I agree that is a fundamental difference. That’s what I meant about reinforcement learning. Our ‘model weights’ are being updated with new data all the time.

I was just referring to what happens at a specific instance in time when someone asks me for example ‘What’s the capital of Norway?’

That one’s not a great example. Either you know the capital or you don’t. There’s no process (other than research) by which you can learn the name while attempting to answer.

A question I get much more often is “how do I solve this math problem?” Many times, the problem is one I’ve never seen before. So in the process of answering the question, I also learn how to solve the problem too.

While you can apply zero shot learning and get the answer to a new math problem, you are only apply the learning to significant depth after a fine-tuning session - sleep.