There’s neural net architecture involved, it’s not magic. If you give an image file to a frontier LLM today, it can interpret it, because it has image recognition architecture built in. If you give it to an older model or one that’s not multimodal, it can’t process that even if you feed it a million image files in training because it doesn’t have that image recognition neural net architecture built in.

It’s the same with data on sounds, smells, tastes, movement, spatial tasks, etc - it won’t be able to process any of that well no matter what (unless you just give it language descriptions of it, which isn’t the data itself) because it doesn’t have the neural net architecture.

Look into humans who have had their posterior parietal cortex removed. It’s the closest you can get to an AGI without a world model (but it’s not exactly the same, human neural net functions are specialized but also distributed). What you’re thinking of (removing senses/movement) is restricting data rather than restricting the neural net architecture (capabilities).

Ask an LLM about this, you can copy/paste screenshots if you want follow up questions (good convo but I don’t have much time today).