What is fine-tuning?
Continuing to train an existing model on your own examples so it adopts a particular style, format or task.
In one sentence
Continuing to train an existing model on your own examples so it adopts a particular style, format or task.
Why it matters to a business
Expensive, slow to change, and it does not teach the model facts reliably. It is the right answer far less often than it is proposed. Try retrieval first.
RAG vs fine-tuning
Retrieval hands the model the right documents at question time. Fine-tuning changes the model itself. Retrieval is cheaper, updates instantly when your content changes, and is the right answer far more often than it gets chosen.
What is retrieval augmented generation (RAG)?
Every term here was explained to us once, too. Asking is how you learn it.
Fine-tuning, in questions
The same answer, in the shape people ask it.
What is fine-tuning?
Continuing to train an existing model on your own examples so it adopts a particular style, format or task.
Why does Fine-tuning matter to a business?
Expensive, slow to change, and it does not teach the model facts reliably. It is the right answer far less often than it is proposed. Try retrieval first.
RAG vs fine-tuning: what is the difference?
Retrieval hands the model the right documents at question time. Fine-tuning changes the model itself. Retrieval is cheaper, updates instantly when your content changes, and is the right answer far more often than it gets chosen.
Wondering what this means for your organization?
Thirty minutes, no slides, no jargon. We will tell you which of this applies to you, and which is noise.