We propose a novel methodology, forest floor, to visualize and interpret random forest (RF) models. RF is a popular and useful tool for non-linear multi-variate classification and regression, which yields a good trade-off between robustness (low variance) and adaptiveness (low bias). Direct interpretation of a RF model is difficult, as the explicit ensemble model of hundreds of deep trees is complex. Nonetheless, it is possible to visualize a RF model fit by its mapping from feature space to prediction space. Hereby the user is first presented with the overall geometrical shape of the model structure, and when needed one can zoom in on local details. Dimensional reduction by projection is used to visualize high dimensional shapes. The traditional method to visualize RF model structure, partial dependence plots, achieve this by averaging multiple parallel projections. We suggest to first use feature contributions, a method to decompose trees by splitting features, and then subsequently perform projections. The advantages of forest floor over partial dependence plots is that interactions are not masked by averaging. As a consequence, it is possible to locate interactions, which are not visualized in a given projection. Furthermore, we introduce: a goodness-of-visualization measure, use of colour gradients to identify interactions and an out-of-bag cross validated variant of feature contributions.

A Tesla electric-powered sedan stands at a Tesla charging staiton at a highway reststop along the A7 highway on June 11, 2015 near Rieden, Germany. SAN FRANCISCO -- Some Tesla owners have used the cars' Autopilot feature to take their hands off the wheel -- and film themselves doing anything but driving. YouTube videos uploaded since Tesla introduced the self-driving feature in October show drivers playing games, pretending to sleep, and in general, not holding the steering wheel. This kind of distracted driving is exactly what Tesla Motors Inc., under federal investigation after a man using Autopilot died from injuries sustained in a May crash, says drivers should not do. The Autopilot feature is designed to allow Teslas to cruise highways without drivers steering, braking or accelerating.

During his 15 years as president of the Service Employees International Union, Andy Stern was a controversial figure. He suffered his share of criticism from inside and outside the union. There was, however, no disputing his success in making SEIU the largest and fastest growing union in the country and a powerful political machine that was instrumental in electing President Obama and getting the Affordable Care Act passed. During Stern's tenure as national organizing director and president, he introduced and implemented strategies of industry-wide organizing and bargaining to counter the changing reality of employers who were becoming large and international. He took SEIU out of the AFL-CIO and formed a new labor federation called Change to Win, because he felt the mainstream labor movement was too conservative about organizing and limited its power by refusing to consolidate smaller unions into bigger and more powerful ones.

The result is that the massive computer power so harnessed helps us to analyse what has happened in the past and, with the use of predictive analytics techniques, opens a window leading to accurate predictions. Undoubtedly, artificial intelligence is fast becoming a major technology for prescriptive analytics, the step beyond predictive analytics that helps us determine how to implement and/or optimise optimal decisions. In business applications, it can assess future risks and quantify probabilities, giving us insights into how to improve market penetration, customer satisfaction, security analysis, trade execution and fraud detection and prevention, while proving indispensable in land and air-traffic control, national security and defence, not to mention a host of healthcare applications such as patientspecific treatments for diseases and illnesses. Typically, the giant search engine firm Google is a pioneer in the field of artificial intelligence, developing self-driving automobiles, smartphone assistants and other examples of machine learning, while it is no secret that Facebook founder Mark Zuckerberg and actor Ashton Kutcher recently invested 40 million in a project focusing on developing artificial brains. In science fiction films such as Matrix, we have seen how futuristic devices will facilitate facial recognition, interpret human comments and perform complex language translations.

Cannes Lions this year saw the ad industry expanding its creative capabilities. Over 13,500 delegates from about 90 countries descended on Cannes again this year hoping for a Lion in one of 17 categories. With awards honoring work from design to creative data to radio, the ceremonies reflected a complex industry drawing on a broader range of creative disciplines than in the past, but also facing unprecedented challenges in making campaigns work across channels. "There's never been so many channels or points of interactions, or agencies working on various parts of that," said Keith Weed, chief marketing and communications officer at Unilever. "It's important to make sure the brand experience does not get fragmented."

