The conceptual Implicit (IT) model of all that is
Suppose that in the beginning, there was a blob of awareness and nothing else, and so there is nothing for the blob to be aware of except itself ie in an infinite stochastic neural network that represents connections between nodes. Lets call this blob “IT”.
Suppose this state of existence was unsatisfying to the “IT, and so it struggled to create something of which it could be aware which could be random noise.
Suppose initially, the best it could do was to produce clones so then at least, it and its clones could be aware of each other. These clones are patterns within a stochastic neural network which could be referred to as being indeterminable (messy) chaos.
Then, once this process started, there would be no particular point at which it should stop, so we could assume it would continue until there were an unlimited number of “IT’s” each aware of all the other “ITs”
The neural network is also constructed to have feed back.
Different types of feed back are possible. Because we assume the neural network (“IT”) is aware, then we can suppose the network will tend to provide positive feed back to features that it finds interesting and provide negative feed back if they are not. In such instances some of these negative features die.
However, if each succeeding “IT” only had a finite awareness, the degree to which it could be aware of other individually cloned “IT’s”, would be reduced in proportion to the total number of other “IT’s”. So if an “IT” allowed itself to be equally aware of each other “IT’s”, its awareness of each other “IT” would be very weak.
As the random noise will randomly add new features to existing “IT” features of interest, this will create new variations , which will also receive positive feed back if they are interesting and negative feed back if they are not.
However, we can suppose that with awareness involving free will, each “IT” could choose to be especially aware of some other “IT’s”, while only very weakly aware of the huge number of others.
Random noise will randomly add new features to existing features to other “IT’s”.
These added random features can be considered as being “IF’s”
So the noisy stochastic neural network will create increasingly complex new patterns of interest to itself (“IT’S”) with without limit “IFs” that we might also say are random features of possibilities to do something.
It is analogous to an infinitely creative brain, which starting off from nothing but random patterns, gradually fashions meaningful images for itself by means of thoughts and patterns of thoughts that mean something unto itself. These images might include thoughts.
However, because human’s don’t have the ability to build infinite stochastic neural networks computer scientists have found that a finite sized network (with a suitable computer feed back mechanism) was able to produce patterns analogous to quantum matter embedded in an expanding and ‘entangled’ 3 dimensional space.
This leads to the hypothesis that reality as we know it (space, matter, life and thoughts) consist of such patterns within a similar but infinite network.
This secondary reality might then be also comparable to what I describe as “IS”.
It is analogous to photo-realistic images within an infinitely created brain of “IF’S (possibilities to do something).
How could one get that into this “IT” “IS” and “IF model”?
Suppose that as a result of being clones, all the nodes of “IT’s” can to some degree share each others awareness. Then it would be possible for them to coordinate the strengths with which they choose to use their awareness to link to other nodes of “IT’s”. These strengthening clones might also be considered to be as patterns of thoughts.
Let us suppose that these patterns of thoughts collectively try various schemes but do not obtain satisfying results until they try a scheme analogous to the finite sized computer that was able to produce patterns analogous to quantum matter embedded in an expanding 3 dimensional space.
The “IT’s” would then find that this scheme allows them to generate patterns of awareness that correspond to quantum matter embedded in an expanding 3 dimensional space.
Then we could suppose that the “IT’s” collectively find this sufficiently interesting that they stick with this scheme.
Then in this “IT” model, space and matter consist of patterns of awareness that are determined by the degree to which “IT’s” are aware of other “IT’s”.
So the Implicit physics model (embracing all processeses entangled within whole of reality [Implicit reality] as well as personal secondary awareness) might be the suitable model to embrace all “ITs”, “IFs” and “IS es” relating to wider reality (what ever reality might be).
It is only a physical model but suppose that the infinite ”IT” neural network is aware then that allows speculation about the nature of “IT” (awareness) and whether we could include human awareness in the awareness of the “IT” network itself. Human awareness might also be considered as being”IS”. This is simply because this is the way things (nature) are.
This also means that my Implicit (“IT”) thought model has similar form to the Bohm Holomovement Physics model because patterns of awareness (“IT”s) can also be seen as equivalent to patterns of information as Bohm described.
I considered these types of ideas when I wrote this abstract conceptual science (physics) story for students.
If you have a science interest you may find these two items of interest as well.