"Just over 50% of developers engaged in AI projects now solely implement machine learning in those projects." Evans Data Corp. has released a study that estimates some 6.5 million developers worldwide are already using a purely AI approach, pivoting away from traditional rules-based techniques. The study, Evans Data's Global Development and Demographics Study, also reveals strongly growing momentum, with another 6 million developers expected join the ranks of AI/machine learning before the end of the year. "There's been a huge uptake for AI and ML technologies by developers." said Evans Data CEO Janel Garvin about the study's results. In specific, Evans Data estimates 29% of developers worldwide (6,452,000) are today using some form of AI or ML.

Editor's Note: The following blog post is a summary of a presentation from RFUN 2017 featuring Staffan Truvé, CTO and co-founder of Recorded Future, and Chris Poulin, principal/director at Booz Allen Hamilton. Artificial intelligence is about constantly trying to push the technology barrier -- once you actually succeed, however, it can be challenging to find the next new territory. There are a multitude of tricky questions to answer in dealing with artificial intelligence, so fortunately, there is no shortage of work in the field. Artificial intelligence is a complex contradiction in that it simultaneously deals with solving simple problems that are just repetitive, human tasks, while at the same time trying to push machines beyond human capability. Staffan Truvé, CTO and co-founder of Recorded Future, recently shared his expertise at the company's annual threat intelligence conference in D.C.

New technologies generate new buzzwords. Artificial intelligence (AI) as a technology and term has been around for decades, but only recently seems buzzworthy. Unfortunately, some vendors are associating the buzzword with their products without having any real AI. Or to be charitable, they stretch the limits of what can be considered AI. Maybe they don't really understand what AI is, or maybe the marketing team cajoled them into it.

One of the most important jobs of any national leader is to quit. National liberation heroes, from George Washington to Nelson Mandela, who stepped down without being forced to, ought to be venerated for that as much as for any good they accomplished while in office. Generally, rulers do not give up power unless they have to. In Africa, peaceful transfers of power are rare enough that a billionaire has set up a generous annual prize to reward leaders who step down voluntarily; many years it goes unclaimed. Around the world, cases like Bashar al-Assad, willing to watch his country crumble rather than give up power over it, or Robert Mugabe, forced out by his own military after 47 years, are more common.

IBM is trying to woo and support new developers as the battle for skilled AI talent ramps up. AI is among the hottest technologies on the horizon, and sub-topics like machine learning have emerged as a must-have for many new applications. IBM and others want to empower developers with tools to simplify the creation of AI-powered apps. Oracle released the long-awaited Java 9, but what will this mean for developers? Uncover how Java 9's improvements aim to simplify the development process.

Rich Rogers, a senior vice president of product and engineering at Hitachi Vantara, envisions a data center in which AI-driven management software (some or all of it cloud-based) will monitor and control IT and facilities infrastructure, as well as applications, seamlessly and completely across single or multiple sites. Compute, power, storage, networking and cooling operations will flex dynamically to achieve maximum efficiency, productivity and availability. Human operators, meanwhile, will be free to do what they do best: plan new capabilities and innovate improvements. "IoT and AI will enable data center issues to be root-caused and resolved automatically by software," Rogers said. Data center administrators will no longer be woken-up at night to troubleshoot outages.

Zoning codes are a century old, and the lifeblood of all major U.S. cities (except arguably Houston), determining what can be built where and what activities can take place in a neighborhood. Yet as their complexity has risen, academics are increasingly exploring whether their rule-based systems for rationalizing urban space could be replaced with dynamic systems based on blockchains, machine learning algorithms, and spatial data, potentially revolutionizing urban planning and development for the next one hundred years. These visions of the future were inspired by my recent chats with Kent Larson and John Clippinger, a dynamic urban thinking duo who have made improving cities and urban governance their current career focus. Larson is a principal research scientist at the MIT Media Lab, where he directs the City Science Group, and Clippinger is a visiting researcher at the Human Dynamics Lab (also part of the Media Lab), as well as the founder of non-profit ID3. One of the toughest challenges facing major U.S. cities is the price of housing, which has skyrocketed over the past few decades, placing incredible strain on the budget of young and old, singles and families alike.

Just as the Industrial Revolution transformed the world during the 18th and 19th centuries, we are facing the dawn of an equally far-reaching artificial intelligence or AI revolution that will be measured in years rather than decades. AI has reached the point where it is capable of surpassing the decision-making of humans in many situations; consistently, accurately, 24/7 and based on more facts. But why now and how do businesses harness this capability? AI has been around since the 1960s; only now is the confluence of three key factors coming together. Firstly, AI has languished as a "disembodied brain in a jar", isolated from the real world.

In December, Oakland-based U.S. District Judge Haywood Gilliam blocked the changes to President Barack Obama's health care law. The judge said the Trump administration failed to give the notice and comment period required before implementing the changes.

We've been promised so much over the years, but now AI is ready to deliver. From connected cars and smart homes, through to improved ambient assisted living (AAL), AI is the common thread that unites them all. Analysts predicted that worldwide revenues for cognitive and artificial intelligence (AI) systems will reach $12.5 billion in 2017, an increase of 59.3% over 2016, and that investment will continue that trajectory, achieving a compound annual growth rate (CAGR) of 54.4% through 2020 when revenues will be more than $46 billion. The analysts might just be right this time too, as the supporting base of technology has caught up with the demands and opportunities offered by improved AI. A clear example was at CES 2018, one of the biggest annual showcases of technology, which lit up Las Vegas in early January, and much of the major noise this year was around AI and associated devices.