Another possibility is that the only thing that LLMs are doing is encoding the structural data that exists in natural language. For example, you can load a corpus into vector space and then do algebra like:

  let v = man - woman;
  let r = king - v;
  assert( r == queen );

or so I'm told.

And then it turns out that those structures only have the intelligence of a child. Arbitrary LLM and other ML advancements that focus solely on scanning large natural language datasets may never be able to advance past child level intelligence if the intelligence that they're approximating isn't better than a child.