Our talk commences with an insightful exploration into the fundamental concepts of Graph, Graph Databases, and NebulaGraph.

We will demystify: the innovative integration of Graph + Large Language Models (LLM) and demonstrate how this potent combination enhances both existing LLM stacks and Knowledge Graph processes.

Moving forward, we'll focus on Docker and Docker Extensions. We'll explore how containerization and the Docker extension facilitate a seamless development and learning environment for NebulaGraph, NebulaGraph AI, and NebulaGraph LLM. We'll explore how these technologies simplify intricate processes into one-click solutions.

This talk will demonstrate how leveraging Docker optimizes infrastructure, accelerates dev/production deployment, and enhances AI development efficiency.

"It is a must-attend for those intrigued by the potential of streamlining distributed graph-based machine learning and AI infrastructure."