Unveiling the Magic: Scaling Large Language Models to Serve Millions
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Patrick Koss
STACKIT
Tech Lead
In this beginner-friendly talk, we’ll explore the scaling laws that explain how AI performance improves as we scale up compute. You’ll learn how models are pre-trained and why bigger models often deliver better results. You will understand why developers and researchers use techniques like fine-tuning and distillation to optimize model performance and why reasoning models continue to push performance even further. What does this mean for developers building real AI applications? No advanced math required — just curiosity and a desire to understand the next generation of AI models.
World Congress 2025
Patrick Koss
STACKIT
Tech Lead
Andrew Wafaa
Arm
Engineering Lead for Generative AI
Andreas Blattmann
Black Forest Labs
Co-Founder
Ankit Patel
NVIDIA
Senior Director Developer Marketing
Lucie-Aimée Kaffee
Hugging Face
EU Policy Lead & Applied Researcher
Matt White
Linux Foundation
General Manager of AI
Philipp Schmid
Google DeepMind
AI Developer Experience
Andreas Erben
daenet
CTO for Applied AI