But it’s also based on neurons with far more complex behavior than artificial neurons and also has other separate dynamic systems involving neurochemicals, various effects across the nervous system and the rest of the body (the gut becoming seemingly more and more relevant), various EEG patterns, and most likely quantum effects.
I personally wouldn’t rule out that it can’t be emulated in a different substrate, but I think calling it “an algorithm” is to def stretch and misapply the usefulness of the term.
Ah ok. Here you use the word “explain” which implies more of a descriptive, reducing action rather than extrapolative and constructive. As in, it can explain what it has “read” (and it has obviously “read” far more than any human), but it can’t necessarily extrapolate beyond that or use that to find new truths. To me reasoning is more about the extrapolative, truth-finding process, ie “wisdom” from knowledge rather than just knowledge. But maybe my definition of “reasoning” isn’t quite right.
Edit: I probably should define reasoning as solely “deductive reasoning”, in which case, perhaps it is better than humans. But that seems like a premature claim. On the other hand, non-deductive reasoning, I have yet to see from it. I personally can’t imagine how it could do so reliably (from a human perspective) without real-world experiences and perceptions. I’m the sort that believes a true AGI would require a highly-perceptual, space-occupying organ. In other words it would have to be and “feel” embodied, in time and space, in order to perform other forms of reasoning.
(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.)