Originally published at: Finding the Best Chunking Strategy for Accurate AI Responses | NVIDIA Technical Blog
A chunking strategy is the method of breaking down large documents into smaller, manageable pieces for AI retrieval. Poor chunking leads to irrelevant results, inefficiency, and reduced business value. It determines how effectively relevant information is fetched for accurate AI responses. With so many options available—page-level, section-level, or token-based chunking with various sizes—how do you…
Hi @SteveHan,
Is the Jupyter Notebook/source code available for following along? The results seem interesting and we would like to perform a similar analysis with our documents.
Thanks.