Comment by D-Machine

> There's no such thing as a "world model"

There obviously is in humans. When you visually simulate things or e.g. simulate how food will taste in your mind as you add different seasonings, you are modeling (part of) the world. This is presumably done by having associations in our brain between all the different qualia sequences and other kinds of representations in our mind. I.e. we know we do some visuospatial reasoning tasks using sequences of (imagined) images. Imagery is one aspect of our world model(s).

We know LLMs can't be doing visuospatial reasoning using imagery, because they only work with text tokens. A VLM or other multimodal might be able to do so, but an LLM can't, and so an LLM can't have a visual world model. They might in special cases be able to construct a linguistic model that lets them do some computer vision tasks, but the model will itself still only be using tokenized words.

There are all sorts of other sensory modalities and things that humans use when thinking (i.e. actual logic and reasoning, which goes beyond mere semantics and might include things like logical or other forms of consistency, e.g. consistency with a relevant mental image), and the "world model" concept is supposed, in part, to point to these things that are more than just language and tokens.

> Obviously not true because of RL environments.

Right, AI generally can have much more complex world models than LLMs. An LLM can't even handle e.g. sensor data without significant architectural and training modification (https://news.ycombinator.com/item?id=46948266), at which point, it is no longer an LLM.