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Is your RAG system failing in production? Moving beyond "Hello World" AI requires more than just chunking text into a vector database. In this masterclass, we break down the cutting-edge evolution of Retrieval-Augmented Generation (RAG) used by top-tier engineers to handle security, massive scale, and long-term memory. We dive deep into the transition from Bi-Encoders to Cross-Encoders, the "Silo vs. Pool" security patterns for SaaS multi-tenancy, and how frameworks like SimpleMem and GraphRAG are revolutionizing how agents "remember" information. 🔍 What You’ll Learn: Bi-Encoders vs. Cross-Encoders: Why the "Hybrid" approach is the winning recipe for precision. Multi-Tenancy Security: How to use Amazon Bedrock and metadata filtering to keep tenant data isolated. Lifelong Agent Memory: Using Semantic Lossless Compression to reduce token usage by 30x. Recursive Bayesian Updates: Handling AI uncertainty with REALM. GraphRAG: Navigating complex relationships with Neo4j and PersonaAgent frameworks. Don't forget to LIKE and SUBSCRIBE if you want to stay ahead of the AI curve! 🚀 🔗 Resources Mentioned: https://celorisdesigns.com/courses/ra... #AI #RAG #MachineLearning #GraphRAG #LLM #VectorDatabase #LangChain #AIEngineering