🧠 Problem: Too much data for embedding? 🤯🧩 Solution: Chunk your data! ✂️

A core principal of RAG is to search through your data to use as an input for LLMs. You can embed the data into a vector so it is searchable, but if you have a large video or entire book that will be too much data in one embedding.

Let’s talk about some strategies for chunking your data for using with embedding models.

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