Respondents were asked what they saw as the biggest area of opportunity for Big Data in comparison to traditional systems, with 62% agreeing that they consider real time analysis as the biggest area of opportunity today. Artificial intelligence (AI) has been capturing imaginations in the past year as Facebook announced plans for an army of 1.5 billion AI agents, and a Dutch-led consortium painted "The New Rembrandt" using machine learning. But perhaps equally surprising, enterprises are already looking seriously at machine learning for Big Data, having only made its appearance on the Gartner Hype Cycle in 2015. This development signifies how businesses are understanding the advantage of leveraging and building upon new Big Data technologies to produce valuable business insights.

What technologies are developers focusing on these days? According to the Evans Data Corporation Global Development Survey (PDF), the Internet of Things (IoT), robotics, and automobiles are three areas targeted by app-builders. Some 45 percent of the 1,441 surveyed developers said that IoT was very important to their overall app strategy; another 41 percent suggested that cognitive computing and artificial intelligence (A.I.) were very important. Among those developers whose primary focus is creating apps with machine-learning capabilities, the most-targeted categories for those apps included the Internet of Things (11.4 percent), professional, scientific and technical services (10 percent), and manufacturing (9.4 percent). In addition, these categories sometimes overlap.

Intel has launched the new-generation of the Xeon Phi processors that are aimed at the High Performance Computing (HPC) segment. Intel announced the standalone Xeon Phi processors in November 2015 and they are finally available to customers. All the new processors incorporate 16 GB of MCDRAM memory, which the company suggests is five times more power efficient as GDDR5. The Xeon Phi processors are the company's first bootable host processor and they are designed especially for highly parallel workloads. "It is also the first to integrate both memory and fabric technologies. A bootable x86 CPU, the Intel Xeon Phi processor offers greater scalability and is capable of handling a wider variety of workloads and configurations than accelerator products," says Intel.

I am working on skills and leadership models for the IT industry and we are already considering a programme for IT recruiters that goes half-way to what you call the singularity. I think we are some years off yet, and the smarter recruiters will use the shift towards AI in career planning and talent management to market advantage. Big data will make today's enterprise HR systems look like chalk and slates.

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The robot revolution might not begin with a rogue defense system declaring war on humanity, as Terminator predicted. Instead, it might take place when a bunch of robots finally decide that they're tired of picking up our stinky socks. OpenAI, an open source artificial-intelligence non-profit with 1 billion in funding from Elon Musk and Amazon among others, has announced details of its biggest project to date. The group intends to lay the groundwork for the creation of a robot that will "perform basic housework" in households around the world. In other words, the group intends to create software that will enable the proliferation of robot housemaids. DON'T MISS: Next year's iPhone may feature a futuristic design that makes Jony Ive's dream a reality "We're working to enable a physical robot (off-the-shelf; not manufactured by OpenAI) to perform basic housework," Elon Musk, Sam Altman, Ilya Sutskever, and Greg Brockton wrote in a post on the OpenAI blog.

The 4-1 victory of Deep Mind's AlphaGo over the Go world champion, Lee Sedol, was a landmark event in the development of Artificial Intelligence (A.I.). Advances in A.I. and robotics are transcending the realm of science fiction and are re-shaping the way we do business and interact with each other. Chartwell is delighted to work with leading experts in robotics and A.I., such as Raffaello D'Andrea and Paul Markillie, as well as top thinkers examining the economic, social and ethical implications of a roboticised future, such as Lucy and Stephen Hawking, Nick Bostrom, Calum Chace and David Rowan. For bookings, or to request a short list of tailored suggestions matched to your event, contact us for ideas.

If you're interested in working with artificial intelligence (A.I.) and machine-learning platforms, chances are good you've heard of OpenAI, the non-profit "artificial intelligence research company" funded by tech luminaries such as Tesla CEO Elon Musk and venture capitalist (and Gawker bestie) Peter Thiel. OpenAI has a unique mission: develop open-source A.I. software that's friendly to humanity (as opposed to SkyNet). Earlier this year, the organization launched OpenAI Gym, a toolkit for building reinforcement learning (RL) algorithms, which tech pros in the space may find useful as they build out their own A.I. projects. Now comes the next OpenAI initiative: a breakdown of "concrete problems in A.I. safety." OpenAI researchers, in conjunction with colleagues from Google Brain, have issued a paper that delineates how machine-learning systems can potentially go haywire.

Equity deals to startups in artificial intelligence -- including companies applying AI solutions to verticals like healthcare, advertising, and finance as well as those developing general-purpose AI tech -- increased nearly 6x, from roughly 70 in 2011 to nearly 400 in 2015. Q1'16 saw a new peak in deal activity to the category. So far in 2016 (as of 6/15/2016), over 200 AI-focused companies have raised nearly 1.5B in equity funding. Our analysis includes all equity funding rounds and convertible notes. Deals and dollars reached a new high in 2015.

Programmers worldwide are preparing to welcome our new robot overlords, after the University of Reading reported on Sunday that a computer had passed the Turing test for the first time. But what is the test? And why could it spell doom for us all? Coined by computing pioneer Alan Turing in 1950, the Turing test was designed to be a rudimentary way of determining whether or not a computer counts as "intelligent". The test, as Turing designed it, is carried out as a sort of imitation game. On one side of a computer screen sits a human judge, whose job is to chat to some mysterious interlocutors on the other side.