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That's highly reductive of our capacities. We are not weighted transformers that can be explained in an arxiv paper. GPT, at the end of the day, is a statistical inference model. That's it. It's not going to wake up one day, decide it prefers eggs benny and has had enough of your idle chatter because of that sarcastic remark you made last week. Could we simulate a plausibly realistic human brain on silicon someday? I don't know, maybe? But that's not what GPT is and we're no where near being able to do that. You can scale up the tokens an LLM can manage and all you get is a more accurate model with more weights and transformers. It's not going to wake up one day, have feelings, religion, decide things for itself, look in a mirror and reflect on its predicament, lament the poor response it gave a user, and decide it doesn't want to live with regret and correct its mistakes. |
I'm not saying that GPT4 is as capable as a human-- it can not be, by design, because its architecture lacks memory/feedback paths that we have.
What I'm saying is that HOW it thinks might already be quite close in essence to how WE think.
> We are not weighted transformers that can be explained in an arxiv paper. GPT, at the end of the day, is a statistical inference model. That's it.
That is true but uninteresting-- my counterpoint is: If you concede that our brain is "simulatable", then you basically ALREADY reduced yourself to a register based VM-- the only remaining question is: what ressources (cycles/memory) are required to emulate human thought in real time, and what is the "simplest" program to achieve it (that might be something not MUCH more complicated than GPT4!).