Almost a third (32%) of consumers surveyed globally by PwC plan to buy an AI device including robots or automated assistants, with retailers watching closely as'voice commerce' develops in the home. The findings are published today in PwC's Global Consumer Insights survey, which assesses the shopping behaviour, habits and expectations of over 22,000 consumers in 27 countries. The study reports that 10% of respondents already own artificial intelligence (AI) devices, such as robots and automated personal assistants like Amazon Echo or Google Home, and 32% said they plan to buy one. Both consumer and retailer habits and offerings still need time to adapt however, to make the most of the new voice commerce channel. Interest in the devices is strongest amongst consumers in emerging economies including China, Vietnam, Indonesia and Thailand.

Over the past few years, technology has seen a significant shift from cyclical, invention-led spending on point solutions to investments targeting customer-driven, end-to-end value. The next wave of disruption and productivity improvements is here, which means a huge opportunity for digital-focused enterprises – if you are following the right roadmap. Technology trends have significant potential over the next few years. Establishing a digital platform will not only set the stage for business innovation to provide competitive advantage, but it will also create new business models that will change the way we do business. Technology trends in 2018 will lay the foundation for the maturity of innovative technologies like artificial intelligence and machine learning and will prepare both businesses and shoppers to be ready for their consumption.

This article first appeared in the Winter 2017 issue of The Record. Gone are the days where customers visiting US-based home improvement store Lowe's had to flick through multiple swatches of paints and materials, or wander round the store looking at appliances. Now, they simply populate their Pinterest boards with images of their ideal kitchens, send it to Lowe's and the retailer uses analytics and machine learning technologies to find relevant products in its inventory to produce relevant kitchen concepts. When they get to the store, customers use a Microsoft HoloLens headset to finalise a holographic representation of their newly designed kitchen in real scale by switching between different colours and finishes and moving appliances. While Lowe's is somewhat of a pioneer, this is just the start of what's likely to become the standard for retail customer experiences, predicts Pinar Salk, Microsoft's industry solutions director for retail.

The smart speaker is a tech innovation that's caught fire with consumers, according to the "Smart Speaker Consumer Adoption Report 2018" released by Voicebot.ai in collaboration with PullString and the RAIN Agency. The findings are based on an in-depth national survey of 1,057 U.S. adults, who were queried on ownership, product preference and use cases. About 19.7 percent of U.S. adults are said to have access to a smart speaker, which would mean an absolute number of 47.3 million out of the total U.S. adult population of 252 million, according to Voicebot.ai. "Access" includes adults who have a device in their homes but are not the primary user. A separate survey by NPR and Edison Research completed in November found 16 percent of adult Americans, or about 39 million, own a smart speaker.

A version of this article appeared in the Spring 2018 issue of strategy business. If you haven't noticed, a high-stakes global game of digital disruption is currently under way. It is fueled by the latest wave of technology: advances in artificial intelligence, data analytics, robotics, the Internet of Things, and new software-enabled industrial platforms that incorporate all these technologies and more. Every enterprise leader recognizes that, as a result, the prevailing business models in his or her industry could drastically and fundamentally change. A wide range of industries, such as entertainment and media, military contracting, and grocery retail have already been profoundly affected. No enterprise, including yours, can afford to ignore the threat. Yet most companies are still not moving fast enough to meet this change. Some leaders are still in denial about it, some are reluctant to upend the status quo in their companies, and some are unaware of the necessary steps to take. But these excuses are not good enough. If your company is aleady struggling, then digital disruption will accentuate your problems. You may not have needed a plan for the new digital age yet, if only because it didn't seem relevant to your industry. But you will need it now.

Widescale technology adoption is causing disruption in many industries, and for retail it means an increase in what consumers expect from their shopping experience. Download this e-guide to discover the results of our 2018 UK IT Priorities survey, where IT leaders shared with us what they are going to be investing in over the coming 12 months. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

Introduced at re:Invent 2017, Amazon SageMaker provides a serverless data science environment to build, train, and deploy machine learning models at scale. Customers also have the ability to work with frameworks they find most familiar, such as Scikit learn. In this blog post, we'll accomplish two goals: First, we'll give you a high-level overview of how Amazon SageMaker uses containers for training and hosting models. Second, we'll guide you through how to build a Docker container for training and hosting Scikit models in Amazon SageMaker. In the overview, we'll discuss how Amazon SageMaker runs Docker images that have been loaded from Amazon Elastic Container Service (ECS) for training and hosting models. We will also discuss the anatomy of a SageMaker Docker image, including the training code and inference code. If you are only interested in building, training, and deploying Scikit models in Amazon SageMaker, you can skip the overview. Instead, go right to the hands-on demonstration of how to containerize Scikit models in SageMaker with the minimal amount of effort. SageMaker makes extensive use of Docker containers to allow users to train and deploy algorithms. Containers allow developers and data scientists to package software into standardized units that run consistently on any platform that supports Docker. Containerization packages code, runtime, system tools, system libraries and settings all in the same place, isolating it from its surroundings, and insuring a consistent runtime regardless of where it is being run. When you develop a model in Amazon SageMaker, you can provide separate Docker images for the training code and the inference code, or you can combine them into a single Docker image.

The in-store experience has never been more valuable than it is for luxury brands today. In an industry where marketing is heavily focused on the product experience, it can be hard to imagine an alternate reality where that level of live, in-person engagement can be replicated digitally. However, brands are now confronted with the challenge of maintaining relevance among loyal followers while also attracting a new generation of consumers. The double-digit growth of 2010-13 has dwindled, and e-commerce is starting to represent more and more of the industry's total sales. Amazon and Walmart have charted formidable digital territory, with the former raking in 44% of all U.S. e-commerce sales, and Walmart aiming to grow online sales as much as 40% by 2019.

Since the introduction of self-serve checkouts in Australian supermarkets nearly ten years ago, customers have been engaging in the simplest of hacks to outsmart the supermarket technology. Not so much– mostly it is just by putting through more expensive items as much cheaper ones (think a kilo of lemons as a kilo of potatoes). But thanks to an Aussie start-up, new AI technology will put an end to customer's criminal careers. Tiliter Technology has developed an automated product recognition system which automatically identifies products, removes the needs for barcodes and the entering of additional information at the checkout, so that customers can't cheat the system. Chris Sampson, the co-founder, told News Corp that the "smart checkouts" use a camera to identify the product, and is "based on machine learning and artificial intelligence which has been taught to recognise different types of fruit and other products."

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