Hi Everyone,
It’s been a while!
Something important is happening right now, thanks to the emergence of LLMs as the long-awaited generic RDF client (the so-called “killer app”). We all know how Mosaic → Mozilla/Netscape made HTML and HTTP globally usable by end-users and developers alike. Well, the very same thing is finally happening with RDF—albeit some 20+ years later than expected.
Here’s a post I recently published on LinkedIn about this critical development:
https://www.linkedin.com/pulse/large-language-models-llms-powerful-generic-rdf-clients-idehen-xwhfe
-- Regards, Kingsley Idehen Founder & CEO OpenLink Software Home Page: http://www.openlinksw.com Community Support: https://community.openlinksw.com Social Media: LinkedIn: http://www.linkedin.com/in/kidehen Twitter : https://twitter.com/kidehen
Hi Kingsley,
A good article about using RDF and user interface functionality. But I believe that any information generated by LLM should be marked "May contain errors."
So all those beautiful tables, diagrams, and documents should display this sign prominently.
For me, user interface functionality that reflects the power of RDF is more important.
Best regards,
Alex
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Hi Alex,
Hi Kingsley,
A good article about using RDF and user interface functionality. But I believe that any information generated by LLM should be marked "May contain errors."
Yes, but that’s an optional behavioral configuration. For instance, in my examples, an LLM was part of the production pipeline that produced the reference documents—that is, I have the domain expertise to verify accuracy prior to publication.
If it were a direct-from-LLM pipeline, as I’ve demonstrated in the past, a disclaimer would be attached to anything generated 100% by the LLM. This is a fundamental pattern for managing a probabilistic tool like an LLM.
So all those beautiful tables, diagrams, and documents should display this sign prominently.
See comment above.
For me, user interface functionality that reflects the power of RDF is more important.
Extremely. The point of my article is that LLMs are
powerful, generic RDF clients that free both developers and
end-users from the prior distractions of RDF esoterica (e.g.,
HttpRange-14, preferred syntaxes, notations, and formats, 303 vs
hash re entity denotation etc..).
Kingsley
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Hi Kingsley,
A good article about using RDF and user interface functionality. But I believe that any information generated by LLM should be marked "May contain errors."
So all those beautiful tables, diagrams, and documents should display this sign prominently.
For me, user interface functionality that reflects the power of RDF is more important.
Best regards,
Alex
John,
I agree. Formalization is absolutely crucial, as we're moving toward mathematical methods of knowledge processing, where the differences aren't very large and mostly lie outside the realm of finite models and algorithms.
But constructing the most accurate formalization is a rather delicate matter. And here, the formal language used, while important, is only an auxiliary tool. The knowledge being formalized itself must be a well-structured theory. And that's quite challenging.
Therefore, it's proposed to store theoretical knowledge, along with its various formalizations, in frameworks specifically designed for knowledge concentration [1]. Such theoretical repositories with an emphasis on formalization exist spontaneously in Isabelle, Coq, and other provers.
Despite the enormous accumulation of theoretical knowledge in science and technology, I believe its volume, in a systematic and refined form, would be several terabytes.
The key is to create concentrators of such verified and formalized theoretical knowledge.
Alex
[1] (PDF) Theory framework - knowledge hub message #1 рус
"Storing the theory of a particular subject area in one place and maintaining it (including formalization) through collective efforts is easily possible with the modern development of technology. The concentration and verification of knowledge achieved in this case should give a powerful ordering of theoretical knowledge, which will facilitate their formalization, i.e. mathematical notation, and therefore algorithmic processing in many cases, up to the semi-automatic proof of various kinds of consequences, for example, theorems. This message describes what the framework of the theory is, intended for unified storage and collective accumulation of its results."
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Hi Milton,
What do you think about representation of our theoretical knowledge as axiomatic theories?
Alex
As a mathematician I cannot suppress a chuckle here. The problem here is the implicit discussion about knowledge, knowledge representation and formal knowledge representationThese are three distinct layers and because we still not have a firm grip on the first, which is inextricably linked to consciousness, knowledge representation remains a difficult task to accomplish, and consequently formal knowledge representation, which we are seeking will remain elusive.Large language models ignore the first layer and assume we can use token based systems to create knowledge representation emulation systems that can capture all formal knowledge representation systems.If one looks at the groundbreaking paper MIP*=RE, https://arxiv.org/abs/2001.04383, and what it states about the Connes embedding conjecture being false, this should ring a bell.Because we cannot in all cases assume that a finite matrix in a very high dimensional space can approximate a simulation of an infinite dimensional space.Which means that no matter how high we make the dimension and consequently the number of parameters used, in some cases the simulations will never even get close to approximate a finite accurate model of infinite space.Which means generative LLMs are are a mathematical dead end, and will be the reason why the AI bubble riding on generative LLMs will burst.Milton PonsonRainbow Warriors Core FoundationCIAMSD Institute-ICT4D ProgramPO Box 1154, OranjestadAruba, Dutch Caribbean
John,
I can try to figure out what Milton means if he answers questions (It's always interesting to be Socrates). You've chosen the one closest to yours from "a continuous infinity of possible starting points."
