Creating our own Private OpenAI API

Meryem Arik and Hannes Hapke discuss the challenges and strategies for deploying open-source Large Language Models (LLMs) effectively. They provide a roadmap for startups and corporations, covering infrastructure requirements, optimization, and lessons learned from real-world deployment experiences. The talk emphasizes the importance of self-hosting LLMs for data privacy, low latency, and cost-effectiveness at scale. Key technical aspects covered include batching servers, inference optimization, memory optimization, GPU infrastructure, model controllers, and the future of LLM APIs in 2025 with multimodal models and composability.