Following up an interesting exchange, I'd like to ask you:
- how would you define a "machine" broadly speaking?
- is your definition covering a broad spectrum, such as molecular machines, man made machines, computers, etc?
- are you sure that your definition does not lead to defining as "machine" a forest fire or an hurricane?
- which argument would you use to characterize the differences between a molecular machine like kinesin and a mechanical machine like an old watch? Does it work too for a whole cell or the human brain? (at a high level of abstraction, of course)
I have some ideas to share based on universal Turing machines and complexity science, but would like to get more inputs, first.
As usual, I try to bootstrap the discussion by involving a diverse pool of friends and good thinkers: @PessoaBrain @tiago @lmrocha @thilo @kordinglab @NicoleCRust @hirokisayama @WiringtheBrain
@manlius @PessoaBrain @tiago @thilo @kordinglab @NicoleCRust @hirokisayama @WiringtheBrain
Formally, I think of machine as a (cybernetic) mechanism. That is, when before is state-determined, with (relatively small) finite time memory dependency---in other words, behavior depends on a few time steps. Forest fires, hurricanes and the like can be modeled by mechanisms.
In this view, a Turing machine is not a machine, as it has infinite memory and its (complex) behavior depends on an arbitrary code between memory and instructions, with conditional branching and unpredictable changes/mutations to tape. To see this difference it is useful for me to compare Babbage's difference engine (a machine) with Babbage/Lovelace 's analytical engine (a general-purpose computer). As Babbage said, the "snake eating its own tail" is a completely different device :)
