RAG vs Context

Оригинальный автор：Tech and Biz Hub

Первоисточник：https://www.youtube.com/embed/3AnUx42h6Mk

Is RAG dead now that models support million-token context windows? Not so fast. In this video, we break down the RAG vs long context debate and explore when to use each approach. Learn why RAG (Retrieval Augmented Generation) still matters for enterprise-scale data, and why long context windows win for smaller, complex reasoning tasks. We cover: ✓ Why LLMs struggle with knowledge cutoffs and private data ✓ How RAG and vector databases work (simplified) ✓ The rise of million-token context windows ✓ Simplicity vs. Cost: The real trade-offs ✓ Why long context has the "lost in the middle" problem ✓ Why RAG is still essential for enterprise data at scale ✓ A practical framework to choose the right approach for YOUR project Perfect for developers, engineers, and AI enthusiasts building LLM-powered applications. Whether you're optimizing costs, handling massive datasets, or building complex reasoning systems—this video gives you the clarity to make the right architectural choice. #RAG #LargeLanguageModels #LLM #VectorDatabase #AI #MachineLearning #LLMDevelopment #RetrievalAugmentedGeneration #ContextWindow #GenerativeAI #AIArchitecture #LLMEngineering #DataScience #ArtificialIntelligence