Stop AI From Lying: 5 Proven Techniques to Fix RAG Hallucinations

Description

AI hallucinations destroy user trust. In this video, I break down 5 production-ready techniques to prevent hallucinations in RAG question-answering systems. 🎯 What You'll Learn: Why RAG systems hallucinate and how it kills user trust LLM-as-Judge verification technique RAG pipeline improvements (reranking, contextual retrieval) System prompt optimization strategies Citation methods to minimize hallucination damage User guidance best practices 💻 Resources: Full article: [Link to medium article] GitHub repo: [Your repo link] RAG best practices guide: [Link] 🔗 Connect With Me: LinkedIn: [Your LinkedIn] GitHub: [Your GitHub] Twitter: [Your Twitter] #AIHallucinations #RAG #LLM #MachineLearning #AI Tags (Max 500 characters): RAG system, AI hallucinations, LLM hallucinations, retrieval augmented generation, vector database, machine learning, artificial intelligence, LLM validation, prompt engineering, AI development, NLP, chatbot development, AI agents, semantic search, embedding models, LLM best practices, AI engineering, Python AI, OpenAI, production AI SEO Keywords to Target: Primary: RAG hallucinations, prevent AI hallucinations, LLM hallucination prevention Secondary: RAG system optimization, LLM validation techniques, AI question answering, retrieval augmented generation best practices, fix RAG errors Long-tail: how to prevent hallucinations in RAG systems, RAG citation methods, LLM judge verification technique