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Explore cloud storage considerations for implementing Retrieval Augmented Generation (RAG) systems in AI applications through this 33-minute conference presentation from SNIA SDC 2025 Denver. Learn how data enhances foundational large language models like GPT-4, Mistral Large, and Llama 2 to produce context-aware outputs. Discover techniques for utilizing unstructured, multi-modal data including PDFs, images, and videos within RAG systems. Understand how cloud object storage serves as an ideal file system for LLM-based applications that transform and utilize domain-specific data while storing user context. Gain insights into storage architecture decisions that optimize performance and scalability for AI applications requiring dynamic data retrieval and processing. The session covers practical implementation strategies for integrating cloud storage solutions with RAG workflows, addressing the unique storage requirements of AI systems that need to access and process large volumes of diverse data types efficiently.
