LLMs have a very clear issue of making false predictions, versus knowledge graphs that represent the information mapped within them.

We should be careful to not treat the current hot thing as a hammer.

> Anytime you have an ML system where humans are designing how the information is organized (feature engineering, linking, graph building), it will work poorly.

This is a very broad assertion that I think is not accurate.

> The algorithm needs full control over the information at the lowest level (characters, words). Only then can something that truly works be built.

But data preparation and management is fundamentally important which means there's a human shaping the information at the lowest levels. There's no single ring to rule them all. This is also just fundamentally erasing the utility of any supervised model or hybrid system which is a bit silly.