Has a digital coup begun? Is big data being used, in the US and the UK, to create personalised political advertising, to bypass our rational minds and alter the way we vote? The short answer is probably not. A series of terrifying articles suggests that a company called Cambridge Analytica helped to swing both the US election and the EU referendum by mining data from Facebook and using it to predict people's personalities, then tailoring advertising to their psychological profiles. These reports, originating with the Swiss publication Das Magazin (published in translation by Vice), were clearly written in good faith, but apparently with insufficient diligence.

First of all, I will explain the reason for the post title. For those who have not seen the films, I summarize: "A group of four illusionists win year after year to the public with their incredible magic shows and even mocking the FBI. GSMA is a great illusionist and MWC is their principal magic show. We are invited year after year to visit an event with unique keynote speakers, an enormous list of exhibitors, amazing performances and a great LinkedInplace where we can meet in person some of our social media contacts. What else can we ask for? I know that it is very ruthless to compare the GSMA with illusionists and the MWC as their greatest magic show, but at least I see quite a few reasonable resemblances, you don t. If in 2015 I wrote " MWC 2015: Everything Connected, Tapas and Jamon", and I argued as one the reasons to attend MWC was the fact it was celebrated in Barcelona. In 2016, in my post "GSMA need to think how to reinvent MWC" I justify the reasons why the MWC needed to reinvent itself. One thing has become clear to me after many years attending MWCs, this is the world's biggest phone and mobile networks show, with manufacturers set to unveil a raft of new phone handsets and new technology. However, the GSMA had insisted on introducing more and more distractions like Internet of Things (IoT), Connected Living, Connected Car, AR/ VR, Robots. Maybe the reason is because Telecom operators do not have the DNA to change. Still, many telecom operators take a dim view of some of the aggressive moves being made by these peers, especially when it comes to business models based on commercializing customer data. "I expected to see less hype and a dose of common sense" Starting by the announcement of Spain's Telefonica to introduce a broad plan "4th Platform" to help both consumer and business customers keep greater control over their data rather than giving it away to web giants Google, Facebook and Amazon. "I expected to see more applications where IoT will become a lot less exciting, but more useful and profitable.

At its Google Cloud Next conference in San Francisco today, Google announced the launch of a machine learning startup competition, the winner of which will receive cloud credits and $1 million from well-regarded Silicon Valley venture capital firms. The program is open to startups in the U.S. that have raised less than $5 million and use machine learning software, in any industry vertical. Entrants' use of the Google Cloud Platform public cloud infrastructure is "encouraged but not required," according to the application form. The winning startup gets $1 million in Google Cloud Platform credits, which can cover the cost of computing and storage services as well as fully managed machine learning tools. Employees will get G Suite subscriptions, which includes Gmail, Google Drive, Google Calendar, and other applications -- and Google engineers will help startup employees improve their machine learning models.

The media often likes to proclaim "The Year of This" or "The Year of That." With the greater attention given to advancing capabilities in artificial intelligence and machine learning, it seemed like a no-brainer to declare 2017 "The Year of AI." However, in the interest of truth and the pursuit of all things real, it appears we may have been all wrong. According to a new report from big data management company Talend, 2017 will not be the year of AI, but will actually be the year of (wait for it) real-time analytics. This finding, which is based on a survey of 189 people who attended a Talend event in Paris last fall, may run counter to the prevailing wisdom that AI and ML are taking off in big ways, and that they are doing so right now.

What impact will artificial intelligence (AI) have on the workforce? Will smart machines really replace a large number of people in a variety of jobs? These questions have been on the minds of a lot of people of late -- especially as AI becomes even more advanced. Clearly the technology will take away the need for some functions that are now performed by humans. But there's good reason to believe that AI will actually create a lot of new jobs as well -- at least in some areas of the economy.

The weight of the automotive and tech industries is fully behind the move toward self-driving cars. Cars with "limited autonomy"--i.e., the ability to drive themselves under certain conditions (level 3) or within certain geofenced locations (level 4)--should be on our roads within the next five years. But a completely autonomous vehicle--capable of driving anywhere, any time, with human input limited to telling it just a destination--remains a more distant goal. To make that happen, cars are going to need to know exactly where they are in the world with far greater precision than currently possible with technology like GPS. And that means new maps that are far more accurate than anything you could buy at the next gas station--not that a human would be able to read them anyway.

Illegal, Unreported and Unregulated (IUU) fishing is becoming a major issue around the world . In general, IUU fishing is a broad term encapsulating many different scenarios (i.e. For the purposes of this blog, we'll just limit out discussion to Illegal fishing – i.e. fishing uses practices that are against the law, fishing in areas where it is not allowed, or taking animals which are not allowed to be taken. In this blog, I'm simply going to present some code demonstrating the simulation of a training dataset. The training dataset consists of 3000 fictional ships that engage in fishing activities. First, let's load up the libraries and set variables with our base categories Create names for our 3000 ships here.

Data science today is a lot like the Wild West: there's endless opportunity and excitement, but also a lot of chaos and confusion. If you're new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. With this O'Reilly report, machine-learning expert Alice Zheng takes you through the model evaluation basics. In this overview, Zheng first introduces the machine-learning workflow, and then dives into evaluation metrics and model selection. The latter half of the report focuses on hyperparameter tuning and A/B testing, which may benefit more seasoned machine-learning practitioners. Alice is a technical leader in the field of Machine Learning.

Robots are interacting with patients in medical facilities, handling material in warehouses, working in manufacturing, and helping ill children attend school--all with a hand from the Cloud. Indeed, by linking to the Cloud, robots are bringing homebound students into classrooms, hallways and cafeterias to socialize with their friends and continue learning--in school. "When you allow the student to actually be there, move around, go to classes and go to recess, you return a sense of control," said Daniel Theobald, chief innovation officer and co-founder of Vecna, a Massachusetts-based company that has created the VGo Robotic Telepresence. The VGo robot is essentially a virtual student who is present in the classroom and interacts in all the usual ways, even able to raise a hand (so to speak) to respond to questions in real time. But its creators hope you won't think of it as just a fancy Skype or FaceTime.

Google Cloud announces a Machine Learning Startup Competition in collaboration with venture capital firms Data Collective and Emergence Capital. The competition brings together promising early-stage startups using machine learning for an opportunity to receive up to $1M in Google Cloud Platform (GCP) credits and the potential to receive up to $1M of equity investment from our partners, Data Collective and Emergence Capital. Startups invited to participate in our final pitch-off event will also have an opportunity to meet and receive feedback from our supporting partners, a16z, Greylock Partners, GV, Kleiner Perkins Caufield & Byers and Sequoia Capital. In keeping with Google's spirit of openness, teams don't need to use GCP to be eligible for the competition. U.S.-based startups working in any sector -- from health to financial services and from retail to mobile apps -- are encouraged to apply.