There is no real evidence that we need to solve n-body problems to achieve
human-level AGI...

It does seem we may need lots of processors acting in parallel, though --
say, millions or tens of millions....  That's unclear.

-- Ben

On Thu, Jun 28, 2012 at 10:36 AM, Peter Voss <[email protected]> wrote:

> Thanks, Ben. Yes, that’s in line with my understanding, but it seems to
> miss my point. Let me be more specific: What about achieving AGI in the
> next 10 years – i.e. without “massively parallel femto-computers” or
> anything like that. What is the evidence that in order to have full-blown
> AGI we need (or do not need) to solve n-body-like problems on technology
> that is available nowish. ****
>
> ** **
>
> *From:* Ben Goertzel [mailto:[email protected]]
> *Sent:* Thursday, June 28, 2012 7:28 AM
> *To:* AGI
> *Subject:* Re: [agi] Computing functions versus solving equations
> (calculating versus physical execution)****
>
> ** **
>
>
> Peter,
>
> About physics and computation --
>
> The following is my understanding.  To prove these statements rigorously
> would take some work..
>
> According to the Standard Model (accounting for all known forces besides
> gravity), any physical system could be simulated by some (potentially
> massively parallel) femto-computer, without dramatic inefficiency
>
> Any physical system not relying on degenerate matter (i.e. keeping its
> nuclear particles inside atoms) can be simulated by some (potentially
> massively parallel) quantum computer without dramatic inefficiency
>
> Any physical system not depending on macroscopic quantum coherence, can be
> simulated by some (potentially  massively parallel) classical digital
> computer (say, a big Connection Machine), without dramatic inefficiency
>
> All this is based on the Standard Model without including gravity.  There
> is no consistent, acknowledged unified theory of the Standard Model and
> gravitational (General Relativity) theory.  According to string theory or
> loop quantum gravity theory, two of the leading contenders for a unified
> theory, it is my impression that any physical system could  be simulated by
> some appropriately defined massively parallel string or loop computer,
> without dramatic inefficiency.  But this is less clear to me since the math
> of these theories is rather incompletely understood.
>
> If one takes General Relativity Theory or classical mechanics, and imposes
> some minimum size (to crudely emulate quantum limits), then one finds that
> any physical system with "moving parts" above that size can be simulated by
> some (potentially massively parallel) classical digital computer, without
> dramatic inefficiency.
>
> If one takes General Relativity or classical mechanics at face value and
> allows them to deal with infinite-precision real-number variables, then one
> finds that they can lead to hypercomputational dynamical systems that can't
> be simulated on any digital computer.  Some of these hypothetical
> hypercomputational systems may be set up as n-body problems.  However,
> please note that the total corpus of existing (or possible) scientific data
> is a big set of finite bits.  So, it's a bit odd to place faith in a theory
> stating the universe depends on infinite-precision numbers, based on a
> collection of finite-set data points.
>
> Note that all of the above comments are about massively parallel digital
> computers.  Obviously simulating massively parallel systems on computers
> with a small number of processors is going to be inefficient.
>
> -- Ben G
>
> ****
>
> On Thu, Jun 28, 2012 at 10:05 AM, Peter Voss <[email protected]> wrote:***
> *
>
> 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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>
> --
> Ben Goertzel, PhD
> *http://goertzel.org*
>
> "My humanity is a constant self-overcoming" -- Friedrich 
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-- 
Ben Goertzel, PhD
http://goertzel.org

"My humanity is a constant self-overcoming" -- Friedrich Nietzsche



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