Echobox, a London-based AI startup targeting the publishing industry, has secured 3.4 million from Mangrove Capital Partners and LocalGlobe. The startup's AI service is used by publishers to enhance their reach and distribution on social media. The startup claims its tech can predict if an article will go viral and when the optimal time to publish content is. Axel Springer and Le Monde are among its clients. "Having worked at a well-known publisher, I was amazed by how they were investing vast resources in trying to perfect the science of content distribution in-house with data scientists and analytics tools to guide decision-making," said Echobox CEO Antoine Amann.

Artificial intelligence is being used all around us and in the automotive market especially. Companies are fighting it out to develop the next revolutionary product featured around autonomous driving. This is already becoming apparent with the rise in the number of artificial intelligence (A.I) devices being used throughout various industries. The IHS, who are a company specializing in producing reports and statistics, have been conducting reports based upon this field, and the numbers are quite staggering. They have projected that the use of A.I based systems will rocket from 7 million (2015 figure) to 122 million by 2025, with over 100% (some cars will have multiple A.I devices) of them being installed in new vehicles.

While everyone's eyes were on the Brexit vote and staggering economic implications this week, my mind was drifting to another crucial development within the EU. A draft European Parliament motion was recently put forward to begin to classify robots as "electronic persons." In a response to the proliferation of robotics and AI in the workplace, policy makers are attempting to stay ahead of the curve and preempt challenges they foresee around bureaucratic issues such as taxation and legal liability. As corporations rely more and more on automation and less and less on human workers, a new taxation structure will be required to ensure that governments still have funding flowing into their coffers. Moreover, as robotics become more sophisticated and we hand them increasingly critical tasks, issues around actor liability and insurance become very complicated.

In 2010, a startling rumor filtered through the number theory community and reached Jared Weinstein. Apparently, some graduate student at the University of Bonn in Germany had written a paper that redid "Harris-Taylor"--a 288-page book dedicated to a single impenetrable proof in number theory--in only 37 pages. The 22-year-old student, Peter Scholze, had found a way to sidestep one of the most complicated parts of the proof, which deals with a sweeping connection between number theory and geometry. "It was just so stunning for someone so young to have done something so revolutionary," said Weinstein, a 34-year-old number theorist now at Boston University. Mathematicians at the University of Bonn, who made Scholze a full professor just two years later, were already aware of his extraordinary mathematical mind.

Artificial intelligence (AI) that can understand and answer any work-related question it is asked has been made available in the UK for the first time. The computer software, called Starmind, uses machine learning to understand queries, then finds answers from previous staff conversations on a subject or tracks down experts in the company who are able to help. Its creators refer to it as "brain technology", adding its aim is to become a central knowledge bank within any company, an instant database of information that can be accessed by anyone. Starmind co-founder Pascal Kaufmann said of the technology: "Thousands of human brains connected can outsmart any machine today. "But if you can find ways for humans and AI-inspired technologies to autonomously collaborate rather than focusing on ways for them to compete, you can bring out the best in both." The algorithm within the system, which was developed in Switzerland, becomes more powerful the more it is used and is able to build a map of the people in a business and the areas in which all of them are experts, or are able to provide relevant information. "Starmind acts like an artificial hyperbrain that seamlessly exists at the core of a company," Mr Kaufmann added. "The algorithm is then fuelled by the know-how stored inside the brains of everyone that engages with the system." Several major companies in Europe, including UBS and Bayer, are using the system. A new version of the software - called Starmind NOW - has also been launched. It enables the software to be accessed outside a company intranet for the first time. Starmind says that makes the technology more "intuitive and seamless" to use. Former Microsoft executive Peter Waser has also joined the company as CEO. "It's a new technology that has never been available on the market in this form," he said. "Brain technology is the latest technology in the megatrend of machine learning and artificial intelligence.