What's non linear about spatial reasoning?

>We know that universal solutions can’t exist

Why not?

Spatial models must be 3D, not 1D (linear), much less 2D, which is sufficient for images and object recognition (where models are not needed). And adding time makes it 4D, at least for robot motion.

To reason spatially (and dynamically) the dependence of one object's position in space on other objects (and their motions and behaviors) adds up fast to complicate the model in ways that 95% of 2D static image analysis does not.

	▲	andoando 2 days ago \| parent [-]
		Well hold on, first Im not convinced we have solved 2D spatial intelligence. Analyzing 2D images is very different from being able to reason about 2D geometry. How do you mathematically define relations like "above", "below", "diagonal", etc in a composable way that can be learned? Second, problems in 3D can be deconstructed to 2D. For example, how do you get to the airport? You need to first solve the 2D overview of the path youd take as youd now looking at a map. Then you need to reason about your field of view, and here again I believe youre really reasoning is something like "object A is behind object B and A is to the left of B", and not solving some non linear equation I think a big issue is people are trying to solve this in the realm of traditional mathematics, and not as a simple step by step process