That is a problem for "Open"AI because they want to sell their products, and because they want to claim that LLMs will scale to superintelligence. Not for others.
"Bad" hallucinations come in different forms, and what the article describes is one of them. Not all of them come from complete uncertainty. There are also the cases where the LLM is hallucinating functions in a library, or they reverse cause and effect when summarising a complex article. Stuff like this still happen all the time, even with SOTA models. They do not happen because the model is bad with uncertainty, they have nothing to do with knowledge uncertainty. Esp stuff like producing statements that misinterpret causal relationships within text, imo, reveals exactly the limits of the architectural approach.