I don't mean it in a philosophical sense, more in a rigorous scientific one.

Yes, we do have reliable datasets as in your example, but those are for specific topics and are not based on natural language. What I would call "classical" machine learning is already a useful technology where it's applied.

Jumping from separate datasets focused on specific topics to a single dataset describing "everything" at once is not something we are even close to doing, if it's even possible. Hence the claim of having a single AI able to answer anything is unreasonable.

The second issue is that even if we had such a hypothetical dataset, ultimately if you want a formal response from it, you need a formal question and a formal language (probably something between maths and programming?) in all the steps of the workflow.

LLMs are only statistical models about natural languages, so it's the antithesis of this very idea. To achieve that would have to be a completely different technology that has yet to even be theoretized.