In this Intel on AI podcast episode: There is a massive amount of insight to be gained by studying brick and mortar customer behavior. Yet capturing, labeling, and analyzing that data can be a very complicated and compute intensive activity. Dan Klein, Chief Data Officer at Valtech, joins the Intel on AI podcast to discuss how Valtech’s project VOID (Visual Object Identification) uses Intel® NUCs and the Intel developer stack to capture retail customer data like customer locations, face metadata, and apparel metadata to provide incredible real time insights for retail organizations. He talks about how powerful this technology can be to help retailers better analyze and cater to their customers in real-time but also how sensitive capturing individual information can be from a privacy and bias standpoint. Dan highlights how Valtech is proactively working to build their training data sets to include a diverse set of individuals of different genders and ethnic backgrounds to fight discrimination and bias in their analysis. He addresses the importance of ensuring individual privacy and fighting gender and racial bias in AI analytics and highlights that building a strong and diverse team at Valtech provides the foundation for this effort.

To learn more, visit:
valtech.com

Visit Intel AI Builders at:
builders.intel.com/ai

Tags: AI, artificial intelligence, Dan Klein, deep learning, machine learning, natural language processing, Supercomputing, Valtech, visual analytics
 
Posted in: Artificial Intelligence, Audio Podcast, Intel, Intel on AI