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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.

Agenda

17:30 – Doors Open
Arrive early, grab a drink, and meet the community before the talks kick off.

18:00 – Scaling Generative AI: Cost-Efficient Multimedia Platform Architecture with Cloud Run, GKE, and Vertex AI
by Nikolai Danylchyk
This talk is a deep-dive into building a cost-optimized, multi-tenant platform for generating diverse multimedia content, including text, images, 2D/3D models, and audio. We will explore the technical challenges and solutions for balancing high throughput with low operational cost with Intelligent GPU Allocation, Decoupled Workloads and Granular Resource Sharing.

☕️ Break – 10 min

18:50 – 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.

☕️ Break – 10 min

19:40 – TBD Talk
Details to be announced — stay tuned!

🕺 Networking until 21:30 💃
Enjoy discussions with the speakers and connect with fellow AI & cloud practitioners.

🍕 Food, snacks, and drinks will be served.

🙏 Thanks to Google Berlin for hosting and to our partners Google Cloud ,CLOUDPILOTS Software & Consulting GmbH & Neo4j

Huge thank to Diana Nanova Lisa Nöth Katsiaryna Skwarek Jakob Pörschmann Alexander Erdl. who made this event possible