Integrating AI with Real-time Data and RAG - Part 2

Learn how to integrate external, real-time data sources with fine-tuned AI systems in this comprehensive 29-minute video tutorial. Explore the fundamentals of customizing Large Language Models (LLMs) for specific operational needs, drawing parallels with vehicle customization to illustrate the concept. Master technical methods for connecting AI to external databases and data lakes, including SQL prompts and Retrieval Augmented Generation (RAG) techniques. Discover new tools like Databricks RAG for building production-ready applications while understanding the distinctions between simple keyword searches and complex vector searches. Examine critical challenges in AI data integration, including vector space construction, data privacy considerations, and context length limitations. Gain practical insights into creating effective vector spaces for data retrieval, managing privacy risks associated with vector embeddings, and selecting appropriate methods for connecting AI systems to external data sources.