How different are world models from LLMs? I'm not in the AI space but follow it here. I always assumed they belonged to the same "family" of tech and were more similar than different.

But are they sufficiently different that stalling progress in one doesn't imply stalling progress in the other?

> How different are world models from LLMs?

Depends if you’re asking about real world models or synthetic AI world models.

One of them only exists in species with a long evolutionary history of survivorship (and death) over generations living in the world being modeled.

There’s a sense of “what it’s like to be” a thing. That’s still a big question mark in my mind, whether AI will ever have any sense of what it’s like to be human, any more than humans know what it’s like to be a bat or a dolphin.

You know what it’s like for the cool breeze to blow across your face on a nice day. You could try explaining that to a dolphin, assuming we can communicate one day, but they won’t know what it’s like from any amount of words. That seems like something in the area of neuralink or similar.

There are similarities with that one. From their website:

>It is comprised of a spatiotemporal video tokenizer, an autoregressive dynamics model, and a simple and scalable latent action model.

my point is more people can try different models and algorithms rather than having to stick to LLMs.

The world models are not really useful yet. So they are starting lower, compared to LLM. So they probably have some decent gains to make still, before it gets really hard (diminishing returns).

machine learning street talk has interview with the team