Part of why I comment is specifically to attract naysayers. I can learn from them. I've never been one to mind being wrong. I will argue vehemently for a position both because it seems correct to me, but also because it exposes my ideas to be torn down, so when I rebuild them they can be better.

I looked into things a number of people just in this thread brought up. It was a very rewarding discussion for me. I feel like my understanding is better than before it.

I became frustrated with you because your stance seemed a combination of "you can't prove it" and "it works like it does because it is what it is". You weren't expanding on your positions. It is possible that you are assuming context others in the thread do not share. It seems likely you think many here are reading into or seeing things that aren't actually present. Being tricked by the model, essentially. It is possible. But it also seemed possible that you were simply enjoying telling everyone they are wrong for fun.

With your refusal to expand on anything, it all looks much the same from this side.

I would like to understand what perspective you were arguing from, because even if I disagree with it in the end, knowing your perspective will allow me to understand where my own may be weak or flawed, and either shore it up or discard and rebuild it.

It is very frustrating to have a discussion with someone who seems to only contradict, but never explain their contradictions. They may be right. You may be right. But it was frustrating to talk to you because you didn't seem to want to say where or how people were wrong.

"It's not a brain". "It's works because it's a language model".

Okay, it's not a brain and it's just a language model. How does it perform what appears to be, whether it is or not, obvious translation of subtext in sentences between unrelated literal domains?

When I specifically asked if your position was simply that you would not attribute "meaning" to its representations, you declined to respond.

That's not an unfair position to take. An LLM has no experiential data in it. It has only the words. Philosophically, one could argue that even if it were "proven intelligent", it would still have no knowledge or contain actual meaning because it has only the words to go by. That would be a reasonable position, but you wouldn't confirm if that was what perspective you were taking.

I genuinely would enjoy knowing how you think translations on the level of the one I presented happened. Another poster discussed "latent spaces" where terms can grow closer even if not literally related. Articles I've read indicate any number of surprising results from LLms, assertions that LLMs can or cannot reason, various levels of assertion on whether LLMs can "understand" things. It appears like there are many perspectives active in this field all at once, and that they are quickly out of date as better and better LLMs are trained.

If you would be so kind, please add context to when you correct others. Pointers we can follow in order to understand your perspective.

For much of the thread, it felt like you were arguing that deep blue can't actually play chess because it has no concept of games or people or chess pieces or winning or losing, rather it only performs statistical analyses of numerically represented move sets and just outputs a move based on that statistical analysis. How can it play chess, after all, if it doesn't know what chess is?

>This kind of conversation doesn't work well on the internet

Possibly. I appreciate your having it nonetheless, as I have no one I know that cares to discuss any of this. So I have to make due with discussing it in online forums :)