Earlier quoted context omitted.
Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many things, but the question that matters is whether statistical models of language can ever “learn” abstract thought, or become part of a system which uses them as a tool. My personal assessment is that LLMs can do neither.
Words are the "simplistic" projection of an LLM's abstract thoughts. An LLM has: words in its input plane, words in its output plane, and A LOT of cross-linked internals between the two. Those internals aren't "words" at all - and it's where most of the "action" happens. It's how LLMs can do things like translate from language to language, or recall knowledge they only encountered in English in the training data whil…
The heavy lifting here is done by embeddings. This does not require a world model or “thought”.