AI Native Netherlands is back! We'll be hosting our 13th edition at the AWS office.
Before anything else - thank you. This community has grown faster than we ever imagined, and it's been great to watch the connections be made, and the conversations getting better at every edition. The AI landscape keeps moving fast, and there's no better way to keep up than in a room full of people working through it alongside you.
We've got two amazing speakers lined up and a great venue for the evening — we'd love to see you there.
A huge thank you to our friends at AWS for hosting us at their Amsterdam office. Food and drinks will be provided!
When to run a task on a CPU versus a GPU — and what that choice does to cost.
Using fine-tuned small models (SLMs) for classifying, routing, embedding, and reranking.
Building a real CPU-first agent on Amazon EKS that calls an LLM only when needed.
Measuring price/performance in practice — and the design assumptions that turned out to be wrong.
Speaker 1: Christian Melendez (AWS)
Christian Melendez is a Principal Specialist Solutions Architect at AWS. He helps the region's largest enterprises build efficient, resilient AI and cloud-native workloads on Kubernetes, with a focus on compute efficiency, cost optimisation, and autoscaling at scale. Author of Kubernetes Autoscaling and creator of Karpenter Blueprints, a best-practices repository that grew Karpenter adoption 16.5x across EMEA, he also built Slemify, an open-source framework for fine-tuning and serving Small Language Models on Kubernetes. A regular speaker at AWS re:Invent, KCDs / CNDs, ContainerDays, and others, Christian focuses on making infrastructure simple, observable, and cost-effective at scale.
Talk: The Right Tool for the Right Token: When to Reach for a CPU or a GPU
While hard reasoning problems require an LLM and a GPU, other tasks can be solved with simpler means. Classifying, routing, embedding, and reranking are structured, high-frequency jobs
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