>Besides, in weights there are no real incompatibility can happen, all is unified with same math chain through architecture. Different set of local minimums/maximums can have different strong/weak consequences but nothing incompatible.

How do you know you're not stuck in a local minimum, always re-generating the God (or worse, the Demon) configuration and thinking it's universal?

This argument that incompatibility is impossible has an easy counterexample by looking at loss of coherence between two networks. You can still mash the weights together (so they're not "incompatible" in the basic number crunching, sure), but the resulting neural net is meaningless.

By "incompatible" I meant not in a software sense, but like two logical axiom systems can be incompatible.

This quietly assumes that "representations" of reality only encode neutral objective facts (that can be objectively judged, good luck finding a judge everyone agrees on), and "representations" does not encode intentions and value judgements, ie internalized training logic.

But that leaks in, and of course it does! If training only rewards "objective truth" we might expect that sort of neat ontological cleanliness, but we all know real training goals are more complicated.

There doesn't appear to be a bright clear distinction between objective facts and subjective values/intentions in neural networks. The distinction is perhaps illusory, just another of our preconceived notion about the nature of thought...

Fascinating to contemplate, thanks

There’s an idea of the “broad and narrow gates” that comes to mind, accompanied by a genre of fascinating illustrations. [1]

A modern version [2] appears in the paper "Asymptotic burnout and homeostatic awakening: a possible solution to the Fermi paradox?" [3]

[1] https://en.wikipedia.org/wiki/Matthew_7:13#/media/File:Der_b...

[2] https://pmc.ncbi.nlm.nih.gov/articles/PMC9065981/figure/RSIF...

[3] https://pmc.ncbi.nlm.nih.gov/articles/PMC9065981/