Bifalgorithm post

Everyone talks about the drag and fine tuning. Like they are the two flavours of the same thing. But they are actually not. And picking the wrong one can cost you thousands of GPO bills. Here is the real difference. Listen carefully. A company was building an internal AI assistant, so employees could go and ask about company policies. First, they tried fine-tuning, like training their models directly on their documents. But the policies keep changing every now and then, and retraining every time means expensive GPU cost and massive delays. So that's the real problem with fine-tuning. You're teaching the model new behavior, but its knowledge freezes the moment training ends. So instead, they have switched to drag. They didn't retrain the model at all. Instead, relevant documents were retrieved and handed to the model. model as context with every query. Now, whenever a policy updates, they just update the document. The model automatically uses the latest information. No retraining needed. So fine tuning changes how model behaves and drag changes what information it has access to.

Everyone talks about the drag and fine tuning. Like they are the two flavours of the same thing. But they are actually not. And picking the wrong one can cost…