Artificial intelligence (AI) is more than just cyborgs in movies trying to destroy humanity. It has actual real-world applications that can make our lives better and our businesses stronger and more profitable. In retail, artificial intelligence is being adopted rapidly - between 2016 and 2018 there was a 600% increase in adoption. Unfortunately the adoption rate is still relatively low, ranging from 26% for home improvement stores to 33% for apparel and footwear. If AI can make such a big difference, why isn't everyone adopting it?

I would like to start with the fact that the retail market today is developing by leaps and bounds, but traders by the way also do not standstill. On the contrary, they gradually seize the initiative by introducing Artificial Intelligence into their products. Note, when many things were simply impossible, but thanks to the arrival chatbots much have changed. Chatbots are one of the most effective tools in building relationships between customers. More and more retailers choose eCommerce chatbots as a primary method of communication with the visitors of their online stores. The main benefits of using Chatbot technology are reducing costs on the workforce and saving time.

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A decade ago, the British department-store chain John Lewis built itself a long warehouse, painted in gradations of sky blue. The shed, as it is called in the industry, cost £100m and covered 650,000 sq ft. Windsor Castle could easily fit inside it. John Lewis named the shed Magna Park 1, after the site where it stands: a "logistics campus" of warehouses, roads, shipping containers and truck bays east of Milton Keynes. Magna Park 1 was intended to supply the company's stores around southern England, but almost as soon as it was finished, John Lewis realised that it wasn't enough. The pace of e-commerce was flying, and Magna Park 1 opened in the midst of a spell in which, between 2006 and 2016, the share of John Lewis deliveries going direct to customers rose 12-fold. So John Lewis built Magna Park 2, measuring 675,000 sq ft. After that, the company realised it needed a new shed for Waitrose, its supermarket chain, where home deliveries were skyrocketing, too. "It became a bit of a standing joke," said Philip Stanway, a regional director at Chetwoods, the architecture firm that designed and built all these facilities. "They used to come to meetings with their forecasts, and they'd say: 'Screw this. This is the new forecast,'" Stanway said, making a scribbling motion in the manner of a John Lewis executive hastily updating the numbers. "We couldn't build the buildings quick enough for them."

As the digital world continues to modernise, and new technologies are developed, the AI and Data Strategy book simplifies the complexities and introduces a structured way to update your strategy to include AI and Data capabilities The book defines the technologies and why they are important and this includes Automatic cars, drones, robots, blockchain, data science, machine learning and internet of things. Most of us are unsure what this all means and may think it's a bit technical and over our head. In the end we really just want to manage our information more securely and be able to access it anywhere anytime any place. The book makes the connection between what the technology is and how it can help us achieve your goals in accessing information. The AI and Data strategy book will get you started on the what, how, who and why to enable you to build and implement an AI and Data strategy.

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It can reduce your labeling costs by up to 70% using automatic labeling. This blog post explains the Amazon SageMaker Ground Truth chaining feature with a few examples and its potential in labeling your datasets. Chaining reduces time and cost significantly as Amazon SageMaker Ground Truth determines the objects that are already labeled and optimizes the data for automated data labeling mode. As a prerequisite, you might want to check the post "Creating hierarchical label taxonomies using Amazon SageMaker Ground Truth" that shows how to achieve multi-step hierarchical labeling and the documentation on how to use the augmented manifest functionality.

Sainsbury's commercial and technology teams are working with Accenture to implement machine learning processes that they say are providing the retailer with better insight into consumer behaviour. Using the Google Cloud Platform (GCP), the key aim of the collaboration is to generate new insights on what consumers want and the trends driving their eating habits. By tapping into data from multiple structured and unstructured sources, the supermarket chain has developed predictive analytics models that it uses to adjust inventory based on the trends it spots. According to Alan Coad, managing director of Google Cloud in the UK and Ireland, the platform can "ingest, clean and classify that data", while a custom-built front-end interface for staff can be used "to seamlessly navigate through a variety of filters and categories" to generate the relevant insights. Phil Jordan, group CIO of Sainsbury's, said: "The grocery market continues to change rapidly. "We know our customers want high quality at great value and that finding innovative and distinctive products is increasingly important to them.

"Rather than questioning the character of thinking machines, futurist Amy Webb turns a critical eye on the humans behind the computers. With AI's development overwhelmingly driven by nine tech powerhouses, she asks: Is it possible for the technology to serve the best interests of everyone?"―Wired "Webb's assessments are based on analyses of patent filings, policy briefings, interviews and other sources. She paints vivid pictures of how AI could benefit the average person, via precision medicine or smarter dating apps...Her forecasts are provocative and unsettlingly plausible."―Science News "Instead of predicting the future, Webb lays out scenarios for optimistic, pragmatic, and catastrophic outcomes -- all extrapolated from current facts. However impractical you may find the idea of a common Apple-Amazon operating system named Applezon, considering potential scenarios is a fantastically healthy exercise, because anyone who tells you they know how AI is going to turn out is lying."―VentureBeat

If you're like most companies, you wish to better understand your customers and your brand image. You'd like to track the success of your marketing campaigns, and the topics of interest--or frustration--for your customers. Social media promises to be a rich source of this kind of information, and many companies are beginning to collect, aggregate, and analyze the information from platforms like Twitter. However, more and more social media conversations center around images and video; on one recent project, approximately 30% of all tweets collected included one or more images. These images contain relevant information that is not readily accessible without analysis.

One of the most anticipated books of the fall! - Adam Grant, Ars Technica, Philadelphia Inquirer, Next Big Idea Club, BookPage "If you're terrified that artificial intelligence is going to take over the world, you clearly haven't asked a computer to write pick-up lines, name pets, or do anything else social or creative. Janelle Shane has, and she's the perfect tour guide to explain what machine learning can and can't do--and why it's already affecting your life. I can't think of a better way to learn about artificial intelligence, and I've never had so much fun along the way."―Adam Grant, New York Times bestselling author of Originals "While everyone else is making questionable predictions about the future of AI, Janelle Shane cuts through the fog by telling you how AI actually works. And even better: she makes it fun!"―Zach Weinersmith, creator of Saturday Morning Breakfast Cereal and New York Times bestselling author of Soonish "An incredibly accessible, informative, and hilarious look at how the AIs deciding things around us operate."―Ryan