Name: AI & Cloud: Graph-Based Recommenders and Cost-Efficient Generative Architectures
Start: 2025-10-30T17:30:00+01:00
End: 2025-10-30T20:30:00+01:00
Location: Google Office Berlin

**Important! Registration possible ONLY here [https://gdg.community.dev/events/details/google-gdg-berlin-presents-ai-amp-cloud-graph-based-recommenders-and-cost-efficient-generative-architectures/](https://gdg.community.dev/events/details/google-gdg-berlin-presents-ai-amp-cloud-graph-based-recommenders-and-cost-efficient-generative-architectures/)**

**Every attendees must provide a real name with identification document in order to enter the building. Every Registration without Full Name will be deleted.**
​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.

Shrinish

Emy Jamalian

Louis Tsai

Mohamed islem ayari

Alex Mir

Google Developer Group Berlin (GDG Berlin)

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AI & Cloud: Graph-Based Recommenders and Cost-Efficient Generative Architectures

Artificial Intelligence Machine Learning Robotics

Google Office Berlin

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AI & Cloud: Graph-Based Recommenders and Cost-Efficient Generative Architectures

Google Developer Group Berlin (GDG Berlin)

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