(In case it was missed, I’ve added a relevant addendum to my previous comment.)
Not sure an example is needed because I agree it “explains” better than pretty much everyone. (From my mostly lay perspective) It essentially uses the prompt as an argument in a probabilistic analysis of its incredibly vast store of prior inputs to transform them into an output that at least superficially satisfies the prompter’s goals. This is cool and useful, to say the least. But this is only one kind of reasoning.
A machine without embodied perceptual experiences simply cannot reason to the full-extent of a human.
(It’s also worth remembering that the prompter (very likely) has far less knowledge of the domain of interest and far less skill with the language of communication, so the prompter is generally quite easily impressed regardless of the truth of the output. Nothing wrong with that necessarily, especially if it is usually accurate. But again, worth remembering.)
I have no idea what happened. I don’t even know what you expect me to describe. Someone feels great about something? And I don’t know what it has to do with reasoning.
That’s the point. You don’t know exactly what happened. So you have to reason your way to an answer, right or wrong.
I’m sure it elicited ideas in your head based on your own experiences. You could then use those ideas to ask questions and get further information. Or you could simply pick an answer and then delve into all the details and sensations involved, creating a story based on what you know about the world and the feelings you’ve had.
I could have created a more involved “prompt story” one with more details but still somewhat vague. You would probably have either jumped straight to a conclusion about what happened or asked further questions.
Something like “He kicked a ball at my face and hit me in the nose. I laughed. He cried.”
Again, vague. But if you’ve been in such a situation you might have a good guess as to what happened and how it felt to the participants. ChatGPT would have no idea whatsoever as it has no feelings of its own with which to begin a guess.
Consider poetry. How can ChatGPT reason about poetry? Poetry is about creating feeling. The content is often beside the point. Many humans “fail” at understanding poetry, especially children, but there are of course many humans that “get it”, escpecially after building up enough life experience. ChatGPT could never get it.
Likewise for psychedelic or spiritual experiences. One can’t explain such experience to one who has never had it and ChatGPT will never have it.
You're talking about describing your memories of your inner experiences. Memories transform with time, sometimes I'm not sure if what I think I remember actually happened to me, or if this is something I read or seen in a movie, or someone else described it to me. Fake memories like that might feel exactly the same as the things that I actually experienced.
GPT-4 has a lot of such fake memories. It knows a lot about the world, and about feelings, because it has "experienced" a lot of detailed descriptions of all kinds of sensations. Far more than any human has actually experienced in their lifetime. If you can express it in words, be it poetry, or otherwise, GPT-4 can understand it and reason about it, just as well as most humans. Its training data is equivalent to millions of life experiences, and it is already at the scale where it might be capable of absorbing more of these experiences than any individual human.
GPT-4 does not "get" poetry in the same way a human does, but it can describe very well the feelings a human is likely to feel when reading any particular piece of poetry. You don't need to explain such things to GPT-4 - it already knows, probably a lot more than you do. At least in any testable way.
Not sure an example is needed because I agree it “explains” better than pretty much everyone. (From my mostly lay perspective) It essentially uses the prompt as an argument in a probabilistic analysis of its incredibly vast store of prior inputs to transform them into an output that at least superficially satisfies the prompter’s goals. This is cool and useful, to say the least. But this is only one kind of reasoning.
A machine without embodied perceptual experiences simply cannot reason to the full-extent of a human.
(It’s also worth remembering that the prompter (very likely) has far less knowledge of the domain of interest and far less skill with the language of communication, so the prompter is generally quite easily impressed regardless of the truth of the output. Nothing wrong with that necessarily, especially if it is usually accurate. But again, worth remembering.)