Because unless you were recreating the wetware, an emulation of the brain on any other architecture is going to be sub-optimal. Why would you want to handicap your amazingly powerful computer?
History is another essential difference, often overlooked. The organization of computers is explicitly designed by people. The structure of brains is not designed but emerges from contact with the world over evolutionary time, developmental time, and in the immediate moment.
If I understand correctly, super-Turing machines has pretty much the same basis. In this perspective it would seem really surprising if they exist.
You’re right. It would be really strange, but I’m just pointing out that it’s still theoretically possible at this point. To say “We can *probably* simulate the brain in a computer, therefore the brain *is* like a computer and it’s just a question of getting a proper interface to hardware” is not a valid argument.
Emotionally, I find the idea that the brain isn’t a Turing machine only slightly less distasteful and unlikely than violating the physical domain in explaining consciousness. But the idea of Peyton Manning winning a superbowl is distasteful and unlikely, but it happened too.
I think, personal loans Maryland that the post addresses a certain, probaly ruling methaphore of brain computation. This comes from the Turing-model of computers and reflects the understandings of the second half of past century. In this sense, the post urges for metaphore change, and I fully agree with that.
If you go out to everyday informatics you’ll hardly find the low-level structures and mechanisms that are used in cognitive sciences, even common systems are much better modelized and understood (see. Universal Modeling Languge, Design Patterns, etc.).
I think, cognitive sciences would gain a lot by recycling the models, patterns, analogies that are used in designed and partly designed systems (like the Internet, and yes, Google is functionally something like the hippocampus). Anyway, in these systems, to get them work (OK, more or less), problems (like asynchronous mixed inputs, information relaying, updating and evolving strucures, interconnection of heterogenous environments, growth, continous work, bottlenecks, prioritizing activities, etc.) must have been resolved in some way. My first candidate is, of course, the Internet, NOT as an analogon to the brain, but as a warehouse of patterns enough rich to reach for better metaphores in the understanding of cognitive processes. Here, you have the unique opporunity to study the evolution of solutions, what forces and processes led to change, what goals could be achieved and what not, and why not, what competing solutions existed, what was the winner, and why (not allways the “better”, the Internet “has body”), etc.
I’m less optimistic about the usability of new hardware architectures, or dedicated brain models, they have a couple of design points in place, so can be good to demonstrate a certain aspect, not more.
A really great post Chris indeed. But an “AI-believer” is throwing the gauntlet : A challenge to the AI-deniers. I cross-linked this posting over there already.
But what falls out of that definition is not particular enough to talk in a meaningful way about organismic knowing. That human cognition can be modelled in a limited way using hardware and software does not mean that computation is the best analytic framework for understanding what cephalized organisms do and how they go about doing it.