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How Tech Startups Are Implementing Checkout-Free Platforms

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According to a recent study conducted by Forrester Research, waiting in the checkout line is the top complaint among U.S. grocery, mass-merchandise, and convenience store shoppers. Mega-retailer Amazon and a quartet of well-funded retail technology startups -- Zippin, Standard Cognition, Grabango and Trigo -- believe they have the solution to the problem: Checkout-free stores powered by various technologies that enable shoppers to walk into the store, grab what they want off the shelves and just walk out. Autonomous checkout, another term for checkout-free, is becoming one of the hottest areas of retail investment today. It comes as the convenience expectations of today's Amazon-shopping, Grubhub-ordering, Uber-hailing consumers are ever-increasing, and informing their in-real-life (IRL) shopping demands. Brands are responding in kind, delivering digital services aimed at automating mundane tasks -- in this case, the checkout process -- so much so that the result is meant to feel "automagical," according to trend forecasting firm TrendWatching. Checkout-free retail has the potential to make shopping even more convenient, retail technology consultant Richard Crone said at this summer's National Retail Federation's NRF Tech 2019 conference in San Francisco.


Amazon.com: Artificial Intelligence: AI Technology and Deep Learning Systems Explained (Audible Audio Edition): Christian Farsley, Blake Ledger: Audible Audiobooks

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Talking to Strangers: What We Should Know About the People We Don't Know 3.8 out of 5 stars 458 #1 Best Seller in Communication Reference $0.00 Free with Audible trial Talking to Strangers: What We Should Know About the People We Don't Know


From AI to Humble Pi: the best new science books to buy for Christmas

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Do we have more to fear from artificial intelligence or natural stupidity? This year's best science books offer plenty of both. Artificial intelligence has been much in the news this year, even though it doesn't really exist yet – as was made clear by the story of how people's conversations with Apple's "smart assistant", Siri, were being listened to by real human beings, low-paid workers in the global digital sweatshop. Nevertheless, the arrival of really intelligent machines has the potential to transform our world utterly. Consider ordering a superintelligent computer to make paper clips.


Network Revenue Management with Limited Switches: Known and Unknown Demand Distributions

arXiv.org Machine Learning

This work is motivated by a practical concern from our retail partner. While they respect the advantages of dynamic pricing, they must limit the number of price changes to be within some constant. We study the classical price-based network revenue management problem, where a retailer has finite initial inventory of multiple resources to sell over a finite time horizon. We consider both known and unknown distribution settings, and derive policies that have the best-possible asymptotic performance in both settings. Our results suggest an intrinsic difference between the expected revenue associated with how many switches are allowed, which further depends on the number of resources. Our results are also the first to show a separation between the regret bounds associated with different number of resources.


IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks

arXiv.org Artificial Intelligence

The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of complex manipulation tasks. The environment is designed to advance reinforcement learning from simple toy tasks to complex tasks requiring both long-term planning and sophisticated low-level control. Our environment supports over 80 different furniture models, Sawyer and Baxter robot simulation, and domain randomization. The IKEA Furniture Assembly Environment is a testbed for methods aiming to solve complex manipulation tasks. The environment is publicly available at https://clvrai.com/furniture


Now available: Batch Recommendations in Amazon Personalize Amazon Web Services

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Today, we're very happy to announce that Amazon Personalize now supports batch recommendations/ Launched at AWS re:Invent 2018, Personalize is a fully-managed service that allows you to create private, customized recommendations for your applications, with little to no machine learning experience required. With Personalize, you provide the unique signals in your activity data (page views, sign-ups, purchases, and so forth) along with optional customer demographic information (age, location, etc.). You then provide the inventory of the items you want to recommend, such as articles, products, videos, or music: as explained in previous blog posts, you can use both historical data stored in Amazon Simple Storage Service (S3) and streaming data sent in real-time from a JavaScript tracker or server-side. Then, entirely under the covers, Personalize will process and examine the data, identify what is meaningful, select the right algorithms, train and optimize a personalization model that is customized for your data, and is accessible via an API that can be easily invoked by your business application. However, some customers have told us that batch recommendations would be a better fit for their use cases.


Artificial intelligence helps retailers anticipate customer needs

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Retailers are increasingly using artificial intelligence to manage their stores and monitor shopping behavior and offer better experiences, as we discover in the second installment of Mergers & Acquistions' 7-part series, Retail Tech M&A. There are 7 technologies retailers are investing in through M&A: The Internet of Things enables enhanced personalization, such as custom drive-thru menus. Artificial intelligence applications predict customers' needs. Modern data centers and warehouses fill orders quickly. Robots assist with sorting and packing consumer goods.


Digital business transformation accelerates: Just ask NCR, Zillow, Axon ZDNet

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An hour of earnings reports highlighted how every business will go digital, becoming software-based and utilize artificial intelligence. Michael Dale Hayford, CEO of NCR, said the company is looking to create software defined stores in its retail business. And banking, which is becoming more about the ATM than the branch. NCR reported third quarter revenue of $1.78 billion, up 15% from a year ago, with net income of $105 million. The company saw strong growth in both ATM and point of sale terminals.


FamilyMart to allow shorter operating hours at stores across Japan

The Japan Times

Convenience store operator FamilyMart Co. has said it will allow its franchise owners across Japan to shorten operating hours from March, in a bid to address a severe labor shortage during late-night hours. Under the new policy, which will cover nearly 16,000 stores, franchise owners will be able to shut down for part or all of the period from 11 p.m. to 7 a.m. if they notify the headquarters in advance. "It is up to each of our franchise owners to make a decision" to end 24-hour operations, said Takashi Sawada, president of the company, at a news conference in Tokyo on Thursday. Store owners who want to cut operating hours would be able to choose to do so either every day or only on Sundays, according to firm, which is Japan's second-largest convenience store operator based on number of outlets. FamilyMart will also raise its monthly incentive to ¥120,000 ($1,100) from ¥100,000 for stores that maintain around-the-clock operations.


Set customer service agents up for success as Black Friday approaches

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A famous television series kicked off with its first episode titled "Winter is Coming." This phrase ended up carrying more weight than just the arrival of a season in the fictional series. In real life, some might say another monumental event is nearly upon us: Black Friday. References to Black Friday began as early as the 1950's in the United States. It wasn't until the 1980's that it came to refer to the retail shopping period following the Thanksgiving holiday, with one explanation suggesting the color indicated this being the time at which retail companies moved from operating at a loss (or "in the red") to profitability ("in the black").