alt Hacker NewsI reject the premise. I read the outputs I generate carefully (too carefully, probably). They don't "continue to output nonsense". Their success rate exceeds that of humans in some places.
To clarify: the problem I have with "statistical text generator" isn't the word "statistical". It's "text generator". It's been two years now since that stopped being a reasonable way to completely encapsulate what these systems do. The models themselves are now run iteratively, with an initial human-defined prompt cascading into series of LLM-generated interim prompts and tool calls. That process is not purely, or even primarily, one of "text generation"; it's bidirectional, and involves deep implicit searches.
Do you think it's akin to Ilya's [1] claim that next token prediction is reality? E.g. any deeper claims about the structure of that intelligence or comparing to humans?
To be clear, I'm 100% with you that "next token predictor" is stupid to call what these machines are now. We are engineers and can shape the capability landscape to give rise to a ton of emergent behavior. It's kind of amazing. In that sense, being precise about what's going on, rather than being essentialist (technically, yes, the 'actual' algorithm, whatever that even means, is text prediction), is just good epistemology.
I still think it's still a very interesting question though to ask about deeper emergent structures. To me, this is evidence of a more embedded cognition kind of theory of intelligence (admittedly this is not very precise). But IDK how into philosophy you are.
[1] https://www.dwarkesh.com/p/ilya-sutskever