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Talk:White paper on Quasi Artifactual Intelligence
- July 10, 2023
- Communique about White_paper_on_Quasi_Artifactual_Intelligence
CC: Stephen J. Roberts (working the project space with me --nuanced on the wiki as psiCommander, me as XenoEngineer the promptrix)
Hi Don D. M. Tadaya!
Your question [ "What is an I-RIB?" ] is answered by Prueitt here:
http://www.bcngroup.org/beadgames/TaosDiscussion/referentialBases.htm
I-RIB: In-memory Referential Information Base. A term coined by P. S. Prueitt. Foundational Paper on Referential Bases, Paul S Prueitt Ph.D, October 31, 2006
I'm pouring through Prueitt's web site, and validating my lingo against logic.
The I-RIB, or In-memory Referential Information Base is a binary-tree data-access structure that preserves access to any and all certain events comprising a categorical trend.
I'm working my edits here, at our think-tank wiki (just installed this wiki a few days ago, and it will host a comic book that extends the concepts of a coalescent school of thought: ... [ The Alienesque Psience of Mind ]
Prueitt's I-RIB, or ORB, as Ontological Reference Base, are exactly reduced a pair of the same data widget, and one table holding the Cartesian product of category pairs within the two widgets. This creates the 'proportionality map' of the categories of two measurement data channels within the same period of time. To see the visual abstraction of the time-block of measurements, one is essentially visually observing a sorting process of categories from a data stream, but sorted by using random-selections, and randomly moving pairs closer together, one can observe motion and grouping behaviors. For future discussion: I'm naïve enough to assume there will be 'something' about the patterns over time of the motions of categories that reflect category frequency as a 'training data' for ML AI.
The above discussion is within Prueitt's concepts of categorical abstraction. ( cA ) Prueitt's 'event chemistry' (eC) shows (I think properly stated as) linking between measurement columns Each category is represented as a circle, and links represent edges of a classic graph showing how any one category links (within the time-line sample block) with any other category. Those linkings can have interlinking between categories several categories, which form the visual kinship to chemical compounds; an event chemistry. This is another discussion topic once I get more smarter with this refreshing refocus on yesteryear!
Cheers! DonEM
The text appears to be an abstract for a technical paper on applying category theory in the context of machine learning and control, more specifically in relation to the development of an AI perception envelope. The language used is quite complex and requires a reasonable understanding of the subject matter to grasp the full meaning. Here are the potential issues and clarifications:
Use of technical jargon: The text uses quite a few specialized terms and jargon. Terms like "QAT," "perceptor," "perceptive envelope," "dual channels of measurement," "artifactual intelligence," and "diffraction grating" are not explained and could potentially cause confusion. If you're writing for an audience familiar with these terms, this might not be an issue. However, if the audience might not have the requisite knowledge, it would be best to clarify these terms or provide a brief explanation for each.
Ambiguous semantics: The sentence "The simultaneity is registered not at a process thread in an algorithmic moment, but as registered as simultaneous within the entire set of dual measurements" could benefit from some rewording for clarity. I'm not exactly sure what is meant by an "algorithmic moment," and the use of "simultaneous" and "simultaneity" in the same sentence creates a tautology that doesn't add clarity.
Sentence structure: Some sentences are quite long and complex, making them harder to parse. Breaking them down into simpler sentences might help with readability and comprehension.
Lack of context: If "911 Era" refers to a specific method or period in the field of category theory, that isn't clear from the text. Providing some background or additional context could be helpful.
Proper Citation: The term "[I-RIB]: In-memory Referential Information Base" is attributed to P. S. Prueitt. If this is a key term, the author may want to cite the original work where it was defined.
Diagram or Illustrations: Given the complexity of the topic and the abstract nature of the described methodology, including some diagrams or illustrations could be beneficial for visual learners and could help to clarify some of the concepts.
Overall, while the text shows a deep understanding of a complex subject matter, it could benefit from more clarity and a simplification of some of the complex sentences. It's also important to ensure that all specialized terms are clearly explained or defined.