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The Best RAG Technique Yet? Anthropic’s Contextual Retrieval Explained!

Anthropic has launched a new retrieval mechanism called contextual retrieval, which combines chunking strategies with re-ranking to significantly improve performance. In this video, I explain how this technique enhances retrieval accuracy, including practical implementation steps and benchmark results. Learn how to optimize your RAG systems by adding contextual embeddings, keyword-based BM25 indexing, and re-ranking to achieve state-of-the-art results. LINKS: https://www.anthropic.com/news/contex... https://github.com/anthropics/anthrop...    • Is This the End of RAG? Anthropic's N...      • Advanced RAG with ColBERT in LangChai...      • Vision-Based RAG System For Complex D...   💻 RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/c... Let's Connect: 🦾 Discord:   / discord   ☕ Buy me a Coffee: https://ko-fi.com/promptengineering |🔴 Patreon:   / promptengineering   💼Consulting: https://calendly.com/engineerprompt/c... 📧 Business Contact: [email protected] Become Member: http://tinyurl.com/y5h28s6h 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 00:00 Introduction to Contextual Retrieval 00:20 Understanding RAG Systems 00:55 Combining Semantic and Keyword Search 01:44 Challenges with Standard RAG Systems 02:48 Anthropic's Contextual Retrieval Approach 03:37 Implementing Contextual Retrieval 07:06 Performance Improvements and Benchmarks 09:02 Best Practices for RAG Systems 12:48 Code Example and Practical Implementation 15:21 Conclusion and Final Thoughts All Interesting Videos: Everything LangChain:    • LangChain   Everything LLM:    • Large Language Models   Everything Midjourney:    • MidJourney Tutorials   AI Image Generation:    • AI Image Generation Tutorials