Re: definitions, problem spaces, methods

Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
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, November 7, 2022 at 05:08:12 PM AST, ProjectParadigm-ICT-Program <metadataportals@yahoo.com> wrote:  
 
 I had the fortune over the weekend to meet a PhD student from the Donders Institute for Brain,Cognition and Behaviour at the Radboud University in Nijmegen, The Netherlands, with a BSc in mathematics and physics and a MSc in physics, who is now doing research in artificial cognitive systems (https://www.ru.nl/donders/research/theme-4-neural-computation-neurotechnology/research-groups-theme-4/artificial-cognitive-systems/)

We had an hour and a half interchange of ideas, and one of the main items discussed is how compression plays a key role in intelligence, as already visible in data compression and information compressing in machine learning.
The other key takeaway from this discussion is that our primary sensory input channel in cognition is the sense of sight, and that we should see language, symbols and semiotics and for that matter any visual input percepts as visual percepts.
Humans as intelligent beings have been able to come up with language symbols sets (letters, characters, glyphs) , formal symbols, pictograms, signs and other visuals to assign in various forms meaning or identification to objects and concepts to process visually.
https://www.sciencealert.com/most-detailed-mapping-of-our-brains-memory-bank-reveals-something-surprising

"We were surprised to find fewer connections between the hippocampus and frontal cortical areas and more connections with early visual processing areas than we expected to see," says University of Sydney psychologist Marshall Dalton.


Which would suggest that the KR for AI should focus on explainable visual input.
And which would expand on purely symbolic explainability, because visuals can be defined as objects which lend themselves for formal conceptualization in category theory, model theory, representation theory and visualization theory.