[kuida0r3]

Andrew Ng's deeplearning.ai just released a course on this yesterday https://www.deeplearning.ai/short-courses/finetuning-large-l... - at a high level it lets one put more data into the model than fits into the prompt.

And yes your use case of a large private knowledge base is one of the prime examples she used in the course. Scenarios that are domain-specific or privacy conscious probably makes more sense for finetuning as opposed to prompting.

[OthmaneHamzaoui]

But can't you still achieve domain-specific or privacy conscious cases by using retrieval + vector dbs?

[kuida0r3]

Not an expert but my understanding is retrieval+vector db enables accurate information retrieval, whereas finetuning is more focused on specific task performance and generating coherent text (maybe in a different style) generally.