Artificial Intelligence (AI) is rapidly becoming the biggest issue on the agenda for many businesses. The current speed of development, the sheer range of possible applications, and the potential impact of AI suggest that it's time for CEOs to pay attention. So, what are the questions every CEO should be asking? Futurist Rohit Talwar, CEO of Fast Future Publishing believes there are ten questions that need to be asked in order to assess and invest in AI's transformative potential: 1. AI will change the philosophy, practice and management of business. It is beginning to transform businesses and replace even senior management and leadership roles.

TOKYO, Nov 29, 2016 - (ACN Newswire) - Fujitsu today announced it has developed five Zinrai-related services that are being rolled out incrementally in Japan, helping customers accelerate their use of artificial intelligence. These services are based on the company's foundation of AI technology and knowledge, and are part of the "Human Centric AI Zinrai" framework, Fujitsu released November 2015. Fujitsu is positioning these services on its FUJITSU Digital Business Platform MetaArc, which works to accelerate the business innovation of customers. The services being introduced are FUJITSU AI Solution Zinrai Platform Service, which offers 30 AI functions in API(1) form, developed in over 300 AI-related projects and field trials; FUJITSU AI Solution Zinrai Deep Learning, a deep-learning platform service that implements the world's fastest class of deep-learning processing; and FUJITSU AI Solution Zinrai Consulting Service, FUJITSU AI Solution Zinrai Integration Service, and FUJITSU AI Solution Zinrai Operations Service, for total support to customers on AI, from consulting to deployment and operations. Zinrai Platform Service and Zinrai Deep Learning are combined with consulting, deployment, and operations services so that customers can quickly build high-quality, high-performance AI-based business systems.

In today's blog post, we shall look into time series analysis using R package – forecast. Objective of the post will be explaining the different methods available in forecast package which can be applied while dealing with time series analysis/forecasting. A time series is a collection of observations of well-defined data items obtained through repeated measurements over time. For example, measuring the value of retail sales each month of the year would comprise a time series. My data set contains data of Sales of CARS from Jan-2008 to Dec 2013.

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.

Machine learning has become an incredibly popular field of research in the last few years. We'll start out comparing the Flambo and Sparkling libraries by building a binary classifier, then move on to exploring image recognition with a convolutional neural network developed with DeepLearning4J. You'll come away with a solid grasp of introductory theory as well as practical approaches to developing models and neural networks in Clojure.

In a recent interview, AthenaHealth CEO Jonathan Bush noted the limitations of traditional doctors and said, "The human is wrong so freaking often, it's a massacre." "By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries." Stephen Hawking has said the development of full Artificial Intelligence (AI) could spell the end of the human race – and Elon Musk agreed. In a recent interview, AthenaHealth CEO Jonathan Bush noted the limitations of traditional doctors and said, "The human is wrong so freaking often, it's a massacre." "By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries."

Artificial intelligence technology has advanced leaps and bounds in a relatively short period of time. What once seemed like science fiction is quickly becoming a reality. The sudden advancement in the technology has reawakened some fears about what artificial intelligence could mean for the future of humankind. Recently, Stephen Hawking, arguably one of the most brilliant minds of the last century and Elon Musk, the CEO of Tesla Motors, have both voiced concerns about the future of artificial intelligence. Should we fear artificial intelligence?

LONDON: Scientists have discovered a way to remove specific fears from the brain, using a combination of artificial intelligence and brain scanning technology, an advance that may lead to new treatments for conditions such as post-traumatic stress disorder (PTSD) and phobias. Currently, a common approach is for patients to undergo aversion therapy, in which they confront their fear by being exposed to it in the hope they will learn that what they fear is not harmful. However, this therapy is unpleasant. Researchers from the University of Cambridge in the UK have found a way of unconsciously removing a fear memory from the brain. They developed a method to read and identify a fear memory using a new technique called'Decoded Neurofeedback'.

I think that having a so much great resources available can sometimes be both a blessing and a curse. It's great that we have so many tools and sources of information to choose from, but to make best use of it -- and our time -- it is really important to actually "choose" and keep "focused." I don't want to say that many resources are "redundant," since "redundant" has a somewhat negative ring to it. However, there are many different books, tools, and courses that cover essentially the same thing, although, the scope and style may be a bit different. So, instead of adding everything that we stumble upon to our reading lists, I'd say that it makes more sense to be absolutely clear about personal goals first ("What skills do I need to learn to solve problem X?," "Do I really to learn this new, shiny tool X instead of Y?").

I'm Yannis, and I joined Dataiku a few months ago to work on applying Deep Learning to image classification. I'm about to show you how to automatically tag images using a pre-trained neural network. Imagine you are an e-commerce company with thousands of flash sales available on your website every day. To view a product offer in detail, users have to click on the specific thumbnail, which is composed of an image and a short description. In these thumbnail images is hidden information, yet you don't know how to use it.