of the new IBM OpenPOWER servers was able to run a data-intensive workload three times faster than its former x86-based infrastructure.

Three military veterans once involved in the U.S. drone program have thrown their support behind a Yemeni man's legal fight to obtain details about why his family members were killed in a 2012 strike. The former soldiers' unusual decision to publicly endorse the lawsuit against President Obama and other U.S. officials adds another twist to Faisal bin Ali Jaber's four-year quest for accountability in the deaths of his brother-in-law and nephew, who he believes needlessly fell victim to one of the most lethal covert programs in U.S. history. The former enlisted service members told the U.S. Court of Appeals for the District of Columbia Circuit in a recent filing that they believe the 2012 drone strike serves as a case study of how mistakes frequently occur in the nation's targeted-killing program, where life-or-death decisions are based upon top-secret evidence. The veterans say they "witnessed a secret, global system without regard for borders, conducting widespread surveillance with the ability to conduct deadly targeted killing operations." Though the veterans did not disclose any personal knowledge of the strike that is alleged to have killed Jaber's relatives, they claim the military frequently labels the deaths of unknown victims as "enemy kills."

Since 1990, extreme poverty has been cut in half worldwide. But there are still more than 700 million people living on less than two dollars a day around the globe. The United Nations has made the elimination of poverty number one on its list of 17 Sustainable Development Goals by 2030, a challenge that may sound impossible but that a team of Stanford University researchers believe could actually be well within reach. That's because they've come up with a cost-effective method of getting over one of the most difficult, if not most obvious, hurdles toward reaching that goal on time. "Poverty is this big problem that everybody wants to solve, but you can't even begin to work on it if you don't know where the poor are," said Neal Jean, a doctoral student and lead author of the Stanford research.

Enterprises collect large amounts of data and analyze it to obtain a competitive advantage. Some are using machine learning techniques to create predictive applications for fraud detection, demand forecasting, click prediction, and other data-intensive analyses. Recent advancements in machine learning make it possible to go even further, bringing deep learning within reach of developers everywhere. Now, computer vision, speech recognition, natural language processing, and audio recognition applications are being developed to give enterprises a competitive advantage. Processing large amounts of data for deep learning requires large amounts of computational power.

One of the ironies of cloud computing is that, the more its cookie-cutter architecture allows it to scale, then the more it becomes possible to reintroduce diversity into that architecture. While cloud computing's early successes came from working out how to automatically manage serried ranks of identical general-purpose commodity computers, the vast scale that providers have now reached makes it economically and operationally viable to introduce pools of specialized computing into that infrastructure. Nowhere is this more pertinent than in the analysis of huge volumes of data, in applications such as big data and, increasingly, machine learning. In search of high performance in these applications, the leading cloud providers are investing in increasingly esoteric processor technologies, even to the extent of custom-building their own designs, as both Google and IBM are known to have done, while Microsoft and Amazon are thought to be doing the same -- perhaps also Apple and Facebook. Google's Tensor Processing Unit (TPU) is a case in point.

Artificial intelligence is set to challenge traditional technologies in financial services, if the startups that demoed at BBVA Open Talent in New York today are any indication. The BBVA Open Talent Challenge is part of Next Money NYC. Today's event is one of three regional finals, from which a few lucky winners will get the chance to work with BBVA. Consult Hyperion and NYPAY are also partners of the Next Money events, formerly known as Next Bank. More than half of the companies that presented in the first session used or mentioned AI, which is an umbrella term that covers a number of technologies used to manage data, often employing the ability to "learn" or change behavior based on trends in data.

We'd forgive you for immediately imagining a character out of I, Robot when we mention the term'artificial intelligence', but it does in fact describes when a machine perceives its surrounding environment and takes actions accordingly. Well, that's exactly what we do in the digital marketing world when we test and improve our campaigns. Once upon a time digital copywriters would write their own calls to action at the end of blog posts and direct users towards relevant blog content that they might be interested in based on the article they had just read. Well, personalised calls to action convert 42% better than generic ones. Now content suggestions can be computer generated and personalised to each reader based on their internet history, in the same way similar products may appear at the bottom of a product page.