Between the Terminator movies, Ava from'Ex Machina', Google's AlphaGo beating the world's best human Go players, machines mimicking Rembrandt's style to paint portraits, debates about morality and privacy, and Stephen Hawking's warnings about the consequences of intelligent machines manned by idiot humans; it's no wonder that Artificial Intelligence (AI) has already made people a little uncomfortable. In the marketing world, it's caused the customary outbreak of confusion. Thus resulting in a series of obtuse declarations like "AI will change everything. EVERYTHING!" that are typical of the industry. Any time anything new threatens to upset business as usual, comrades in the marketing and advertising industry especially lunge headlong into an existential crisis. For instance, "Will AI make the creative kind obsolete?"

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The researchers applied machine learning methods to special type of MRI called arterial spin labelling imaging.

Tesla Motors's statement last week disclosing the first fatal crash involving its Autopilot automated driving feature opened not with condolences but with statistics. Autopilot's first fatality came after the system had driven people over 130 million miles, the company said, more than the 94 million miles on average between fatalities on U.S. roads as a whole. Soon after, Tesla's CEO and cofounder Elon Musk threw out more figures intended to prove Autopilot's worth in a tetchy e-mail to Fortune (first disclosed yesterday). "If anyone bothered to do the math (obviously, you did not) they would realize that of the over 1M auto deaths per year worldwide, approximately half a million people would have been saved if the Tesla autopilot was universally available," he wrote. Tesla and Musk's message is clear: the data proves Autopilot is much safer than human drivers.

The jobs at highest risk are those in the transport and retail sectors. In fact the transport sector could have 1.5 million jobs, that's 74% of the current workforce, replaced with automation and 60% of retail. Not surprising when you see how popular online shopping has become - who needs a high street shop? Almost 750,000 have been lost in manufacturing to automation just in the last 15 years alone. Even Stephen Hawking the renowned scientist fears that AI or Artificial Intelligence could eventually spell the end of the human race.

The Turing test, developed by legendary computer scientist Alan Turing and used to test the artificial intelligence of computers, has a major flaw. A new study, published in the Journal of Experimental and Theoretical Artificial Intelligence, points out that the test, which was devised in the 1950s, could be successfully passed if the computer pleaded the Fifth Amendment and remained silent. Authors Kevin Warwick and Huma Shah from Coventry University argue that a machine could plausibly pass the test by saying very little, or nothing at all. Previous attempts at defeating the Turing test have seen computers pretend to be children, but no matter how great their general knowledge, they are often unable to convince a human interacting with them (over typed messages) that they are also a human. A critical point raised by the study is how the Turing test is based around a machine being discovered as a human based on what it does wrong, rather than what it does right.

It's a sad commentary that the public has become so technophobic that we are even taking these sci-fi claims seriously. The view that smart machines will kill us overstates the pace of technological progress, particularly because the processing power of silicon computer chips is slowing down and progress in AI outside of deep learning is relatively modest. Moreover, machines and the human mind are completely different systems, and even major advances in computing are highly unlikely to produce a machine with humanity's intellectual capacity, imagination, or adaptability. As MIT computer scientist Rodney Brooks puts it, "We generalize from performance to competence and grossly overestimate the capabilities of machines -- those of today and of the next few decades." Just as importantly, even if human-level intelligent machines could be built, which is unlikely, they will remain under the control of humans, because we would never build them unless they are largely safe, with the benefits outweighing the costs (just as we do with all technologies in the marketplace).

Under Armour was founded on a simple idea: Make athletes better. To do that, it's turning human performance into a big data problem. The company is betting on the notion that the right hardware, the biggest dataset, a lot of machine learning, and powerful motivational tools can make everyone better, faster, and stronger. It's betting that technology doesn't exist solely to make us lazy, to bring everything to our door with the push of a button. The centerpiece of that bet is a 400 kit, announced today, called Healthbox, that provides a scale, an activity tracker wearable, and a chest strap for measuring your heart rate. The company also is updating Record, its mobile app, making it a 24/7 real-time barometer of your fitness and health. These tools, combined with three apps Under Armour has purchased in recent years, provide the most comprehensive ecosystem of fitness products yet made.

Google announced today that it has acquired Paris-based Moodstocks, a startup that has developed machine learning technology to bolster the image recognition features on smartphones. "We continue to pursue our machine learning and research efforts," wrote Vincent Simonet, head of the research and development team for France Google, "and Moodstocks is the latest proof of our commitment to this area." Today, we're thrilled to announce that we've reached an agreement to join forces with Google in order to deploy our work at scale. We expect the acquisition to be completed in the next few weeks. Our focus will be to build great image recognition tools within Google, but rest assured that current paying Moodstocks customers will be able to use it until the end of their subscription.

To learn more about the state of AI today and where we might be headed in coming years, download the free report "What is Artificial Intelligence?," by Mike Loukides and Ben Lorica. There are four basic ingredients for making AI: data, compute resources (i.e., hardware), algorithms (i.e., software), and the talent to put it all together. In this era of deep learning ascendancy, it has become conventional wisdom that data is the most differentiating and defensible of these resources; companies like Google and Facebook spend billions to develop and provide consumer services, largely in order to amass information about their users and the world they inhabit. While the original strategic motivation behind these services was to monetize that data via ad targeting, both of these companies--and others who are desperate to follow their lead--now view the creation of AI as an equally important justification for their massive collection efforts. While all four pieces are necessary to build modern AI systems, what we'll call their "scarcity" varies widely.