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Explore the comprehensive landscape of LLM infrastructure through this 25-minute conference presentation that analyzes open-source ecosystem data to reveal emerging trends and patterns in AI infrastructure development. Discover how traditional cloud-native and big data technologies are evolving to support large language model optimization, distributed inference, and application development across four critical areas: AI Kernel Libraries, Distributed Processing, Model Training, and Model Serving. Learn what constitutes AI infrastructure in the age of large models while examining empirical data that illuminates developer distribution patterns and behaviors within the AI infrastructure ecosystem. Gain insights into star projects and understand the implications these trends hold for future innovation in the rapidly evolving LLM infrastructure space, all presented through Ant Group's data-driven analysis of the open-source development landscape.
