Text and languages contain structured information and encode a lot of real-world complexity (or it's "modelling" that).
Not saying we won't pivot to visual data or world simulations, but he was clearly not the type of person to compete with other LLM research labs, nor did he propose any alternative that could be used to create something interesting for end-users.
But that sure didn't happen.
The issue is context. trying to make an AI assistant with just text only inputs is doeable but limiting. You need to know the _context_ of all the data, and without visual input most of it is useful.
For example "Where is the other half of this" is almost impossible to solve unless you have an idea of what "this" is.
but to do that you need to have cameras, to use cameras you need to have position, object, and people tracking. And that is a hard problem thats not solved.
the hypothesis is that "world models" solve that with an implicit understanding of the worl and the objects in context