Many data scientists dream of using their skills to develop ground-breaking AI technology. Yet, few manage to translate their dreams into commercially viable products – or even know where to begin. In this episode, start-up founder Dr Jeroen Vendrig joins Dr Genevieve Hayes to discuss his experiences in developing AI-driven products, both in an academic setting and in a variety of organisations within the commercial world.This is the first part of a three-part special focussing on the use of data science in start-ups.Guest BioDr Jeroen Vendrig is the Chief Technology Officer of ProofTec, an Australian technology start-up specialising in the development of AI-driven software for damage detection and assessment of high value assets. He has over 20 years’ experience in video analytics with world leading R&D labs and has over 25 patents in force.Talking PointsThe key differences between doing data science/AI in an academic setting and doing it in the commercial world.How to go about translating academic research into commercially viable AI-based products.What makes for a successful university/commercial collaboration?The challenges of building AI products from scratch, including lack of data and how to tell if a project has the potential to be commercially viable.Protecting IP for AI systems.The impact of having real end users on AI product development.The most valuable skills data scientists can develop for building commercial AI technologies.LinksConnect with Jeroen on LinkedInProofTecConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

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