Analysts have estimated that one third of Amazon's sales come via their recommendation system. Where do you think they got this recommendation system?? From visualization to data preparation, from the creation of machine learning models to putting these models in production -- all of this generates a lot of plumbing to connect all the parts. These pioneers broke the CLIENT-PROVIDER RELATIONSHIP that exists INSIDE companies between the business, IT and analytics teams. They found a way to create a predictive application "dream team" with all the key players focused on building the best product possible.

When the term "artificial intelligence" – better known as "AI" – was initially coined, it was thought that humans (carbon based life forms) had "real" intelligence while the best a machine's intelligence (to the extent they had any) could get was "artificial". As I work with companies that are leading major machine learning, algorithms, and AI initiatives I'm convinced that we're ushering in a new golden age of AI but one that might need some terminology refinements. IBM, one of the leaders in AI's new golden age, talks about how cognitive computing will take us to the promised land where machines aren't just augmenting our calculation skills but really recognize patterns without being taught by humans, sift through data without us teaching them, digitize our experiences without our involvement, strike up conversations, drive our cars, and make decisions just like humans do. With the rapid progress that we've been making, much of which I'll get to see first-hand when I attend the next week, I've been wondering whether we should move away from the term artificial intelligence to just silicon intelligence. We're carbon-based so our intelligence could be called carbon Intelligence (CI) not "real intelligence".

This book includes a selection of research papers in robot control applications, and presents several tools and mathematical concepts that allow the development and operation of robotic systems. The description of projects using robotic systems in areas such as vision, navigation, path planning, trajectories, non-holonomic systems, mobile robotics, robot control with very specific structures, as well as artificial intelligence systems is pointed out. The development of different ideas in control systems that are useful and hopefully enriching for the reader are also presented in this book.

In his prescient work on investigating the potential use of information technology in the legal domain, Lawlor surmised that computers would one day become able to analyse and predict the outcomes of judicial decisions (Lawlor, 1963). According to Lawlor, reliable prediction of the activity of judges would depend on a scientific understanding of the ways that the law and the facts impact on the relevant decision-makers, i.e., the judges. More than fifty years later, the advances in Natural Language Processing (NLP) and Machine Learning (ML) provide us with the tools to automatically analyse legal materials, so as to build successful predictive models of judicial outcomes. In this paper, our particular focus is on the automatic analysis of cases of the European Court of Human Rights (ECtHR or Court). The ECtHR is an international court that rules on individual or, much more rarely, State applications alleging violations by some State Party of the civil and political rights set out in the European Convention on Human Rights (ECHR or Convention).

Artificial intelligence, such as neural networks, deep learning and predictive analytics, has the potential to transform radiology, by enhancing the productivity of radiologists and helping them to make better diagnoses. This short report from Signify Research presents 5 reasons why artificial intelligence will increasingly be used in radiology in the coming years and concludes with a list of the barriers that will first need to be overcome before mainstream adoption will occur.

Artificial intelligence programs have beaten chess masters and TV quiz show champions. Two exchange operators have announced plans to launch artificial intelligence tools for market surveillance in the coming months and officials at a Wall Street regulator tell Reuters they are not far behind. Executives are hoping computers with humanoid wit can help mere mortals catch misbehavior more quickly. The software could, for instance, scrub chat-room messages to detect dubious bragging or back slapping around the time of a big trade. It could also more quickly unravel complex issues, like "layering," where orders are rapidly sent to exchanges and then canceled to artificially move a stock price.

YOKOHAMA – The top executive overseeing connected vehicles at Nissan and Renault believes the benefits of developing a common technology for connectivity within the Japanese and French auto partnership outweigh the risks of sustaining huge damage from a possible defect or cyberattack. Ogi Redzic, senior vice president at the Renault-Nissan Alliance, oversees such connected services, including staying connected with family, navigating best routes and remote control of vehicles -- an area where all the world's automakers are trying to gain an edge. Redzic, formerly of Motorola and Nokia, was tapped for the post at the alliance earlier this year. He told reporters Tuesday at Nissan's Yokohama headquarters that the alliance has begun hiring 300 people to build such software applications for future cars, in addition to 300 employees at Nissan Motor Co. and 300 at Renault SA already working on the effort. Nissan-Renault hopes to lead in connected vehicles, in addition to green cars and self-driving cars, the two other increasingly vital auto technologies.

You might well have been responsible for one of the biggest-ever attacks on the internet last week. And you're probably going to do it again. A huge network of webcams and other internet of things devices is being built that can be used as perhaps the biggest cyberweapon ever created. And those people who own the devices probably don't even know that they're infected with the malicious code that allows them to be used that way. To be involved in the attack, you wouldn't need to do more than buy a common webcam – perhaps for keeping an eye on your house, or a pet that lives in it – or any other connected home or internet of things device.

The ability to think is one of the things that marks us out as human, "I think therefore I am," as the philosopher René Descartes put it. But what if machines were able to mimic human thought processes? This is the basic premise behind cognitive computing. In order to replicate human thought processes, cognitive computing uses techniques like pattern recognition, data mining and natural language processing. The ultimate goal is to be able to make computer systems that are capable of solving complex problems without needing human assistance to prompt them in the right direction.

Customer satisfaction is the bread and butter of every customer service team. We all want to make our customers happy, and satisfaction becomes both the reason we show up to work and barometer by which we measure our success. Every interaction offers a business the chance to leave a customer feeling good, helping to build a relationship for the longer term. Yet some customer interactions have a mercurial quality and end up in a different place than they began. If you knew what direction customer interactions were heading, you'd be better-equipped to handle them successfully, able to deploy specific tools and resources to ensure a positive outcome.