By the end of 2021, more than 1.6 billion people will use voice assistants on a regular basis, and it is certain they will want to do more than ask about the weather or hear their favourite song. Such assistants will provide retailers with an unprecedented opportunity as consumers use them to find, research and buy products. For this reason, exploring how voice assistants can improve the customer experience is a core focus for many retailers right now. Conversational artificial intelligence (AI) is powering voice technology systems and be it Alexa, Siri or Google Home, these platforms are enabling customers to interact with brands in ways that are not only convenient but also highly personalised and contextualised. In a conversational AI world, virtual assistants will search, open, fetch, command and engage the dozen or more websites, portals, apps and systems we all interact with daily.

Today's shoppers have developed a new standard of behaviors, preferences and expectations for all of their retail experiences. Responsible with meeting these elevated needs, retailers seek to overcome the hurdles of legacy technology and captivate each of their customers on a 1:1 basis. In the past, consumer value expectations were centered on three variables: cost, choice, and convenience. With instant gratification available at the push of the button, customers are looking to have more control of their purchase journey and are seeking out personalized shopping experiences. Accustomed to the instant access of e-commerce shopping, customers are looking for opportunities to skip the line and have direct communication channels to ask, troubleshoot, and of course, shop.

In this post I'm going to show what streaming ETL looks like in practice. My first job from university was building a data warehouse for a retailer in the UK. Back then, it was writing COBOL jobs to load tables in DB2. We waited for all the shops to close and do their end of day system processing, and send their data back to the central mainframe. From there it was checked and loaded, and then reports generated on it.

Imagine you walk into aretail store wearing a blue striped shirt and by the time you go to the store help, he is already prepared with half a dozen striped shirts that you could consider buying. This might very well be possible, thanks to a suite of artificial intelligence (AI) based retail in-store products of SaaS provider Capillary Technologies. The company, which recently raised $20-million, has been working on using AI to understand the demographics, footfall and conversations within a retail store to give these stores a helping hand in an era where online players are aggressively expanding their operations. By using these solutions, stores can now attempt to do targeted advertising, produce heat maps, analyse conversations and build unique customer profiles. Capillary is piloting these solutions with an initial few customers. For Capillary, this is opening up a new suite of products other than its existing omnichannel customer engagement products.

Original, accessible, and provocative….Tegmark successfully gives clarity to the many faces of AI, creating a highly readable book that complements The Second Machine Age's economic perspective on the near-term implications of recent accomplishments in AI and the more detailed analysis of how we might get from where we are today to AGI and even the superhuman AI in Superintelligence…. At one point, Tegmark quotes Emerson: 'Life is a journey, not a destination.' The same may be said of the book itself. Enjoy the ride, and you will come out the other end with a greater appreciation of where people might take technology and themselves in the years ahead.

In this paper, we consider a realistic and meaningful scenario in the context of smart grids where an electricity retailer serves three different types of customers, i.e., customers with an optimal home energy management system embedded in their smart meters (C-HEMS), customers with only smart meters (C-SM), and customers without smart meters (C-NONE). The main objective of this paper is to support the retailer to make optimal day-ahead dynamic pricing decisions in such a mixed customer pool. To this end, we propose a two-level decision-making framework where the retailer acting as upper-level agent firstly announces its electricity prices of next 24 hours and customers acting as lower-level agents subsequently schedule their energy usages accordingly. For the upper level problem, we optimize the dynamic prices for the retailer to maximize its profit subject to realistic market constraints. The above two-level model is tackled by genetic algorithms (GA) based distributed optimization methods while its feasibility and effectiveness are con-2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. Please cite this accepted article as: Fanlin Meng, Xiao-Jun Zeng, Yan Zhang, Chris J. Dent, Dunwei Gong, An Integrated Optimization Learning Approach to Optimal Dynamic Pricing for the Retailer with Multi-type Customers in Smart Grids, Information Sciences (2018), doi: 10.1016/j.ins.2018.03.039 Preprint submitted to Information Sciences March 22, 2018 firmed via simulation results. Keywords: Bilevel Modelling, Genetic Algorithms, Machine Learning, Dynamic Pricing, Demand-side Management, Demand Response, Smart Grids 1. Introduction With the large-scale deployment of smart meters and two-way communication infrastructures, dynamic pricing based demand response and demand-side management programs [37] [12] have attracted enormous attentions from both academia and industry and are expected to bring great benefits to the whole power system. Real-time pricing (RTP), timeof-use pricing (ToU) and critical-peak pricing (CPP) are commonly used dynamic pricing strategies [20].

Most people have heard of AI (artificial intelligence) and BI (business intelligence), but few have heard of CI (customer intelligence). Some even call it cloud intelligence because so much customer data is now stored in the cloud. Is CI for real or just a figment of our imaginations? Before we get to the numbers, let's look at the definitions. AI is all about getting computers to perform tasks or processes that would be considered intelligent if done by humans.

Amazon CEO Jeff Bezos has taken a robotic dog for a walk at a secretive conference in California. The 54-year-old has been pictured strutting alongside Boston Dynamics' four-legged SpotMini robot, which has previously been compared to killer canine bots featured in the Netflix series Black Mirror. Bezos, who is worth a reported £92 billion ($130 billion), posted the photo to his Twitter account on Monday with the caption: 'Taking my new dog for a walk.' He is currently attending Amazon's'Mars' conference in Palm Springs - an invite-only gathering of robotics companies and academics that focuses on machine learning, automation, robotics and space exploration. Amazon CEO Jeff Bezos has taken a creepy robotic dog for a walk around a secretive conference in California.

Google routinely fields product queries from millions of shoppers. Now, it wants to take a cut of their purchases, too. Under a new program, retailers can list their products on Google Search, as well as on the Google Express shopping service and Google Assistant. In exchange for Google listings and linking to retailer loyalty programs, the retailers pay Google a piece of each purchase, which is different from payments that retailers make to place ads on Google platforms. A new Google initiative called'Shopping Actions,' should help retailers fend off Amazon's growing dominance.

We're positive you'll agree that chatbots have become a significant part of our everyday lives. Judging by the market situation today, it seems like chatbots are here to stay. Although chatbots aren't being used to their full potential, the new millennium has brought a change for the better. Chatbots are finding their place in marketplaces worldwide, and recent results stand behind scientific assumptions that the artificial intelligence is slowly'conquering the world'. Information technology is moving a lot faster than other industries nowadays. As a result, budget-retailers like Nordstrom Rack rely on chatbots to provide assistance to their customers, and so does TJ Maxx.