Training, Fine-Tuning, or RAG: How to Choose for Your AI?
Introduction
A question comes up frequently when I work with companies on their AI projects: "Should we train our own model?". Or the slightly more advanced variant: "We want to fine-tune a model on our data".
Every time, I need to take a moment to explain what that actually means in practice. Because between training a model from scratch, fine-tuning it on your own data, or simply giving it context with a RAG, there is a world of difference. In cost, time, complexity, and above all in outcome.
In this article, I will try to lay things out simply. What is an AI model, how do you train it, what does it cost, when is it worth it, and most importantly why in 95% of cases you probably do not need to do either.