I write here from time to time that the most commonly used knowledge, presented as theories in various textbooks, articles, and lectures, is selected for formalization. You can say: don't formalize the Geometry of Hilbert, Euclid, or Tarski. And so on for physical theories, and then say the same to every computer scientist and ontologist formalizing in RDF, OWL2, CL(🤝), Isabelle, Coq, or Lean.
A strange proposition for our community of practice.
Formalization is not the creation of new knowledge. It is the formalization of existing, human-verified knowledge for reliable processing by computers.
It should be added that we formalize (some would say, crudely, "cram" them into a computer) not only theories, but also their models and methods for solving problems about the properties of these models [1]. We spend our entire lives constructing theories and their models, and testing them in practice by solving various problems: Close your eyes and solve the problem of taking a sip from your cup of tea.
Alex
"This document describes a specific framework of specific tasks about a particular structure posed and solved GNaA Fig.1.1 within the framework of a specific theory, namely Ugraphia, the theory of undirected graphs, with little involvement of the theory of binary relations, Binria. The task framework stores the formulation and solution of tasks in a structured form and is intended for use by everyone in the world (be it the world of a research group or Humanity): having set a task on the structure before solving it on their own, a person can look into the task framework and see: perhaps it has already been solved. The structure and tasks about it are described in the first paragraph of the first chapter of [GSiA]."
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John,
Euclid's exposition [1] is completely informal, but the idea of axioms, definitions, theorems, and proofs is used extensively.
Hilbert wrote out all the primary terms and axioms. This is a major step forward, but his exposition is informal [2]. In doing so, he laid the foundation for the formal notation of theorems and their proofs.
An example of a formal text for geometry can be found here [3]. The beginning of the definitions section is given.
To make such formal texts publicly accessible and collaboratively developed, a theoretical knowledge framework is proposed: (PDF) Theory framework - knowledge hub message #1.
Alex
[1] http://aleph0.clarku.edu/~djoyce/elements/elements.html
[2] https://en.wikipedia.org/wiki/Hilbert%27s_axioms
[3] https://github.com/ivashkev/math-formalizations/blob/master/07_EuclideanGeometry.v
Class Definitions `(dc : Declarations) :=
{
Convergent (x y : Line) : Prop
:= (x <> y) /\ (exists A : Point, [ A @ x, y ]);
Parallel (x y : Line) : Prop
:= (~ Convergent x y);
SameRay (O : Point)(A B : Point) : Prop
:= O <> A /\ O <> B /\ [ A, O, B ] /\ ~ [ A # O # B ];
OppositeSide (x : Line)(A B : Point) : Prop
:= ~ [ A @ x ] /\ ~ [ B @ x ] /\ (exists O, [ O @ x ] /\ [ A # O # B ]);
SameSide (x : Line)(A B : Point) : Prop
:= ~ [ A @ x ] /\ ~ [ B @ x ] /\ ~ (exists O, [ O @ x ] /\ [ A # O # B ]);
SameHalfplane (O A B C : Point) : Prop
:= O <> A /\ exists x : Line, [ O @ x ] /\ [ A @ x ] /\ SameSide x B C;
OppositeHalfplane (O A B C : Point) : Prop
:= O <> A /\ exists x : Line, [ O @ x ] /\ [ A @ x ] /\ OppositeSide x B C;
Segment
:= @Duo Point;
BuildSegment
:= @BuildDuo Point;
Triangle
:= @Triple Point (fun A B C => ~ [ A, B, C ]);
BuildTriangle
:= @BuildTriple Point (fun A B C => ~ [ A, B, C ]);
Ray
:= @Duple Point (fun A B => A <> B);
BuildRay
:= @BuildDuple Point (fun A B => A <> B);
EqRays (a b : Ray) : Prop
:= (da a = da b) /\ SameRay (da a)(db a)(db b);
OpRays (a b : Ray) : Prop
:= (da a = da b) /\ [ db a # da a # db b ];
Sector
:= @Duple Ray (fun a b => da a = da b);
BuildSector
:= @BuildDuple Ray (fun a b => da a = da b);
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