[mirzap]

Vector DBs don't create embeddings; they store them. As the article points out, the LLM's slowness to respond diminishes the performance that vector DB's can potentially add.

[singularity2001]

You can easily create embeddings locally though, with small (L)LMs. Three lines of code using hugging face. I don't understand the point of this article.

[mirzap]

Look it this way: you have a web app that can handle 10 req/s. It does not matter if you add a database behind it that can handle 10,000 req/s. 10 req/s still limit you. You're not gaining any performance benefits. I always wondered why you would need a dedicated vector DB.

[singularity2001]

vector DBs have much higher 'semantic' recall than classical search engines if you want to ask questions about your documents or previous discussions.

[luke-stanley]

Actually, some Vector DB's can generate embeddings as well as storing them, Chroma in particular uses SentenceTransformers models.