Err, that wasn't meant as literal example because real conversations obviously have more than 1 turn. The only thing you could prove by getting a different result is that they don't _always_ do that, even if I shared the full conversation log.
You "don't understand the need for such hyperboles" because they're not hyperboles, I don't know how you can not pick up on these errors in your own conversations.
> and pretending that models are still gpt3
I explicitly said that the new ones are better. How's that for hyperbole?
Then this entire conversation is a pointless argument - as I agree that models aren't omniscient, godlike entities that are perfect sources of truth, and that you need to use critical thinking when using them.
I don't trust models blindly, and interrogate and verify claims that they make, but that's a basic component of being a human being.
I also never try to have massive multi step conversations to the point where I'm nearing the context limits, as if there's a subclaim i need to interrogate it's far better to clear context and just start a new chat, I have notes to join up ideas.
When learning, I'm not just doing so blindly asking a model questions, I have other material up, I can look at the answer to a example question from a textbook to verify whether I have used a model to successfully learn.
This conversation is just going to devolve further into a "well it doesn't always work" to which yes, I agree, but that doesn't mean it's not useful and doesn't help the learning process.
You "don't understand the need for such hyperboles" because they're not hyperboles, I don't know how you can not pick up on these errors in your own conversations.
> and pretending that models are still gpt3
I explicitly said that the new ones are better. How's that for hyperbole?