Register: https://gdg.community.dev/events/details/google-gdg-berlin-presents-ai-amp-cloud-graph-based-recommenders-and-cost-efficient-generative-architectures/

Join us for a deep dive into two exciting froantiers of AI. We’ll explore how graph-based approaches can enhance recommendation systems, and how to architect scalable, cost-efficient generative AI platforms using Cloud Run, GKE, and Vertex AI. Expect practical insights into building smarter algorithms and running them efficiently in the cloud.

A Sommelier's Guide to Recommendation Algorithms: Classical and Graph-Based Recommender Systems

by Moritz Wegener Recommendation engines are all around us – on Netflix, Spotify, Amazon and many other platforms, they subtly shape what we watch, listen to, or buy. In fact, around 80% of what users watch on Netflix comes from recommendations, making these systems critical for user satisfaction and engagement. But building effective recommendation systems comes with challenges: massive datasets, complex user preferences, and the need for fast, accurate predictions.