Convergence to representational commensurability must occur when using abstract

Convergence to representational commensurability must occur when using abstract representation (N-dimensional networks) – humans are marginally indifferent in sense perception – and language must be accessible across the sex (responsibility), class (genetic load) and intelligence (neotenic development) spectra.
Many ‘discoveries’ in AI are only discoveries of consistency and correspondence with the operational model of the brain discovered by neuroscience.
Many problems with neuroscience emerge from failing to produce an operational (what) model of the brain instead of a neurochemical (why). Turns out the nerve, neuron, neural microcolum, neural column, region, hemisphere, network organization of the brain is pretty simple in the aggregate even if complex out of sheer numbers – just like parameters in our AI neural networks.