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In this webinar we will be exploring how 𝗔𝗜 is and can be used in the retail sector.
𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗲
12:00 Introduction & Welcome
12:05 Talk #1 The rise of robots in retail stores: An exploration of first opportunities
12:20 Q&A
12:30 Talk #2: How we introduced data science into a new 'space' within bol.com
12:50 Q&A
13:00 End!
𝗧𝗮𝗹𝗸 #𝟭 𝗯𝘆 𝗧𝗶𝗯𝗲𝗿𝘁 𝗩𝗲𝗿𝗵𝗮𝗴𝗲𝗻
Tibert Verhagen is a professor Emerging Technology for Business at the Amsterdam University of Applied Sciences. His research projects center on innovative technology, store innovation and information systems. His research has been published in academic journals and business magazines. He has been involved in setting up master programs and business startups. He is one of the chairmen of the Robots in Retail expert group of the ShoppingTomorrow program.
Robots are expected to bring change to the future of retail. Driven by developments in artificial intelligence, machine learning, speech and voice technology, and sensory technology, robots will be increasingly able to perform tasks for the retailer autonomously. This could include managing stock, cleaning the store, welcoming customers, providing entertainment, and delivering purchases at home. Still, many retailers wonder what the possibilities of robots are today. The expert group Robots in Retail of ShoppingTomorrow explored the opportunities of robots for physical stores. The results of this exploration are shown and discussed in the presentation.
𝗧𝗮𝗹𝗸 # 𝟮 𝗯𝘆 𝗠𝗮𝗿𝗹𝗼𝗲𝘀 𝗞𝘂𝗶𝗷𝗽𝗲𝗿
Marloes Kuijper is a data scientist from the Netherlands. She has a background in computational linguistics and NLP. She has been at bol.com for two years, and is currently working on implementing data science solutions in the Platform Quality department.
At bol.com, data science has been successfully embedded into various different product teams. Yet, in order to keep innovating, they also explore data science opportunities in new or previously unexplored departments. Last September, Bol.com started a new data science task force within the Platform Quality department. In this talk, she will explore what it's like to start a data science team in a new domain and how you can optimize this process much like a machine learning algorithm itself. She will explain the resemblance between their way of working and multi-armed bandit algorithms and how it can help you to avoid common pitfalls and be more confident about the long-term success of your data science project.
