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Efficient Serving of LLMs for Experimentation and Production with Fireworks.ai

Posted Oct 18, 2023 | Views 453
# LLMs for Experimentation
# LLMs for Production
# Fireworks.ai
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Dmytro Dzhulgakov
CTO, Co-Founder @ Fireworks AI

Dmytro (Dima) Dzhulgakov is the co-founder and CTO of Fireworks.ai, which focuses on the transition to AI-powered business via interactive experimentation and a production platform centered around PyTorch technologies. Fireworks.ai offers high-performance low-cost LLM inference service that helps to try out and productionize large models.

Dmytro is one of PyTorch core maintainers. Previously he helped to bring PyTorch from a research framework to numerous production applications across Meta's AI use cases and broader industry.

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Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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SUMMARY

Deploying LLMs to products is no easy feat. It's common to have dozens of model variants when trying things out. As usage scales up, cost-to-serve and latency become primary concerns. In this talk, we will dive into how Fireworks.aI GenAI Platform helps developers on the journey from early experimentation to highly loaded production deployments without breaking the bank.

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