I gained access to this book free, via the sponsor of our non-profit's first year of operations, or I would not have bought it. It must certainly be in the library of any university or college with ambitions to educate those who will lead the next wave moving us toward Web 3.0 and Web 4.0. It is however reasonably priced and I recommend it for both library acquisition and deep reader purchase. The publisher has been responsible about posting useful information (see inside the book, the second active link below the cover on this page) so I urge anyone asking that this work be acquired, at this price, print and attach the table of contents to their requisition. The book is very well-organized with ample white space and excellent illustrative graphics and figures.

Imagine wanting a cup of coffee and suddenly finding it before you, freshly prepared to your exacting standards. In the not-so-distant future, this will be reality for Muggles, too. In fact, thanks to a surge in consumer data, brands and marketers can already make better inferences about consumer wants and needs, but as AI and machine learning are more deftly integrated, insights will only get better, as will the ability to anticipate consumer needs – and to even make decisions on behalf of consumers without any input from them whatsoever. Like, say, ordering a cup of coffee. As it stands, digital enables brands to customize offers for specific users rather than provide generic solutions.

Artificial intelligence (AI) has made its way into many aspects of our lives – even into toys for kids like Anki's Cozmo, which resembles a roboticized Ewok. But as things go, AI isn't just for devices, it's made and continues to make it's way into e-commerce and is out there working to determine what to sell to you, how you shop and ensure you have a good shopping experience. According to Gartner by 2020, 85% of customer interactions will be managed without a human and at the close of 2018, customer digital assistants will recognize customers by face and voice across channels. Investment-wise, in 2014 there were more than 300 million in venture capital invested in AI startups according to Bloomberg. Brands are on board and are using AI to build smarter platforms they hope will create a better online shopping experience for the consumer.

I am a big fan of the authors 1999 book on Statistical Natural Language Processing, and I and was thrilled when I found this new book online -- just search for "Information Retrieval" on Google. In these two books, they describe the theory behind a vast toolbox which can be used to construct new tools/products for the Internet. Now I can go back to them when the need arises. For starters, I appreciate the detailed theoretical explanations of topics that I could not find in other texts, and the references to related work are especially helpful. One of the other books I read was Information Retrieval by Grossman, which is an older book but has a more condensed style compared to this.

I received my copy today and instantly decided I would be using it in several of the courses I teach for pre-service teachers. They have been asking for a book like this for years, but the existing books were aimed at the wrong audience, had content that was oversimplified (or overly complex), or failed to incorporate important current research. Dr. Fredricks' book masterfully incorporates the most relevant research with perfect tone and an engaging narrative. There's no way I'll be assigning a 100 textbook when this new book does so much more at less than a third the price.

KEVIN C. DESOUZA is Research Associate with the Center for Research in Information Management, University of Illinois, Chicago. He lectures widely on topics in e-commerce, data warehousing, data management, and computer-based training, and has served in various managerial and technical capacities with organizations worldwide.

Artificial intelligence technology is finding its way to every corner of the modern enterprise. Last week Google set out to help organizations embrace the trend faster by acquiring a startup called API.AI Inc. that has developed a cloud-based chatbot builder. The platform provides pre-packaged communications modules, a repository of encyclopedic data and other components that can be quickly cobbled together into a working artificial intelligence. API.AI claims that companies can use its service to build everything from Slack-based bots focused on a specific task to standalone virtual assistants capable of taking a wide range of different requests. Google will likely make the technology part of its public cloud in the wake of the acquisition to try to gain an edge over better-established providers like Amazon.com Inc. Oracle Corp. is pursuing a similar goal with the competing chatbot development tool that it unveiled at its annual customer conference last week.

The retail industry is inundated with buzzwords that describe the best way to engage with consumers -- such as omnichannel marketing, customer journey, and a 360-degree view -- to provide a more personalized and optimized experience. All of these buzzwords point to a common problem most retail marketers are aching to solve: How can they use customer data to create timely insight into what customers are doing in-store and/or online and convert that into strategies and actions that increase sales? It's an age old question with new age solutions, and the retail industry is now leveraging artificial intelligence (A.I.) to usher in a unique way of thinking about this problem. In fact, a new chart shows there are 45 A.I. companies focused on retail across a range of verticals, including recommendations, merchandising, search, conversational commerce, and especially multichannel marketing. Using omnichannel retailing, the ability to connect with a customer both online and offline, is ideal because omnichannel customers have a 30 percent higher lifetime value than single channel customers.

The review you are reading was written by a human, not a machine. This fact would no doubt disappoint some of the pioneers of artificial intelligence, who would have thought that by the 21st century a computer would be able to read a book, consider it in the context of other knowledge and express some thoughtful opinions about it. On the other hand, the human who wrote this review was aided in researching and preparing it by telecommunications and computer networks, including the Internet, that owe a big part of their existence and even more of their smooth functioning to theories and concepts that arose from artificial-intelligence research. The enormous, if stealthy, influence of AI bears out many of the wonders foretold 25 years ago in Machines Who Think, Pamela McCorduck s groundbreaking survey of the history and prospects of the field. A novelist at the time (she has since gone on to write and consult widely on the intellectual impact of computing), McCorduck got to the founders of the field while they were still feeling their way into a new science.

I am curious what the fellows at Rebellion Research would have to say about this book? I am not aware of any other firm that using artificial intelligence beyond trading and for investing the way Rebellion Research is using ai to manage money and predict global economics.