We're about to take a big step down the proverbial rabbit hole – I hope you're prepared… They either believe that through the ages, man evolved from single-celled organisms or that a Supreme Being created this world, along with mankind and the rest of the cosmos. It's easy to see why so many people have so many opinions as it's hard to completely buy into either idea, seeing as they're both just theories. Neither is like the Law of Gravity or the Law of Inertia. And while evolution gets closer and closer to being proven every day – until that time – they're both only the opinions of much more educated men than me. The reason I bring this up is because there is an interesting side to the theory of evolution that most people tend to not think about.

In a recent interview, I was asked about the rapid improvements in artificial intelligence (AI) and whether they pose a significant threat to jobs in marketing, and, indeed, the wider workforce. To offer a logical response, we have to understand what we're discussing and why. A truncated, working definition of AI would be the automation of processes via machines able to perform cognitive tasks that were once performed by a human. Examples include computers built to defeat chess champions, operate vehicles, and perform specific, repetitive tasks. By no means does the term refer to an omnipotent, omnipresent, fully self-aware machine.

Interaction with the world around us should be as easy as walking into your favorite bar and getting your favorite drink in hand before your butt hits the bar stool. The bartender knows you, knows exactly what drink you like and knows you just walked through the door. Advances in AI help make new human-to-machine and machine-to-human interaction possible. Traditional interfaces get simplified, abstracted, hidden -- they become ambient, part of everything. Everyone's getting in the game, but few have cracked the code. We must fundamentally change the way we think.

This fall, an unusual vessel will begin sea trials off the coast of California. The 51-foot-long Boeing Echo Voyager will have no crew. It will glide underwater for days or weeks, quietly collecting data from the ocean floor to send back to crews on ships or on land. Ever since the start of the war in Afghanistan in 2001, the U.S. military has relied more and more on flying drones to take on dangerous air missions. But increasingly, drones are taking to the sea as well.

I joined Spotify in 2008 to focus on machine learning and music recommendations. It's easy to forget, but Spotify's key differentiator back then was the low-latency playback. People would say that it felt like they had the music on their own hard drive. In 2009 after a crazy amount of negotiation the music labels agreed to try it out as an experiment. Music distribution is a trivial problem now.

This tutorial will get you set up and running SystemML on the Spark Shell like a star. But first, to refresh your memory, let me remind you that I am on a quest to create a life-changing app! I am new to the world of data science and am currently tackling the challenge of building an app using Apache SystemML and Apache Spark one step at a time. If you haven't already, make sure to check out my previous tutorials, which start here. So far we've daydreamed about delightful data, complained about how hard it is to find good data, found good data, learned how to write Scala and NOW we will learn how to access SystemML from the Spark Shell.

Earlier this year, Adobe took the wraps off its new Adobe Marketing Cloud, touting new data science capabilities like Adobe Analytics' Segment IQ, which uses machine learning to help marketers gain deep insight into audience segments. On Wednesday, Adobe advanced Segment IQ another step with the release of Segment Comparison for Analysis Workspace. Segment Comparison for Analysis Workspace is the first in what Adobe promises will be a series of audience analysis and discovery tools within Segment IQ. It uses machine learning techniques to perform automated analysis on every metric and dimension to which you have access. Nate Smith, senior product marketing manager, Adobe Analytics, says this allows Segment Comparison to uncover the key characteristics of the audience segments that are driving your company's KPIs.

Research from Narrative Science claims confusion over the definition of artificial intelligence is holding it back, although 62% of enterprise respondents believe it will be place by 2018, reports Telecoms.com. Although this is an encouraging statistic, the report also highlights there is confusion over the definition of the technology itself. These statistics more than anything else highlight confusion, and ignorance to the artificial intelligence technology which is already present in their day-to-day lives. From Siri on Apple devices to Amazon's recommended purchases or Facebook's content recommendations, AI has been drip feed into the real-world of technology with few people realizing its impact. The functions mentioned are AI at one of its simplest versions, though IBM has been making progress with its Watson offering moving into more complex arenas, such as medical diagnosis, building management and weather modelling systems. But what is the real potential of artificial intelligence?

It's no secret that I love technology. From the domination of mobile to the latest in recruitment tools and gamification, and how video and live streaming is having an impact on hiring and training--changes are afoot that many of us couldn't have imagined 15 or so years ago. The reason this "tech meets HR" marriage is so exciting is how quickly the technology evolution has disrupted HR and enhanced the way HR professionals get things done. Now there's another big disrupter on the horizon, one that you would be wise to keep your eyes on: Artificial intelligence. In layman's terms, artificial intelligence (or, AI as it's commonly referred to), is an area of computer science where computers are "developed" to behave much the way humans do.

BBC Worldwide today announces a partnership with start-up Thoughtly, leaders in artificial intelligence solutions. With the rate and magnitude of content produced, consumed and disseminated growing the support of even more sophisticated technology is crucial. This, the latest partnership for BBC Worldwide's Insight team, offers an opportunity to explore how machine learning can support its commitment in gaining a deeper understanding of which genres are most in demand, and where. Following an initial trial, BBC Worldwide and Thoughtly have recently completed a more detailed piece of analysis – which includes looking at synopses and descriptions of programmes alongside data mining- to tease out more detail as how best to categorise individual titles. David Boyle, EVP Insight, BBC Worldwide said: "We are excited that Thoughtly can help us reveal patterns and trends previously unknown and hidden in our content. "Through working with Thoughtly, and utilising machine learning, we are building a deeper understanding of our content so that it can be paired with the most relevant audiences for both the BBC Worldwide and our partners." We are working together to answer some key analytical questions including: What are the recurring and elusive patterns that transcend the various genres in our catalogue? And how have themes evolved over the years - which have grown, declined, appeared and dissipated?"