some dazkarieh this time. i love this song, they have a new album out.
in the previous series we saw how information can be stored and processed by physical entities without any elaborate structure. we also saw how the speed at which it is both processed and stored has increased as life became more complex. today, i will summarize again the whole series from the beginning, including our formulation for minds.
- reality R is a set of N discrete things repeated M times
- the distribution of these things is non-random (i.e., it has patterns)
- this distribution is not static, it can change thanks to free energy, leading to specific distributions that can be exceptionally complex (e.g., minds)
- the development of complexity comes simply from random fluctuations and non random possibilities for existence (e.g., anti matter particles still form, but they are annihilated by reality (see 2.), hence the evolutionary trait present in all layers of reality)
- these specific arrangements versus the general ones can be quantified using arbitrary boundaries, they are arbitrary because there are no boundaries in reality
- minds represent a specific subset of R, whose distribution is non random, which is a subjective representation of the whole reality. this means minds can be conceived depending on the boundary: draw one around a planet, an animal, a cell, an atom, and you can define its observations and its thoughts
- complex minds made of neurons represent not only observations themselves, but their structure allows for thoughts to generate hypothetical observations, i.e., by virtue of their hierarchical structure, they can generalize patterns so much that impossible distributions can exist as thoughts. this means that even fantasy is real, because it exists physically as a distribution of things (in this case for example, the electrical signals and wiring of the person with the idea).
note that it is not said whether all of the constituents of reality are observable by us, human beings, i.e., of the N things reality is made of, i make no claim on how many, and what type, are they made of. this means that if someone wants to use this model to justify spirituality, they can do so, all they have to do is say there is a “spirit particle”. and though i accept it, as i said before, the quest is for the simplest generative space with minimum distortion versus reality, and the more symbols are added that do not improve fitting, but instead distort it, the worse. but in essence, this is an objective formulation of a subjectivist model. it sounds completely ridiculous, but that’s exactly what it is. it harmonizes both subjectivity and objectivity in a way in which both are complementary, not opposing views.
regarding the minds as generative spaces, i will provide a simplistic formulation on how to look at complex brains and see them at work, and will provide predictions and tests that can be done to verify this model.
as we saw first, we are dealing with a limited and discrete set of symbols to work with. i postulate that brains create multi-dimensional spaces on which they project their sensory signals (sensory signals are not observations, they are interpretations, thoughts done over classification of input). the best way to imagine this is to imagine a two dimensional brain (two neuron brain). one of its neurons can classify red, and another can classify green. if we shine red, the red neuron lights up. if we shine green, the green neuron lights up. but if we shine yellow, both light up. now, each neuron “knows” only one color, but combined they can represent colors that alone they couldn’t represent. this is typical of many dimensional systems. two lines, one dimensional, once put perpendicular to each other can now represent all points in a plane, even though each one of them has only one dimension, together they’ve expanded “each other’s” representation of reality. red could not see yellow without green, and vice versa.
this means, and this is mostly, as i said, a very broad generalization i am making, that a single neuron is a base vector of that multi-dimensional space. so these two color neurons can represent yellow because when combined together they create a base vector for a 2 dimensional space versus two 1 dimensional spaces. obviously this view is a bit influenced by neural networks (which actually estimate an n-dimensional polygon and hyperplanes). but i take a simpler approach: i’m thinking just in terms of axis, projections and expansions.
each neuron is a base vector, and together they create the “brain” (a base matrix). the imaginable space of a “brain” is, therefore, the space expanded from these base vectors. note that it might be that not all neurons are independent of each other, that would be expectable, so this actually overestimates the capacity of this system. the main point is that i’m saying we are dealing with generative complexity, not actual complexity: the ideas that flow are consequence of the possibilities of representation, and this representation is a consequence of a reducible set of base “structures”.
i will develop on this soon, with more concise definitions, and discuss this whole block of ideas in terms of their predictable consequences in understanding the interaction of living things.