Abstract
AI inference is expensive, but it doesn’t have to be. In this talk, we’ll break down how to systematically drive down the cost per token across different types of AI workloads. Using real-world examples from data transformation, offline agents, and aggregated insights, we’ll unpack how to measure, optimize, and ultimately produce the world’s cheapest tokens. The session will be hardware-agnostic, featuring analysis of both Nvidia and AMD GPUs, and will include advice which can be implemented by using open-source serving frameworks such as Dynamo, vLLM, and SGLang.
What you'll take away:
- Token Economics 101 - Understand what actually drives cost per token
- Inference Optimization Tactics that can be used to drive down unit economics depending on the AI workload type
- Right GPU, Right Job - Ho two choose hardware and deployment strategy for maximum cost performance
Speaker
Meryem Arik
Co-Founder and CEO @Doubleword (Previously TitanML), Recognized as a Technology Leader in Forbes 30 Under 30, Recovering Physicist
Meryem is the Co-founder and CEO of Doubleword (previously TitanML), a self-hosted AI inference platform empowering enterprise teams to deploy domain-specific or custom models in their private environment. An alumna of Oxford University, Meryem studied Theoretical Physics and Philosophy. She frequently speaks at leading conferences, including TEDx and QCon, sharing insights on inference technology and enterprise AI. Meryem has been recognized as a Forbes 30 Under 30 honoree for her contributions to the AI field.
Find Meryem Arik at:
Date
Wednesday Nov 19 / 10:35AM PST ( 50 minutes )
Location
Ballroom A
