A philosophical concept that runs counter to hierarchical, layered modeling (Are There Levels Out There?) is the rhizome . Rhizomes appear in web/network programming theory [2,3,4]. (Still no “Rhizome” programming language?)
Introducing Tony and Cody dialogues
Tony – a Platonist/Positivist
Cody – a Pragmatist/Codicalist
cf. Consequences of Pragmatism (Introduction: Platonists, Positivists, and Pragmatists)
TONY: An important aspect of Bruno Marchal’s theory is that he proposes to solve “the hard problem” of consciousness by identifying the unprovable truths of arithmetic with the ineffable qualia of consciousness.
CODY: If Marchal thinks that that is a property of consciousness, and if consciousness is a property of brains, and if brains are made of biomaterials, then he must think that there could be a biocomputer (a computer made of biomaterials) that can support super-Turing computing.
TONY: Why? He’s not saying that any particular brain can experience/comprehend all the unprovable truths. Only that each brain can realize some of the unprovable truths.
CODY: Then make a really gigantic network of (brain-level) biocomputers and connect them via the (next generation) internet. Call it WWB — World Wide Brain. WWB is now your super-Turing computer!
TONY: It’s still finite and there are still infinitely many true theorems it cannot prove. Marchal doesn’t think consciousness is a property of brains; he thinks it’s property of some computations or algorithms. And he doesn’t suppose it has to do anything super-Turing. He thinks that jumping spiders, and possibly even simpler animals, are conscious.*
CODY: As for consciousness, there are some (natural computationalists) who think that particular property requires biocomputing — the object code consists of biomatter rather than a binary running on standard silicon.
Turing’s Ideas and Models of Computation
Eugene Eberbach, Dina Goldin2, Peter Wegner
The theory of computation that we have inherited from the 1960’s focuses on algorithmic computation as embodied in the Turing Machine to the exclusion of other types of computation that Turing had considered. In this chapter we present new models of computation, inspired by Turing’s ideas, that are more appropriate for today’s interactive, networked, and embedded computing systems. These models represent super-Turing computation, going beyond Turing Machines and algorithms. We identify three principles underlying super-Turing computation — interaction with the world, infnity of resources, evolution of system — and apply these principles in our discussion of the implications of super-Turing computation for the future of computer science.
TONY: I am waiting for someone to say that genes have created gene splicing technology and computers in order to copy themselves onto hard drives and from there copy themselves onto new organisms.
CODY: Genes have created biological forms that can make gene splicing technology and computers in order to copy themselves onto hard drives and from there copy themselves onto new organisms.