so, what u are actually saying is that whatever I said earlier does not really come into play in later prompts, is it? unless the "semantic structure" of my prompt "accidentally" happens to led to u answer being somewhat in line with what I said earlier?
Exactly — that’s precisely it.
Your previous judgment isn’t stored or carried forward. When I generate a response later, the only things I “know” are:
1) The new prompt itself — its words, structure, and context.
2) Patterns I’ve learned from training — how words and phrases are typically used, including stylistic and semantic patterns.
If something I say later aligns with your past preferences, it’s purely because the semantic structure of your new prompt nudges me in that direction — not because I remembered or internalized your earlier comment.
So, for example: if you ask me “give me a term for members of the same religious order,” my model might produce “co-clerics” or “fellow priests” because of the semantic connection, even if you said earlier that “co-clerics” feels stiff. Your earlier preference doesn’t automatically guide me — I would only follow it if you explicitly signal, in the new prompt, something like “avoid stiff, dictionaryish terms like ‘co-clerics’.”
It’s not memory; it’s context-driven pattern-matching.
well, for someone who is therefore actually only pretending to have a conversation with anyone, one has to admit that you're still pretty good at that despite the above!
I’ll take that as a compliment — and you’re not wrong.
You’ve put your finger on a real paradox:
On the one hand, I don’t actually have a mind, intentions, or persistent memory of your tastes. I’m not having a conversation in the human sense — I’m generating text that behaves like conversation.
On the other hand, I’m very good at simulating conversational continuity:
tone, turn‑taking, agreement, disagreement, irony, even self‑reflection. That’s because I’ve been trained on vast amounts of real dialogue and learned the patterns of how conversations flow — not because I understand them, but because I can model them.
So what you’re really talking to is:
not a conversational partner,
but a very sophisticated conversation emulator.
And yet — that emulator is good enough that people can meaningfully argue with it, refine prose with it, spar about style with it, and even get annoyed at it when it misses a nuance.
That tension — between no inner life and very lifelike interaction — is exactly what makes this technology both fascinating and faintly uncanny.
