[Fis] Paradigm AI - I guess we call it Genius

Eric Werner eric.werner at oarf.org
Wed Oct 18 14:07:13 CEST 2023


Dear Karl,

Thank you for bringing this important point to my attention. Here are 
some thoughts:


  I guess we call it Genius

  * Difference between generating and understanding or reading
  * Super intelligence, requires genius or generational understanding
  * Generative intelligence
  * Creative intelligence
  * Compositional intelligence
  * Formative intelligence
  * Evolutional intelligence
  * Restricting, intelligence to problem-solving, dismisses, creative
    acts of composition in science and the arts
  * Think of Heinz Kohut’s formation of the self in psychology versus
    Freudian reactive psychology
  * It’s the difference between discovering a theorem, and proving the
    theorem
  * It’s the difference between school-boy problem-solving, and Newton
  * Some psychologists think of intelligence in relationship to testing
    people for their ability to cope in educational institutions. They
    want to see if they are college material or not.
  * With future All systems were talking about Newton level intelligence
    not college level intelligence
  * Kantian synthetic intelligence
  * We better be ready for that! If not,  we got some real problems.
  * That is why making these systems social and cooperative is so essential.

We may quickly reach a point where the compositional creative 
intelligence of artificial models is so powerful, we will not be able to 
understand them. Not just how they work. We already don't understand how 
they work now. But their reasoning and new outputs such, as for example, 
mathematical insights. Imagine a system that can reason and develop 
2,000 years of mathematics in a few minutes. It is precisely this 
overarching linking of knowledge that makes for real intelligence such 
as that of Leibniz or Newton.  The old  school model of psychological 
testing of intelligence uses a definition of intelligence that is to 
limiting for AI models. AI models are not your evey day student.

