Natural language can represent an abstraction of very diverse stuff and phenomena in the world. It can represent events (with time dimension) and interactions b

Natural language can represent an abstraction of very diverse stuff and phenomena in the world. It can represent events (with time dimension) and interactions between entities and events, abstract and physical, and meta-interactions as well, at multiple layers of abstractions. 2D still images, at least the sort that humans are familiar with, are more limited in terms of representation power and thus more amenable to compression into network weights. Perhaps models representing 4D phenomena (3D entities with time dimension, e.g. videos of real 3D models) would be more comparable in size to natural language models. Since LLMs can also represent abstract and unreal entities, while 4D representation can represent more details, it's hard to say which kind of models is richer.