Food, Beverage & Tobacco


Using AI, Predictive Analytics, and Recommendations - DZone Big Data

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Here's what retailers can get from using recommendation systems: Increased customer loyalty by sending offers based on specific customer needs. The idea is simple: we define a market basket for every customer and calculate the distance between the specific customer and others having similar items in the market basket. Then, we recommend customers buy the goods purchased earlier by those customers with similar market baskets. If a customer feature set coincides with an item feature set, then this customer gets a recommendation for this specific item.


How Artificial Intelligence Is Taking Over The World [VIDEO]

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Giant tech companies, like Google, Apple, and Amazon, believe that the next economic wave will be driven by artificial intelligence. For example the UK only spent $53.5 billion on research and development while Russia spent $47.6 billion. Aside from spending truckloads on research and development, these tech companies are also acquiring companies in different industries. For example, Amazon has acquired giant retail Whole Foods which has scared a lot of grocery stores around the world.


Amazon just acquired a training ground for retail artificial intelligence research

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Big-box grocery stores are easy sources of data on human purchasing behavior. Obviously, Amazon already collects a ton of data on consumer purchasing behavior, but it's relatively new to groceries and brick-and-mortar retail in general. Amazon just acquired a company that can improve its AI models on both of those counts. The logistics of shipping fresh food around the country are not easy, and that generates a ton of specialized data that Amazon can use to improve its own distribution strategies as well as build a cloud retail AI product for AWS customers.


What will Whole Foods of the future, powered by Amazon, look like?

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Amazon essentially plans to shake up this notion with sophisticated technology like artificial intelligence, computer vision, customer profiling, and drone delivery systems. Amazon has already outlined some of its high-tech ambitions to kill long lines at grocery stores when it previewed its concept store Amazon Go back in December. In the end, Amazon just wants to make it easier for people to buy things from Amazon stores. SEE ALSO: Amazon's delivery drone system is getting parachutes for your packages Ultimately, Amazon's goal is simply making it easier for people to buy stuff from the company.


Forget driving to the supermarket, this one wants to come to you instead

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You pull out your phone, click a button -- and a grocery store pulls up in front of you. That's essentially the concept behind Moby Mart, an autonomous, self-driving grocery store on wheels. The firm behind it is a Swedish startup aptly named Wheelys Inc. SEE ALSO: Google's autonomous car company is now testing out self-driving trucks The Moby Mart, which is about the size of small bus, carries a selection of everyday products like snacks, meals, basic groceries, and even shoes. "We've tested it [the prototype] on the roads around our assembly plant and in the campus area at Hefei University," Wheelys co-founder Per Cromwell told news outlet news.com.au.


Amazon’s homegrown products are moving beyond batteries and baby wipes

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Its ambitious new efforts include a host of higher-end fashion lines and premium food labels. On the other hand, the company's more basic apparel brand, Amazon Essentials, proudly wears the corporate badge. They've made some headway in the time since, according to a recent research report from Slice Intelligence, but still lag far behind department-store counterparts. "Consumers are willing to buy private label apparel brands online, particularly from the brands that they are familiar with in the offline world."


Yeah, the Tinder pick up line from Master of None? It probably won't work for you.

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Be honest: you've thought about stealing that genius Whole Foods line from Master of None, right? The world first witnessed Aziz Ansari's character Dev deploy his go-to dating app opener, "Going to Whole Foods, want me to pick up anything?," in the "First Date" episode. It was an actual line a friend of the show's creators used to get a massive response. She posted about it on Facebook -- as she does with all her ridiculous messages -- and a friend explained the line's origins.


Qualitative Research Methods for Data Science?

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First, we should remember that two people may buy the same brand for the same reasons (Miller Lite tastes great). However, they may also buy the same brand for different reasons (Miller Lite tastes great versus Miller Lite is less filling), or buy different brands for the same reasons (Miller Lite tastes great versus Bud Light tastes great) or buy different brands for different reasons (Miller Lite is less filling versus Bud Light tastes great). There are many other ways qualitative can help inform quantitative research, but a fuller elaboration would require much more space than I have here. And, of course, we all can be guilty of condemning sweeping generalizations with... sweeping generalizations!


Are Amazon's AI-powered Go stores on their way to the British high street?

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With a beta testing store size of just 1800 square feet, while convenient, does not leave room for many products on the shelf. 'Just Walk Out' is powered by a combination of deep machine learning, sensor fusion, and computer vision. While details are sparse, it is presumed that after scanning into the store with their associated Amazon account, computer vision tracks customers as they shop. The computer vision tracking, combined with the weight sensors could synchronise with an Amazon account, charging customers as they leave the store.


Artificial intelligence in grocery stores could affect what you buy and pay

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The platform, provided by Blue Yonder, uses big data and machine learning to predict exactly what stock is needed based on historic sales data, as well as outlying variables like the weather surrounding each individual store, nearby events and, in cases where the AI gets the prediction wrong, it can learn from its mistakes.