[apinstein]

I think it would be significantly less accurate. Their error rates for performing physical tasks would be different b/w they lack the sensors to accurately train decent world models. For instance, I don't think they could catch a ball at the same skill level as a sighted child no matter how hard they tried.

So the lack of that sensor will cause the brain to develop poor representations of motion in 3d space.

How lack of those representations would affect other representations is less clear; because seeing the fusion between the LLM (which similarly doesn't have an embodied world model representation) and the robot AI (which presumable does) obviously works really well.

Now, it's possible that the 2 models are just inter-communicating between their own features (apple the concept and apple the image/object) and then being able to connect that together. The point of this meaning that there could be benefits from separate training and then post-training connection to bridge any gaps in learned representations.

However, I'd think that ultimately a model that can train simultaneously on more sensory input vs less will have a better/more efficient world model with more useful & interesting cross-connections between that space and applied uses in non-physical domains.

[beambot]

Blind people are still wildly capable people. If your goal is to build a "wildly capable digital brain akin to a person", then the lower bound is much less than 10^15 proposed by LeCun's reasoning.

[uoaei]

Clearly you have never known a blind person.