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Stop Losing Context! How Late Chunking Can Enhance Your Retrieval Systems

In this video, I explore the powerful technique of late chunking in long context embedding models. By preserving contextual information across entire documents before chunking, this method offers more precise retrieval while minimizing storage needs. Join me as I compare it to other methods like Anthropic's contextual retrieval and provide insights for implementing it in your applications. LINKS: Colab: https://tinyurl.com/ynxjjyu8 https://jina.ai/news/late-chunking-in... https://jina.ai/news/what-late-chunki... https://weaviate.io/blog/late-chunking https://arxiv.org/pdf/2409.04701 https://www.anthropic.com/news/contex... https://github.com/jina-ai/late-chunk...    • Contextual Retrieval with Any LLM: A ...      • The Best RAG Technique Yet? Anthropic...   💻 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 and Late Chunking 00:28 Understanding Embedding Models and Their Parameters 00:55 Challenges with Standard RAG Pipelines 02:08 Late Chunking Explained 03:06 Implementation and Benefits of Late Chunking 05:21 Comparing Late Chunking with Other Techniques 10:51 Practical Implementation Guide 16:09 Conclusion and Further Resources All Interesting Videos: Everything LangChain:    • LangChain   Everything LLM:    • Large Language Models   Everything Midjourney:    • MidJourney Tutorials   AI Image Generation:    • AI Image Generation Tutorials