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  • Re: Every computable function can be construed as --- finite string tra

    From Richard Damon@21:1/5 to olcott on Sat Oct 26 11:35:39 2024
    On 10/26/24 9:33 AM, olcott wrote:
    On 10/26/2024 8:22 AM, olcott wrote:
    On 10/25/2024 11:07 PM, Richard Damon wrote:
    On 10/25/24 6:11 PM, olcott wrote:
    On 10/25/2024 10:45 AM, Richard Damon wrote:
    On 10/25/24 9:56 AM, olcott wrote:
    On 10/25/2024 7:27 AM, Richard Damon wrote:
    On 10/24/24 8:56 PM, olcott wrote:
    On 10/24/2024 6:23 PM, Richard Damon wrote:
    On 10/24/24 9:36 AM, olcott wrote:
    On 10/23/2024 9:48 PM, Richard Damon wrote:
    On 10/23/24 9:51 PM, olcott wrote:
    ChatGPT does completely understand this.


    But, it is just a stupid idiot that has been taught to repeat >>>>>>>>>>> what it has been told.


    It is a brilliant genius that seems to infallibly deduce all >>>>>>>>>> of the subtle nuances of each of the consequences on the basis >>>>>>>>>> of a set of premises.

    I guess you don't undetstand how "Large Language Models work, >>>>>>>>> do you.

    It has NO actual intelegence, or ability to "deduce" nuances, >>>>>>>>> it is just a massive pattern matching system.

    All you are doing is proving how little you understand about >>>>>>>>> what you are talking about,

    Remember, at the bottom of the page is a WARNING that it can >>>>>>>>> make mistakes. And feeding it LIES, like you do is one easy way >>>>>>>>> to do that.


    There is much more to this than your superficial
    understanding.  Here is a glimpse:
    https://www.technologyreview.com/2024/03/04/1089403/large-
    language- models-amazing-but-nobody-knows-why/

    The bottom line is that ChatGPT made no error in its
    evaluation of my work when this evaluation is based on
    pure reasoning. It is only when my work is measured
    against arbitrary dogma that cannot be justified with
    pure reasoning that makes me and ChatGPT seem incorrect.

    If use your same approach to these things we could say that
    ZFC stupidly fails to have a glimmering of understanding of
    Naive set theory. From your perspective ZFC is a damned liar.


    The articles says no such thing.


    *large-language-models-amazing-but-nobody-knows-why*
    They are much smarter and can figure out all kinds of
    things. Their original designers have no idea how they
    do this.

    In fact, it comments about the problem of "overfitting" where the >>>>>>> processing get the wrong answers because it over generalizes.

    This is because the modeling process has no concept of actual
    meaning, and thus of truth, only the patterns that it has seen.

    AI's don't "Reason", they patern match and compare.

    Note, that "arbitrary dogma" that you try to reject, are the
    RULES and DEFINITONS of the system that you claim to be working in. >>>>>>>

    How about we stipulate that the system that I am
    working in is termination analysis for the x86 language.
    as my system software says in its own name: x86utm.

    But it doesn;t actually know


    I said the the underlying formal mathematical system
    of DDD/HHH <is> the x86 language.

    Can't be.

    That isn't a formal logic system.


    Sure it is. A formal logic system is any system
    tat applies finite string transformation rules
    to finite strings.

    The simplest concrete example of such a system
    transforms pairs of ASCII digits into their sum.


    Every computable function can be construed as applying
    finite string transformation rules to an input finite
    string and deriving an output finite string.


    Which is a concept not in the x86 language, but in Computation Theory,
    so you just proved that you were lying with your statement that you were working in the "logic system of the x86 language semantics". (Which
    isn't a thing).

    And it isn't even correctly stated, as what are called "Functions" in Computation Theory, is the mathematical abstraction that maps one domain
    to another. That mapping can be thought of as a mapping between finite
    strings that represents the elements of those domains.

    A "Computable Function" is a Function (that mathematical concept of
    mapping) that can be computed with a finite algorithm, that is a finite
    string transformation of input finite strings to output finite strings,
    that match the full mapping of that function.

    The Computable Function is not that resulting program, and that program
    is not called a Computable Function. But, since all programs that always
    halt (called deciders by some) end up computing some mapping, we can
    talk about the computable function it generates. But it is NOT that
    function, it computes that funcition, and its existsance is what makes
    that function "computable".

    The key point is that if the Function it computes doesn't exactly match
    the Function it was claimed to compute, it is just wrong and doesn't
    match its claim.

    The domain that does call the thing that does the mapping functions is
    other parts of Computer Science, but those don't use the adjective "computable", as ALL funtions (that return values) compute something.

    And the question of if the program is correct, becomes parts of
    Requirements analysis.

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