At this year's CES, one of the largest global consumer electronics and consumer technology tradeshows, it was announced that augmented reality, virtual reality and artificial intelligence will be the primary disruptive consumer technologies for the next 20 years. In addition to this a recent report published by research company, Mintel, looked at how virtual and augmented reality technologies are entering our homes and stated that this will have an impact on how we shop, the brands we choose, and so on. You only have to think about the potential of drones delivering your goods versus the good old parcel delivery driver, to appreciate the impact this technology is likely to have on our lives and the environment around us. In 2016 Pokémon Go and Snapchat demonstrated how brands can effectively capture consumer attention and monetise augmented reality experiences at scale. Add to this recent news from Digi-capital, which showed that in the first quarter of 2016 investment in augmented reality and virtual reality grew to $1.1 billion (compared to the $700m total in 2015) and you can start to appreciate how these technologies are beginning to move centre stage.

Have you ever wondered how Facebook collects all the data it has to feed you with the content it presumes you'll like and keep you coming back for more? Well, now there's an app that can answer these questions. Available for free, Data Selfie is an open-source Chrome extension that helps you discover how machine learning algorithms track and process your Facebook activity, and gain insights about your personality and habits. TNW Conference won best European Event 2016 for our festival vibe. See what's in store for 2017. To accomplish this, the nifty extension monitors your Facebook interactions for patterns and then crunches the collected data into insightful reports.

The more we use electronic devices, be they handheld devices like smartphones and tablets or the larger laptops and desktop computers, the more we are frustrated by the inevitable crashes and freezes the devices suffer from time to time. And each time that happens, we curse the device manufacturer (or the office tech support) with doing a shoddy job. But in reality, the actual blame may not lay with the usual suspects at all. In fact, no one on the entire Earth may be at fault. At a Friday presentation in the ongoing annual meeting of the American Association for the Advancement of Science, Bharat Bhuva from Vanderbilt University in Nashville, Tennessee, blamed "these operational failures" on the "impact of electrically charged particles generated by cosmic rays that originate outside the solar system." In the morning presentation, titled "Cloudy with a Chance of Solar Flares: Quantifying the Risk of Space Weather," Bhuva said the millions of invisible, subatomic particles -- such as energetic neutrons, muons, pions and alpha particles -- that originate very far from our planet, and flow through Earth and our bodies (they have no known negative impact on living tissues) can alter bits of data stored in the memories of electronic devices when they interact with the integrated circuits the devices use.

Machine Learning is getting a lot more air time these days but are we actually sure what it is? It gives computers the ability to learn without being explicitly programmed" (Arthur Samuel, 1959). This is an old quote but it has held the test of time. But,how can computers "learn" – have we really reached the age of artificial intelligence where they will take over the world and make humans redundant? Let's explore the core of the definition: the ability to learn What this really means is there are a set of algorithms that, rather than simply following a static set of program instructions, they can make data driven predictions, or decisions through building a model. Supervised learning – The computer is presented with example inputs (training data) and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs. The "easiest" example of supervised learning is a decision tree – this uses a tree-like graph or model of decisions and ...

An agtech company from the Netherlands is about to make landfall on U.S. soil with a new technology it says could change the way farmers manage soil fertility. With its initiatives Springg and SoilCares, the company, Dutch Sprouts, works with Talend, a big data integration company, to blend a mix of hardware and software to gather and analyze soil samples around the globe. It all starts with a handheld scanner that allows farmers to analyze soils on the go, according to Angelique van Helvoort, head of marketing and communications with Dutch Sprouts. "You simply scan the soil and transfer it to our database," she says. "Within minutes, a readout and fertilizer advice is sent to the user's smartphone.

It takes bravery nowadays to predict the future. Indeed, if the events of 2016 have taught us anything, it's that unlikely outcomes can easily become a reality. This year marks the 20th year of our CEO Survey and it's been fascinating to look back over the surveys to see how the thinking of CEOs has developed, reflecting the environment around them. To their credit, CEOs saw a lot of the turmoil coming; back in 2009, 76% predicted a rise in political and religious tension and even then 46% believed that governments would become more protectionist. But successful predictions are relatively rare - and that's a salient lesson for people strategy. In 2015, our CEO survey showed that a third of business leaders were increasing their reliance on contractors and freelancers – signalling the emergence of the'gig economy'.

With a thrilling blend of customer feedback, digital interfaces, algorithms, and nuanced brewing, a British company has concocted four beers using artificial intelligence, and they are now available in the United Kingdom. The company, IntelligentX, created a survey system that uses Facebook Messenger chat bots to gather feedback from consumers on their taste preferences for beer. The data is fed into an algorithm to develop a beer recipe that is passed on to actual humans who brew, bottle, and share the beers. The whole system is like crowdsourcing a recipe for the perfect beer, and IntelligentX thinks it can master the process. A taste tester from Bloomberg sampled some of the beers and consulted with other testers to see how well the automated brewing intelligence (or ABI) system performed.

We provide a scheme for inferring causal relations from uncontrolled statistical data based on tools from computational algebraic geometry, in particular, the computation of Groebner bases. We focus on causal structures containing just two observed variables, each of which is binary. We consider the consequences of imposing different restrictions on the number and cardinality of latent variables and of assuming different functional dependences of the observed variables on the latent ones (in particular, the noise need not be additive). We provide an inductive scheme for classifying functional causal structures into distinct observational equivalence classes. For each observational equivalence class, we provide a procedure for deriving constraints on the joint distribution that are necessary and sufficient conditions for it to arise from a model in that class. We also demonstrate how this sort of approach provides a means of determining which causal parameters are identifiable and how to solve for these. Prospects for expanding the scope of our scheme, in particular to the problem of quantum causal inference, are also discussed.

Staying up to date with rapidly evolving technologies in the ecommerce and marketing industries can be a daunting task. With a slew of new technologies out there, it is also not easy to pinpoint which ones are worth the venture. We analyzed the top 3 most successful technologies impacting the ecommerce industry today. In 2016, total retail sales across the globe reached a whopping $22.049 trillion estimation, up 6 percent from the previous year, according to eMarketer forecasts. EMarketer also predicts that sales will top $27 trillion in 2020, despite annual growth rates slowing over the next few years.

Bill Gates thinks robots should get taxed just like humans, he said in a recent interview with Quartz. "Right now if a human worker does you know, $50,000 worth of work in a factory, that income is taxed," the billionaire said. "If a robot comes in to do the same thing, you'd think we would tax the robot at a similar level." Gates said robots can be good thing by doing certain types of labor done by humans so that people can focus in other fields where there is a shortage of workers. "If you can take the labor that used to do the thing automation replaces, and financially and training-wise and fulfillment-wise have that person go off and do these other things, then you're net ahead," Gates explained, "But you can't just give up that income tax, because that's part of how you've been funding that level of human workers."