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Kitchen disruption on the horizon as tech firms add AI, big data to food production The Japan Times

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WASHINGTON – Looking for that perfect recipe, or a new flavor combination that delights the senses? Increasingly, players in the food industry are embracing artificial intelligence to better understand the dynamics of flavor, aroma and other factors that go into making a food product a success. Earlier this year, IBM became a surprise entrant to the food sector, announcing a partnership with seasonings maker McCormick to "explore flavor territories more quickly and efficiently using AI to learn and predict new flavor combinations" by utilizing data collected from millions of data points. The partnership highlights how technology is being used to disrupt the food industry by helping develop new products and respond to consumer preferences and offer improved nutrition and flavor. "More and more, food companies are embracing digitization and becoming data-driven," said Bernard Lahousse, co-founder of Foodpairing, a startup with offices in Belgium and New York that develops digital food "maps" and algorithms to recommend food and drink combinations.


McDonald's Acquires Machine-Learning Startup Dynamic Yield for $300 Million

WIRED

Mention McDonald's to someone today, and they're more likely to think about Big Mac than Big Data. But that could soon change: The fast-food giant has embraced machine learning, in a fittingly super-sized way. McDonald's is set to announce that it has reached an agreement to acquire Dynamic Yield, a startup based in Tel Aviv that provides retailers with algorithmically driven "decision logic" technology. When you add an item to an online shopping cart, it's the tech that nudges you about what other customers bought as well. Dynamic Yield reportedly had been recently valued in the hundreds of millions of dollars; people familiar with the details of the McDonald's offer put it at over $300 million.


eBay (EBAY) Acquires Expertmaker

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"Today, eBay announced it has agreed to acquire Sweden-based Expertmaker, which specializes in providing intelligent solutions powered by artificial intelligence (AI), machine learning and big data analytics. Expertmaker has been a partner of eBay's since 2010, most recently helping with eBay's structured data initiative. Financial terms of the acquisition were not disclosed. Upon the close of the transaction, Expertmaker's employees will join eBay's structured data product and technology team. Expertmaker's Founder and CEO, Lars Hard, will join as Director, Data Science reporting into Amit Menipaz's organization.


BCS Technology Launches Machine Learning-Based Chatbot Solution to Drive Customer Insights

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ISAAC is now available on Cloudera's Solutions Gallery. ISAAC, analyses customer conversations in the airline and travel industry to derive insights and gain a 360-degree view of their customers in the easiest and most convenient way possible. The solution combines the use of modern big data analytics technologies and natural language processing (NLP) by leveraging Microsoft's LUIS framework and the Cloudera Enterprise platform. Businesses are able to create a customer experience using ISAAC that not only generates effective communication using predictive analytics, but also has the ability to collect this data and transform and translate it into prospective strategies and opportunities. "The launch of ISAAC in the wider market will have a significant impact on charting future customer loyalty strategies, sales promotions and competition in the industry," said Richard Parhusip, BCS Technology's Commercial Director.


Quantzig Highlights How Supermarkets Are Increasing Sales Growth Using Big Data Analytics - Press Release - Digital Journal

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This Smart News Release features multimedia. Big data analytics offers various benefits for supermarkets. In a blog titled What Big Data Can do for Supermarkets, global analytics and advisory firm Quantzig evaluates some of the ways supermarkets are using big data to manage their inventory and customers. Quantzig notes that analytics can "determine how quickly promoted products leave the shelf and predict when they will need to be restocked, resulting in fewer empty shelves and dissatisfied customers. This analysis can even be done while a sale is currently in progress: by analyzing the first several hours of sales, it is possible to get a stronger idea of how those items are moving, allowing you to more accurately predict necessary stock levels."