Re: the intersection between AIKR and COGAI

Dear Dave,
Let me start with drawing the background for my observations.
https://www.zdnet.com/article/ai-true-goal-may-no-longer-be-intelligence/
In this article a concern of many scholars and excerpts is voiced. Investors and and the AI industry are more concerned about technological marvels like GPT-3, DeepMind and AlphaFold than the theoretical computer science and mathematics behind AI development.
When it comes to future trends and policy directions the European Union, the White House and the US DoD all have produced documents announcing strategic issues and opportunities for development in AI
Even Yann LeCun has weighed in on the issue and proposed a new research paradigm.
And in the field of robotics ethics and the resolve not to produce harmful products is making inroads:

https://www.bostondynamics.com/resources/blog/ethical-approach-mobile-robots-our-communities
When we try to emphasize on the science and not so much the technologies we are forced to take stock of what is the current state of scientific endeavors.
I am well aware that RDF, predicate calculus and higher dimensional vector spaces provide forms of knowledge representation, but there are many more forms possible, and the problems is that so many different fields of research are converging on knowledge representation each with their own paradigms, theoretical models, that we have yet to arrive at a common ground and a way to find a way to be able to interchange these, and standardize these.
It is at the modeling and design, not the engineering nuts and bolts level that we need to focus our attention for knowledge representation.
In spite of all the marvelous neuroscience results and biologically inspired cognitive architecture research programs, AI in order to be open.inclusive, ethical, explainable and trustworthy as the European Union proposes, will have to rely on knowledge representation that combines, natural language, artificial languages of mathematics and logic, semiotics, information theory, representation theory and formal theories of observation, perception, reasoning and decision making.
In all of this the hardest parts are perception (percepts) and sensory inputs through sensors, as these correctly noted aren't language based.
Whether we like it or not, explainable AI requires formal knowledge representation that goes beyond the current linguistic and formal concepts used.
I did propose a interdisciplinary research program, much like what the Langlands program is in mathematics.

Milton Ponson
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Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development 

    On Monday, October 31, 2022 at 05:23:17 AM AST, Dave Raggett <dsr@w3.org> wrote:  
 
 I don’t understand what you are trying to say.  Knowledge can be expressed symbolically as with RDF and Predicate Calculus, or in a distributed way when using vectors in noisy high dimensional spaces, as is the case with neural networks, both artificial and biological. Stable Diffusion knows the human faces have two eyes, two ears and one nose, as well as the variations in their shapes.  It isn’t using symbols, though, despite knowing the differences between humans, dogs and cats. Whilst it recognises the word “dog”, it does so by mapping it to a vector space for a latent representation of meaning, avoiding symbols.  Reasoning can likewise be implemented in vector spaces without resorting to symbols. Human languages uses words, which can be thought of as symbols, but the closer you look at them, the fuzzier they are, as the meaning is context dependent and hard to pin down.

On 30 Oct 2022, at 20:41, ProjectParadigm-ICT-Program <metadataportals@yahoo.com> wrote:
I beg to differ on KR is by definition symbolic. Is is slightly more complicated. Its is a question of signs, symbols, concepts and how to encode (assigned) meaning. And consequently the concept of languages is also slightly more complicated.
Chomsky, Saussure and Peirce basically define our current scope on linguistics, and semiotics therein, but we use artificial languages with symbols in mathematics, logic, physical sciences, computational linguistics, computer science and NLP.
The discussion here is more of a philosophical nature, but is essential. Because we intend AI to be open, inclusive and explainable, the KR must reflect this as well.I don’t 

Dave Raggett <dsr@w3.org>