This issues has bothered me for a long time, and I'd like to explore it a
bit:

 

While digital computers obviously can be set up to solve equations, there
still seems to be a significant difference in efficiency of simulating/
calculating versus physical analog 'doing'/ execution - like for example in
solving an n-body problem.  Real systems system just produce the result by
interaction of all the forces (electro/ mechanical), while computers have to
approximate/ iterate. 

 

Key question: Are there AGI common problems where digital/simulated
approaches need hyper-exponential amounts of computing power compared to
physical systems? Is this kind of equation-solving core to AGI?  I don't
think so, but.

 

Other may be able to formulate this better. 

 

What has bothered me is the glib assertion that a digital computer an
calculate to any arbitrary level of precision (true).  but does the cost
become unworkable in practice, even with Moore's law.

 

Peter

 

From: Steve Richfield [mailto:[email protected]] 
Sent: Thursday, June 28, 2012 6:39 AM
To: AGI
Subject: Re: [agi] Happy 100th Birthday Alan Turing - No, computers will
never think, but machines will!

 

Hey everyone,

Remember my discussions about how computers fundamentally compute functions,
while biological neurons appear to fundamentally solve equations - a MUCH
higher level thing to do. It appears possible to design something resembling
a computer to do this, but NOT to simulate this sort of functionality in any
sort of practical way because of the astronomical inefficiency of solving
huge systems of simultaneous NON-linear equations using conventional
computational methods.

No, I don't think that we need any sort of silicon wetware, but we DO appear
to need a radically more advanced sort of "computer", but probably NOT
anything that Turing has ever thought of - in short, NOT a "Turing machine".

Besides, you'll never get 2-D silicon to work like 3-D wetware.

Steve
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