The problem is none of these approaches to intelligence are related to biointelligence. These are intuited, folk psychological/scientific, in a sense pseudoscientific graftings from machine vision principles. While there is spatial computing in brains, there is no metric or need to claim there is such a thing as spatial intelligence, it's like saying intelligence intelligence. The brain is spatial, so what? And the spatial this approach uses is mechanically formulaic, without any connection to how we grow intelligence.
Biology does not see 3-D, we integrate two 2-D inputs and make a 2.5-D from them in varying degrees of resolution. Within the brain our mapping systems and sensory/emotional/memory architectures range from no D (they are affinities of exploding areas) to 2-D topology, which integrate from whole brain to the finer aspects of mapping in what we understand so far are unique combinations of allo and egocentric scales of space.
Also as thought and words (and symbols, representations, metaphors, add anything arbitrary here in our weak externals) are divergent and unrelated, the manifest idea these approaches link them as a route to an unsupportable and additonal layer of "world modelling" is inferior innovation (if can even be called innovation). These are all steps back from the integrations we see biointelligence operating with. This is synthetically deciding that intelligence can be simplified with limited general processes and then form fitting them into a binary code to mimic it. It's really poor ideation.
None of this requires models (maps are not models), and the entire idea that a model is being used as a gateway to intelligence as redundant and oxymoronic as in any "world model". In essence, this is the last range of disability to achieve intelligence from binary, which in itself is a poor form to interpolate the oscillatory dynamical nature of consciousness/intelligence. It was very premature to develop this phase of code like this.
Marshferm•1h ago
Biology does not see 3-D, we integrate two 2-D inputs and make a 2.5-D from them in varying degrees of resolution. Within the brain our mapping systems and sensory/emotional/memory architectures range from no D (they are affinities of exploding areas) to 2-D topology, which integrate from whole brain to the finer aspects of mapping in what we understand so far are unique combinations of allo and egocentric scales of space.
Also as thought and words (and symbols, representations, metaphors, add anything arbitrary here in our weak externals) are divergent and unrelated, the manifest idea these approaches link them as a route to an unsupportable and additonal layer of "world modelling" is inferior innovation (if can even be called innovation). These are all steps back from the integrations we see biointelligence operating with. This is synthetically deciding that intelligence can be simplified with limited general processes and then form fitting them into a binary code to mimic it. It's really poor ideation.
None of this requires models (maps are not models), and the entire idea that a model is being used as a gateway to intelligence as redundant and oxymoronic as in any "world model". In essence, this is the last range of disability to achieve intelligence from binary, which in itself is a poor form to interpolate the oscillatory dynamical nature of consciousness/intelligence. It was very premature to develop this phase of code like this.