The A.s.a. H. project has involved work in all but perhaps a half dozen or so of the subfields* (dynamical systems, diagrammatic reasoning, ...) that make up AI research. I had not planned on this, it simply proved necessary. It looks like nearly all of the subfields really are important and work in any of them can be a contribution. This breadth of coverage of the subfields may be the main difference between "weak or narrow AI" and "strong AI."
* See my blog of 9 September 2010.
Stephon Alexander et al* argue that the universe is a learning (and therefore a thinking) machine.
But again, such extraordinary beliefs would require extraordinary evidence.
* The Autodidactic Universe, arXiv:2104.03902v1, 9 April 2021 , see also arXiv:2008.01540 The Universe as a Neural Network by Vitaly Vanchurin, 4 August 2020.
How should one first introduce special relativity to students? Here's a stab at it:
The Kansas academy of science meeting this April is to be virtual. Posters are to be made available online about a week prior to the meeting. It would be a good idea to keep that practice even when the meetings go back to being traditional face to face.
How should one first introduce quantum mechanics to students? Here's a stab at it:
Chaining of case-based reasoners* was a separate project from Asa and made use of its own software. It is possible, however, to import chained case-bases directly into the Asa H hierarchy. This is most easily done early on before Asa has done much independent learning.
* See my book "Twelve Papers" available on my website www.robert-w-jones.com under "book."
I have spent a good deal of time giving A.s.a. H. the same concepts that humans use.* Donald Hoffman's arguments** are perhaps further reasons to want A.s.a. H. to create new/original concepts. Starting from the concepts A.s.a. already has feature extraction algorithms*** can be used to decompose these. The features so identified can then be recombined in order to produce new concepts.
* See my blogs of 9 May 2020 and 12 September 2020 for example.
** See, for example, The Case Against Reality, W. W. Norton, 2019.
*** Autoassociative neural networks offering one such algorithm.
