models dont have access to information, we can augment information to it using rag
embeddings are a way to represent words, phrases and images as vectors in a high dimentional space
there’s an implication here, larger the input to the embedding, the worse it is in quality.
so how would you approach embedding content longer than a simple phrase?
chunking is the process of breaking material down into digestible chunks for the embedding search to search better