They have a chart that shows it. The education level of the input determines the education level of the output.

These things are supposed to have intelligence on tap. I'll imagine this in a very simple way. Let's say "intellignce" is like a fluid. It's a finite thing. Intelligence is very valuable, it's the substrate for real-world problem solving that makes these things ostensibly worth trillions of dollars. Intelligence comes from interaction with the world; someone's education and experience. You spend some effort and energy feeding someone, clothing them, sending them to college. And then you get something out, which is intelligence that can create value for society.

When you are having a conversation with the AI, is the intelligence flowing out of the AI? Or is it flowing out of the human operator?

The answer to this question is extremely important. If the AI can be intelligent "on its own" without a human operator, then it will be very valuable -- feed electricity into a datacenter and out comes business value. But if a model is only intelligent as someone using it, well, the utility seems to be very harshly capped. At best it saves a bit of time, but it will never do anything novel, it will never create value on its own, independently, it will never scale beyond a 1:1 "human picking outputs".

If you must encode intelligence into the prompt to get intelligence out of the model, well, this doesn't quite look like AGI does it?

In general it will match the language style you use.

If you ask a sophisticated question (lots of clauses, college reading level or above) it will respond in kind.

You are basically moving where the generation happens in the latent space. By asking in a sophisticated way you are moving the latent space away from say children's books and towards say PhD dissertations.