Retail
Could AI Be the Future of Fake News and Product Reviews?
When Hillary Clinton's new book What Happened debuted on Amazon's Web site last month, the response was incredible. So incredible, that of the 1,600 reviews posted on the book's Amazon page in just a few hours, the company soon deleted 900 it suspected of being bogus: written by people who said they loved or hated the book, but had neither purchased nor likely even read it. Fake product reviews--prompted by payola or more nefarious motives--are nothing new, but they are set to become a bigger problem as tricksters find new ways of automating online misinformation campaigns launched to sway public opinion. Amazon has deleted nearly 1,200 reviews of What Happened since it debuted on September 12, according to ReviewMeta, a watchdog site that analyzes consumer feedback for products sold on Amazon.com. ReviewMeta gained some notoriety last year when, after evaluating seven million appraisals across Amazon, it called out the online retailer for allowing "incentivized" reviews by people paid to write five-star product endorsements.
How Walmart Is Using Machine Learning AI, IoT And Big Data To Boost Retail Performance
According to a patent application Walmart filed, it seems like its next step is integrating IoT tags to products in order to monitor product usage, auto replace products as necessary and monitor expiration dates or product recalls. These sensors would rely on a variety of technology such as Bluetooth, barcodes, radio frequencies and RFID tags and would provide Walmart with an incredible amount of data including the time of day products are used to where the products are kept in the house. This data could help create personalized advertising and expand cross-selling opportunities. If you had a tag reader installed on your fridge, it could scan everything you place inside and alert you when you need to restock or when items are expired. In another example, a RFID system could monitor how many times you pick up your laundry detergent and predict how much is left.
Japan turns to tech, adaptation to beat worst labor crunch in 25 years
Before Hisashi Kanbe in 2013 introduced BakeryScan, the world's first image recognition checkout system designed specifically for bread, it was the job of every bakery worker in Japan to memorize the assorted prices of each baked good -- from baguettes back to bagels. Unlike shrink-wrapped food, whose prices are easy to calculate by scanning barcodes, bread is usually displayed sans packaging because "it sells better that way," said Kanbe, CEO of a Hyogo-based company Brain Co. "But in a store with as many as 100 kinds of bread, it's virtually impossible for inexperienced workers to remember all of their prices." But with BakeryScan, even novices can handle purchases by placing a tray of bread under a scanner, which identifies every item based on shape and color, calculates the prices and displays the total on a screen -- all in just one second, eliminating the need for workers to manually enter prices piece by piece at the cash register. "Many bakery owners say our product has made their job much easier and much more efficient," he said, adding that the system is already used by about 250 bakeries nationwide. BakeryScan could be a game-changer for the nation's service industries, which are struggling with the worst labor shortage in a quarter of a century.
High-tech EEG headset lets you shop subconsciously
All women will be familiar with that rush of excitement that comes when you lay eyes on the perfect LBD or pair of heels. But what if technology could harness that instinctive surge of emotion to help you make the right purchase - without so much as a click of a button? The unstoppable rise of online shopping means we are overwhelmed by choice - a search for'black dress' turns up 35 million results - but increasingly, retailers are using neuroscience to predict our needs and help us filter through the myriad options available at our fingertips. Eventually, online retailers may even be able to automatically place items into our shopping cart based on our brain signals. Now, the site has partnered with brain technology company MyndPlay, using electroencephalogram (EEG) headsets to research the effects of shopping on the brain.
Gartner: Conversational Artificial Intelligence. We Need To Talk About It.
Gartner released its Top Strategic Predictions for 2018 and beyond on 29th September. I heaved a sigh of relief when I saw that one of the predictions by my esteemed colleagues read, "By 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30%." It goes on further to predict that "by 2019, half of major commerce companies and retailers with online stores will have redesigned their commerce sites to accommodate voice searches and voice navigation."Phew. This ties in perfectly with my research note, How to Exploit Conversational AI to Drive Digital Commerce, which I feared was running too far ahead of the digital commerce clients I was voicing out to since early August . Often, the conversations were met with skepticism from business unit leaders who were far too concerned about day-to-day commerce operations.
Target teams up with Google for voice shopping
Target is jumping into voice-activated shopping as it deepens its relationship with Google, offering thousands of items found in the store except for perishables like fruit and milk. The move is happening as Google says shopping will be available later this year through Google Assistant on iPhone and Android phones, joining its Google Home device and Android TV. So shoppers can shout out orders to their phone while they're running around doing errands or just walking. TTarget is jumping into voice-activated shopping as it deepens its relationship with Google, offering thousands of items found in the store except for perishables like fruit and milk. The move is happening as Google says shopping will be available later in 2017 through Google Assistant on iPhone and Android phones, joining its Google Home device and Android TV.
Order from Target nationwide by chatting with Google Assistant
For the past few years, Target has been testing the Google Express service in California and New York City. Now, the service is expanding nationwide. Starting today, you can now use Google's same-day home delivery service at Targets all across the continental US (but not Alaska or Hawaii). You can also use Google Assistant to shop with your voice; it's coming soon to eligible Android and iPhone devices and available now on Google Home devices and Android TV. Google Express is a delivery service that is somewhat of a competitor to Amazon Prime. You can shop from local stores and pay a per-order delivery fee, rather than Amazon's flat yearly fee.
Target joins other retailers in offering voice shopping
Target's higher minimum wage aims to attract and retain good staffers. See how much other big retailers are paying. This May 3, 2017, photo shows the Target logo on a store in Upper Saint Clair, Pa. Target is jumping into voice-activated shopping as it deepens its relationship with Google, offering thousands of items found in the store except for perishables like fruit and milk. The move is happening as Google says shopping will be available later in 2017 through Google Assistant on iPhone and Android phones, joining its Google Home device and Android TV.
Target Joins Other Retailers in Offering Voice Shopping
More devices are in the hands of shoppers. Even Apple has one coming out this year. But the key is personalizing the order so if a consumer shouts out "detergent," the voice assistant will know the exact brand that the shopper wants. Target says that it will give customers the option to link their accounts with Google Express for more personalized shopping. In fact, Walmart, which went live with voice shopping last week, is integrating its easy reorder feature -- which has data on both store and online purchases -- into Google Express.
Introducing Gluon: a new library for machine learning from AWS and Microsoft Amazon Web Services
Today, AWS and Microsoft announced Gluon, a new open source deep learning interface which allows developers to more easily and quickly build machine learning models, without compromising performance. Gluon provides a clear, concise API for defining machine learning models using a collection of pre-built, optimized neural network components. Developers who are new to machine learning will find this interface more familiar to traditional code, since machine learning models can be defined and manipulated just like any other data structure. More seasoned data scientists and researchers will value the ability to build prototypes quickly and utilize dynamic neural network graphs for entirely new model architectures, all without sacrificing training speed. Gluon is available in Apache MXNet today, a forthcoming Microsoft Cognitive Toolkit release, and in more frameworks over time.