I think, the key word here is "mostly". If it doesn't do better, the transformation is really that we have managed to engineer reliability and repeatability out of machines, which have been their defining characteristic in the past.

So, will they do better? I personally think that knowledge is about implications. Notably, things that are similar do not necessarily have identical implications. And I can't see LLM tackling this issue anytime soon. (I even doubt that LLMs provide a suitable approach to this, at all.) So we'll probably end up with "we managed to get rid of reliability", which may be just the opposite of the role, the computer plays in Star Trek scripts.

*) To provide a bit of context to reliability and repeatability: These are really externalization of the major generalizations of Husserl's life-world (Lebenswelt), as in "and so on" and "I can do this again". We are generally fine with machines, because they embody these principles in confined parameters. However, there's also a certain danger in this, as we tend to generalize and idealize along these lines, as this is essential to how we construct and navigate the world, we live in. We'll also apply this to things that are just "mostly", and are apt to be fooled by this, as may be the case with LLMs. (And in the past, machines were a great way out of this trap, as long – and as soon – as we were able to verify the parameters and boundaries.)