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First, there’s the matter of what architecture of neural net one should use for a particular task. One might have thought that for every particular kind of task one would need a different architecture of neural net. OK, so let’s say one’s settled on a certain neural net architecture.
But it also highlights how significant our specifics—our particular history, biology, etc.—are. Some of it seems intrinsic to our biological nature. For now, there’s a certain element of what we want to do that’s “anchored” by our biological nature. And in biology it shows up as some structure (ribosome, cell, wing, etc.)
The global structures of metamathematics , economics , linguistics and evolutionary biology seem likely to provide examples—and in each case we can expect that at the core is the ruliad, with its unique structure. And this is where our pieces of “falsifiable naturalscience” come in.
In early 1984 I visited MIT to use the machine to try to do what amounted to naturalscience, systematically studying 2D cellular automata. People had discussed reaction-diffusion patterns as examples of structure being formed “away from equilibrium”. What kinds of models could realistically be made for these?
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