[foothebar]

Yes, like said. Also I did not see your first draft of writing before. First which comes to my mind when seeing it: It seems you are not referencing any existing work of scientists, which will be a large caveat for many, because that is like science works – enhance what others have done, prove your starting or side points of your arguments by citing what others found, do not do everything from scratch. Don't write about what you think something is like (e.g. NN), but prove it is like that by citing the right sources, which you have read.

[peterweyand]

Yeah understandable. The paper is ambitious in that it starts from first principles in some areas by necessity, but I would have to have someone check for consistency and references to Husserl, Heideger, Lacan, Plato, Korzybski, Zizek, modality theory, vagueness, and more and that's just for philosophy. The neural networks is an issue in that I don't know if my references to A^ are addressed within neural networks currently, but I provide some evidence that they don't appear to be.

Mostly I just want someone to read my paper because the ideas are rather startling to me, but I don't know if this has been done before. If it's original work I think there are important reasons to have it published so everyone can read it at once, which is explained in the paper. But I may be completely off base.

To the extent that the lack of citation invalidates the conclusions of the paper? I don't know. I think that Korzybski's attitude towards maps, and several other areas where academics have been building on incorrect ideas (such as the theory of interest or that this would necessitate a Marxian dialectic in opposition), mean that original research need be done without necessarily building off of recent research.

Again, super ambitious paper. I could be entirely wrong.

[foothebar]

Just a further note: "AI" is a completely misleading name. No one (sane) in the "AI" business thinks of it as being intelligent. It's just automated statistics (it IS probabilistic) which can find patterns in data. So an An A' pattern won't fit. Also it usually has much less than a single hundred layers.

[peterweyand]

With current machine learning (neural networks as I understand them) I believe that there is no "intelligence". But I think it's possible to create an A^ pattern and my paper provides bounding around this area to make it possible. Whether it is computationally efficient to train an AI from a bottom up approach (np-incompleteness) or if it would return results that would be communicable between the AI and a human if it did I do not know. I need to make A^ more formal and find a specific example, but I think it may be possible to create a model using an image classifier (not a neural network as is currently done with say hand writing OCR).