It's nice that you feel that having one LLM that generates entirely incorrect statements is equally as functional as an LLM that does not, but reality in terms of what LLMs people will actually use in real life and not for the sake of being pedantic over an Internet argument is very much at odds with your sentiment.

How a product happens to currently be implemented using current machine learning techniques is not the same as the set of features that such a product offers and it's absolutely the case that actual researches in this field, those who are not quibbling on the Internet, do take this issue very seriously and devote a great deal of effort towards improving it because they actually care to implement possible solutions.

The feature set, what the product is intended to do based on the motivations of both those who created it and those who consume it, is a broader design/specification goal, independent of how it's technically built.