Tutorial on Landing Generative AI in Industrial Social and E-commerce Recsys

Over the past two years, generative AI (GenAI) has evolved rapidly, influencing interdisciplinary fields including social and e-commerce Recsys.Despite several exciting research advances, landing GenAI innovations in real-world Recsys remains challenging due to the sophistication of modern industrial product and systems.Our tutorial begins with a brief overview of industrial Recsys and GenAI fundamentals (including LLMOps), followed by the ongoing efforts and opportunities to enhance existing Recsys data and model with foundation models.We then explore how GenAI's curation and reasoning capabilities can be integrated into Recsys-for example, by repurposing raw content, incorporating external knowledge for display and creative optimization, and generating personalized insights/explanations to foster transparency and trust.Following this, the tutorial highlights how AI agents can reshape Recsys by introducing interactive reasoning and action loops, moving beyond traditional passive feedback models.Lastly, we shed insights on real-world solutions for human-AI alignment and responsible GenAI practices.A key feature of the tutorial is the presentation of the holistic AI, Infrastructure, LLMOps, and Product roadmap, including evaluation and responsible AI practices, based on production solutions from LinkedIn, Amazon, Meta, TikTok, Microsoft, and Instacart.Realworld case studies and demos are further provided for illustration.While GenRecsys is still in its early stages, this tutorial provides valuable insights and practical strategies for the Recsys and GenAI communities, bridging scientific research and applied solutions in this novel and rapidly growing field.