ADS & ECAAI | Applied AI for Retail
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 VerhagenĀ
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.
Zoom details to follow soon.