The Stack Overflow Podcast Chunking express: An expert breaks down how to build your RAG system
Mar 5, 2024
Roie Schwaber-Cohen, a developer advocate at Pinecone, breaks down the fascinating world of Retrieval Augmented Generation (RAG). He discusses chunking techniques and the future of content formatting, emphasizing the importance of structured data. Roie reveals strategies for effectively integrating generative AI into organizations, along with the cost-saving benefits of RAG. He also shares insights on enhancing query handling in RAG systems and the collaboration between large language models and graph databases to improve data accuracy.
AI Snips
Chapters
Transcript
Episode notes
Chunking Importance
- Chunking is important but not the most crucial part of building a RAG system.
- Simple recursive text segmentation or markdown segmentation often suffices for chunking.
Begin with Business Case
- Before adding GenAI, define the business case clearly.
- Experiment with playgrounds and test models to understand what fits your needs.
Choose RAG for Most Companies
- Building your own LLM is high effort and cost, suited mainly for Fortune 10 companies.
- For most, RAG offers low cost, explainability, and easier use without needing ML engineers.