As soon as you add these physical constraints on what counts as a 'computer' you're no longer talking about computers as specified by turing, nor computer science -- which is better called Discrete Mathematics.
You're conflating the lay sense of the term meaning 'that device that i use' with the technical sense. You cannot attribute properties of one to the other. This is the heart of this AI pseudoscience business.
All circles are topologically equivalent to all squares. That does not mean a square table is 'equivalent' to a circular table in any relevant sense.
If you want to start listing physical constraints: the physical state can be causally set deterministically, the physical state evolves causally, the input and output states are measurable, and so on -- then you end up with a 'physical computer'.
Fine, in doing so you can exclude the air. But you cannot exclude systems incapable of transfering power to devices (ie., useless systems).
So now you add that: a device which, through its operation, powers other devices. You keep doing that and you end up with 'electrical computers' or a very close set of physical objects with physical propeties.
By the time you've enumerated all these physical properties, none of your formal magical 'substrates dont matter' things apply. Indeed, you've just shown how radically the properties of the substrate do apply -- so many properties end up being required.
Now, as far as brains go -- the properties of 'physical computers' do not apply to them: their input/output states may be unmeasurable (eg., if QM is involved); they are not programmable (ie., there is no deterministic way to set their output state); they do not evolve in a causally deterministic way (sensitive to biochemical variation, randomness, etc.).
Either you speak in terms of formalism, in which case you're speaking in applicable non-explanaotry toys of discrete mathematicans'; or you start trying to explain actual physical computers and end up excluding the brain.
All this is to avoid the overwhelmingly obvious point: the study of biological organisms is biology.
You're conflating the lay sense of the term meaning 'that device that i use' with the technical sense. You cannot attribute properties of one to the other. This is the heart of this AI pseudoscience business.
All circles are topologically equivalent to all squares. That does not mean a square table is 'equivalent' to a circular table in any relevant sense.
If you want to start listing physical constraints: the physical state can be causally set deterministically, the physical state evolves causally, the input and output states are measurable, and so on -- then you end up with a 'physical computer'.
Fine, in doing so you can exclude the air. But you cannot exclude systems incapable of transfering power to devices (ie., useless systems).
So now you add that: a device which, through its operation, powers other devices. You keep doing that and you end up with 'electrical computers' or a very close set of physical objects with physical propeties.
By the time you've enumerated all these physical properties, none of your formal magical 'substrates dont matter' things apply. Indeed, you've just shown how radically the properties of the substrate do apply -- so many properties end up being required.
Now, as far as brains go -- the properties of 'physical computers' do not apply to them: their input/output states may be unmeasurable (eg., if QM is involved); they are not programmable (ie., there is no deterministic way to set their output state); they do not evolve in a causally deterministic way (sensitive to biochemical variation, randomness, etc.).
Either you speak in terms of formalism, in which case you're speaking in applicable non-explanaotry toys of discrete mathematicans'; or you start trying to explain actual physical computers and end up excluding the brain.
All this is to avoid the overwhelmingly obvious point: the study of biological organisms is biology.