Cloud Storage Considerations for RAG in AI Applications

Explore cloud storage considerations for Retrieval Augmented Generation (RAG) in AI applications through this 56-minute conference presentation from SNIA SDC 2024. Discover how unstructured, multi-modal data like PDFs, images, and videos can enhance foundational Large Language Models (LLMs) such as GPT-4, Mistral Large, and Llama 2 for context-aware outputs. Gain insights into leveraging cloud object storage as an ideal file system for the LLM-OS concept introduced by Andrej Karpathy, including methods for transforming and utilizing domain-specific data and storing user context. Master the RAG pattern's importance in building customized AI applications across different industries and domains, while learning to implement cloud object storage alongside vector databases for sample RAG applications. Microsoft experts Vamshidhar Kommineni and Saurabh Sensharma deliver practical knowledge on integrating cloud storage solutions with modern AI systems.