What customers want and what businesses think they want are often two different things. Here's what customers are looking for. Anyone who has gotten an unsolicited and irrelevant offer related to something they've done online knows that creepy feeling that someone is watching me. This kind of reaction is the third rail of today's drive to personalize interactions with customers. That's a problem because, when done right, personalization can be a huge boon for retailers and consumers.

Wal-Mart's new robots scan shelves to restock items faster

In a global market that makes room for more competitors by the day, some companies are turning to AI and machine learning to try to gain an edge. Supply chain and inventory management is a domain that has missed some of the media limelight, but one where industry leaders have been hard at work developing new AI and machine learning technologies over the past decade. Many well-known companies are now use machine learning to optimize business processes in ways that might have been deemed science fiction 30 years ago, from customer service inquiries to planning for next month's shelf supply based on satellite data. Supply chain and inventory management is primed to embody the concept of smart automation over the next five to 10 years. We've highlighted three applications of inventory management with machine learning technology, providing a tip-of-the-iceberg view of what's possible.

Since books are expensive, I tend to research extensively before deciding on which ones to purchase. For professional reasons, I wanted to branch into machine learning using the R programming language. Based on customer reviews, the Amazon "Look Inside" feature, and online suggestions, I invested in several books: "An Introduction to Statistical Learning with Applications in R" (James, Whitten, Hastie and Tibshirani), "Artificial Intelligence, A Modern Approach, Third Edition" (Russell and Norvig), "Machine Learning with R" (Lantz), and "Machine Learning with R Cookbook" (Chiu). With these resources, and with a great YouTube course from the University of British Columbia (Google UBC CPSC 340 Nando YouTube), I set out to learn. Still learning (no overnight success stories here), but the progress is encouraging.

Many retailers are struggling to devise the perfect cross-channel experience for their customers--one that takes advantage of digitalization to provide targeted, just-in-time product or service information in an effective and seamless way. The key internal capabilities needed to ensure a successful digital shopping experience are personalization, automation and the unique identification of the customer across shopping channels. In this report, we discuss how AI and IoT are impacting the retail industry. We explore how these technologies are changing the way retailers operate and provide examples of how major industry players are using AI and IoT to increase operational efficiency and unlock new revenue opportunities. Retailers that aim to remain competitive cannot afford to ignore the potential benefits of these technologies. AI, a technology that enables computers to make autonomous decisions, is a step forward in automation that is changing the retail industry. Retailers are using AI to analyze customer data, adapt how they interact with shoppers and predict demand in order to better manage inventory. Because consumers are bombarded with an unprecedented amount of information, being able to deliver highly personalized content for each individual customer is crucial to staying ahead of the competition. Meanwhile, the use of AI to anticipate demand and estimate when items will be returned should translate into more efficient business operations.

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries.

Customers are more tech savvy than ever. Armed with smartphones, they have the entire Internet at their fingertips, which can be either a hazard or an opportunity for retailers. The last thing a brick-and-mortar store wants is to lose a sale because a customer scans a barcode and finds the item cheaper elsewhere. To combat this, retailers are using computing on the edge and Internet of Things (IoT)-connected devices to turn potential showrooming into sales. When a customer scans a pack of printer ink, connecting through the store's WiFi, the retailer can use this as an opportunity to serve a coupon or make personalized recommendations for complementary products such as printer paper or a computer mouse, upselling and cross-selling additional items.

Soon you'll see something new roaming the aisles at Walmart. The company is introducing shelf-scanning robots to its stores to help keep shelves stocked and full at all times. The robots will be operating in 50 stores across the United States, according to Reuters. The robots are vaguely square and have a tower sticking out of one side of the top of them. This part of the bot is fitted with camera to help the robot maneuver aisles and to scan the shelves for any missing items or empty spots where and item needs to be restocked, Reuters reported. In addition to scanning shelves for missing items, the bots can also identify spots where a price is displayed incorrectly, an item is misplaced or where items are mislabeled.

If you squint a little, you can see the Apple Store clerk as a cyborg, a hybrid of human and machine. Each store is flooded with smartphone-wielding salespeople who are able to help customers with everything from technical questions and support to purchase and checkout. There are no cash registers with lines of customers waiting with products pulled from the piles on the shelves. The store is a showroom of products to explore. When you know what you want, a salesperson fetches it from the back room.

The battle for the title of'world's richest man' has taken a fresh twist. Amazon CEO Jeff Bezos, 53, may have pipped Bill Gates, 61, to the title after he added $6.5 billion (£5 billion) to his vast fortune yesterday. The jump came thanks to soaring Amazon share prices after its third quarterly earnings report beat expectations. Bezos now has a net worth of $90 billion (£69 billion), based on data from the Bloomberg Billionaire Index. Microsoft founder Gates still held the title at the market's close yesterday, with a net worth of $88 billion (£67 billion), according to the index.