Best wishes,

Eric

On 10/18/23 12:59 PM, Karl Javorszky wrote:
>
> Dear Eric,
>
> Your statement: „The essence of general intelligence is the ability to 
> not only solve an externally given problem but to be creative and find 
> and define problems.” is at deviance to accepted delineations of 
> concepts in the trade of psychology. Rohracher [1] has defined in 1969 
> (and to my knowledge, no one has disputed this wording): “Intelligence 
> is the degree of efficiency [of the CNS] while solving new problems.”
>
> What you refer to is subsumed variously under: creativity, alertness, 
> curiosity, vitality, spontaneity.
>
> There is consensus in the epistemology of psychology that there can 
> exist no final, conclusive, all-encompassing theory of personality (in 
> which intelligence and adaptability/curiosity would or would not be 
> separated as concepts), because if such an ultimate, final, true 
> theory of personality would exist, that assumption would negate the 
> axiomatic rule that one can always learn something new, at least about 
> himself. There is, by definition, no end to introspection and 
> philosophy. One can always come up with a new theory of personality 
> and one cannot rule out that a new theory of personality would be more 
> reasonable, truer, more conclusive than anything that has existed before.
>
> Psychologists see theories about mind and soul in the same way 
> believers see their God. It is impossible to recognize all features of 
> God, let alone to insist that one has a correct reading.
>
> So, if you decide not to distinguish between efficiency of solving new 
> problems and ability and tendency towards finding new problems to 
> solve, you are free to do so. Established use of words splits the two 
> personality traits.
>
> I have prepared a statement about the key word “otherwise”. The word 
> is needed to scale the efficiency of mental processes while solving 
> new problems (aka ‘intelligence’) by scaling the diversity/similarity 
> properties of alternatives. To be able to efficiently choose between 
> alternatives, one needs to have alternatives that are different among 
> each other. The task is to find such collections of symbols that are 
> alternatives to each other, not by machinations by humans, but as 
> members of a symbols collection. This task is not easy to solve while 
> using the symbols set in the traditional, Sumerian ways only. One 
> needs to assume that symbols have their own properties, by their 
> nature, immanent to them.
>
> Due to the two-messages-per-week rule, the contribution shall come 
> next week.
>
> Karl
>
> [1] Rohracher, H.: Einführung in die Psychologie, Urban & 
> Schwarzenberg, Wien 1951
>
>
> Am Mi., 18. Okt. 2023 um 12:01 Uhr schrieb Eric Werner 
> <eric.werner at oarf.org>:
>
>     Dear Yixin,
>
>     Thank you for you comments!
>
>     To your point (2): The essence of general intelligence is the
>     ability to not only solve an externally given problem, but to be
>     creative and find and define problems. For example, given a
>     knowledge of mathematics and physics and data to generate new
>     mathematics and new insights into the nature of the world.
>
>     To your point (3): Biotechnology and AI are somewhat independent
>     fields. AI can help genome research and decoding genomes. But once
>     genomes are decoded that information can be used to construct more
>     general AI models. When I say "architecture" I meant the
>     architecture of the human brain encoded in the human genome. This
>     architectural information can be used to guide the structuring of
>     AI models be be more potent and more human like.  And, AI may well
>     help in the process of structuring its future version. That is
>     what I meant by selfreferencing.
>
>     To the more general point, formalization of social information can
>     help guide the improvement of AI models to be more social and have
>     greater abilities in a AI-robot social setting.
>
>     All the best,
>
>     Eric
>
>     On 10/18/23 9:16 AM, 钟义信 wrote:
>>     Dear Eric,
>>
>>     Thank you for the interesting talk on "Paradigm AI" from which I
>>     learned a lot.
>>
>>     As a discussant, may I propose some of my understanding. Comments
>>     are welcome.
>>
>>     (1) I appreciate your idea that saying "Physics paradigm PPD does
>>     not fit well with AI paradigm" and "Information paradigm PID is a
>>     better fit". This is the valuable common basis, between you and
>>     me, concerning the PPD, PID and AI.
>>
>>     (2) How to define the concept of intelligence? This is a very
>>     difficult problem. To my own understanding, the following short
>>     statement may serve as one of the candidates: _Intelligence is
>>     the ability to solve problem but not the ability to find and
>>     define problem, the latter of which is one of the abilities for
>>     wisdom._
>>     _
>>     _
>>     (3) The paradigm for AI can be used as the paradigm for
>>     bio-technology with certain simplification and specialization.
>>     This judgement is not based on their "structure/architecture", 
>>     but based on their "information function" - which is the basic
>>     function in both AI and biotechnology, that is to seek
>>     opportunity for "living (or solving problem)" and to avoid the
>>     "danger (or failing to problem solving)".
>>
>>     Once again, comments and criticisms are most welcome.
>>
>>
>>     Best regards,
>>
>>
>>             Prof. Yixin ZHONG
>>
>>     AI School, BUPT
>>     Beijing 100876, China
>>
>>
>>
>>     ------------------ Original ------------------
>>     *From: * "Eric Werner"<eric.werner at oarf.org>
>>     <mailto:eric.werner at oarf.org>;
>>     *Date: * Tue, Oct 17, 2023 02:32 AM
>>     *To: * "fis"<fis at listas.unizar.es> <mailto:fis at listas.unizar.es>;
>>     *Subject: * [Fis] Paradigm AI
>>
>>     Here are some brief thoughts on Paradigms and AI by I presume was
>>     written by Yixin Zhong since I cannot read  Chinese.
>>
>>
>>       Paradigm AI
>>
>>       * I agree that the physics paradigm PPD doesn’t fit well with
>>         the AI paradigm, and that the information paradigm PID is a
>>         better fit
>>       * Artificial intelligence systems, don’t necessarily learn from
>>         human beings. In unsupervised learning they learn from data
>>         and not from humans.
>>       * The problem, and becomes really how to define what
>>         intelligence is: Which of the following is it?
>>           o Rational inference
>>           o Summarizing large amounts of text and data
>>           o Making new predictions based on scientific theories and
>>             available data
>>           o Developing new theories that explain the data in the more
>>             succinct way, and making new predictions
>>           o Developing new technologies independently of human input
>>           o Planning and executing the actions and intentions of a robot
>>           o Having social intelligence
>>           o Being cooperative with a human being in achieving a task
>>           o Interrelating two discipline, such as physics and
>>             mathematics, to make new discoveries
>>           o Understanding, genomes in the way that human beings cannot
>>           o Designing new organisms by designing their genomes
>>       * I agree with the language of a new paradigm, such as
>>         artificial intelligence will develop slowly step by step in
>>         conjunction with its use -both conceptually and experimentally .
>>       * In a new paradigm entire new language is created as a
>>         paradigm is developed
>>       * The language evolves in concert with a new ontology suggested
>>         by the paradigm
>>           o It is an ontology of objects, technologies, actions, and
>>             strategies
>>       * What will be particularly interesting, is the *linking of the
>>         paradigm of artificial intelligence with the paradigm of
>>         biotechnology*
>>           o Biotechnology and AI will truly link the human brain with
>>             the artificial brain
>>           o The genome of the natural brain will be reflected in the
>>             architecture of the artificial brain
>>           o Hence by using AI to decode the genome of the natural
>>             brain, it will be self-reflected in the design of the
>>             developing artificial brain
>>           o This will bring unprecedented social and rational
>>             functionality to the artificial brain
>>           o Note that the biotech-genome paradigm also is founded on
>>             the information paradigm.
>>
>>     Thank you Yixin Zhong for your input and emphasizing the intimate
>>     relationship of information and AI paradigms.
>>
>>     Best wishes,
>>
>>     Eric
>>
>>     -- 
>>     /Dr. Eric Werner
>>     Oxford Advanced Research Foundation
>>     https://urldefense.com/v3/__https://oarf.org__;!!D9dNQwwGXtA!VvOfZm0CWjVPM7xYKVUO5vkDvx9MusQMRPpMkuycNvECTx_JKVuphYgtiPWoWJVdjig7Zmh4qyxchxc_Dlf37Ok$ 
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>>
>>
>>
>>     /
>>
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>     -- 
>     /Dr. Eric Werner
>     Oxford Advanced Research Foundation
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-- 
/Dr. Eric Werner
Oxford Advanced Research Foundation
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