The key difference is that while an encyclopedia holds facts themselves, LLMs trained on that source material encode something more like a highly probable facsimile of those facts - the original fact was lost, LLMs are lossy, but can often be generated again with a decent level of accuracy by churning through stats about words, concepts, and relationships between them.

The whole catch is that they can often be regenerated. But LLMs (on their own, in their parametric memory - which is the result of training) don't have any conception of whether what they've generated is a real reproduction of some training material or whether they've invented something false that seemed probable based on their encoded stats. When the probability produces something contrary to what was in the training material, you get hallucinations.

They're very, very good predictive text models and can be very, very powerful when hooked up to other tools or outside databases. But its fundamentally lossy technology and all the books having been fed in doesn't guarantee all of the knowledge from those books can be spat back out.

Your criticism of LLMs also applies to humans and so implies humans don’t possess knowledge.