The limitations of visual processing (for example) is not literally a
contemporary logical satisfiability problem because the satisfiability
methods of the first 70 years of computing have been so weak. But a
stronger satisfiability method will allow programs to start tying the
products of strong visual methods together across the
(logical)interstices between them. These gaps between the stronger AI
methods have caused such a problem that they have failed to produce
the foundations that are necessary for AGI. The foundations are so
riddled with flaws that we can't even start to test our competing AGI
theories. It is true that programming languages are still pretty
difficult to use to build complicated programs, but when the easiest
approaches fail -just because- they run into combinatorial explosions
(or what I call combinatorial combustion) this is a clue that there
are some underlying logical satisfiability problems.
Jim Bromer


On Tue, Feb 17, 2015 at 11:52 PM, Matt Mahoney via AGI <[email protected]> wrote:
> On Tue, Feb 17, 2015 at 10:26 PM, Jim Bromer via AGI <[email protected]> wrote:
>> I started wondering about how a good Satisfiability model might be
>> used with AGI.
>
> It wouldn't because the hard problems in AI like vision and language
> are not NP-hard. The more useful application would be breaking nearly
> all forms of cryptography. (One time pad would still be secure).
>
>
> --
> -- Matt Mahoney, [email protected]
>
>
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