Tom’s Facebook – feelings

[ 1/5/20 Tom on Facebook – we are our feelings]

For me, that model is too limited.

Yes – certainly, our “feelings” are an important part of what we are, and they are deeply complex in ways that my 50 years of interest in biochemistry and systems and evolution is starting to give me some reasonably useful understandings of (at least in broad brush stroke terms), enough to understand that we are more complex than we are capable of appreciating in detail (and that is a potentially infinitely recursive statement).

And we also seem to be more than our “feelings”, and what that more is constituted of seems to be potentially infinitely recursively extensible.

In order to be as fully aware as possible, we need to accept both the reality and the fundamental uncertainty of both sets of propositions.

[followed by not dominated by feelings – but more coherence]

I agree.

We cannot run from our feelings.

We must acknowledge their existence.

And for the most part, their existence seems to be based on the sorting of random variations by the deep time and experience of our genetic and cultural history, and is thus tuned to “that past” and is not necessarily relevant to “this present”. And it is very likely to be relevant, and one always needs to be open to the possibility of “maybe not in this particular instance”, if one has appropriate sets of evidence and interpretive schema.

Coherence can itself be a trap. As can any distinction. And both are often useful.

[followed by]


I see it very differently.

If you look deeply at the most accurate mathematical model of reality that we yet have (quantum mechanics), it has at is heart the notion of the Planck limit. We may not know anything beyond that limit.

That singular idea is able to give us the behaviour of atoms.

If you burrow deeply into it, it is based on constrained randomness.

Both the lawful (contraints) and the random (fundamental uncertainty) exist.

In some contexts, the regularities of the constraints overwhelm the uncertainties and we get regularities in the observable macroscopic world of our normal perception that are accurate beyond our capacity to measure them, beyond the errors inherent in the tools and techniques we use.

In other cases, the uncertainty is dominant, in fundamental ways, like in the decay of an atomic nucleus.

If you think about working things out.
Anything vaguely circular we need to use Pi in the calculations. Pi cannot be known with absolute certainty, one can keep calculating more digits for the rest of eternity.
Often we don’t need many digits for the sort of accuracy we are looking for, so 3.14 is good enough for many purposes, 3.14159 for many more.

If you were trying to calculate the future state of the atoms of a human being, then the accuracy of Pi you need to use starts to get quite large, as we are a collection of some 10^25 atoms, each of which undergoes some 10^12 collisions per second, and you want to know about the state some years ahead (pretending that we could know things to such accuracy, but QM says we can’t), then you would need to use pi to some 50 digits of accuracy – which makes calculations very slow (not enough matter in the solar system to run a simulation like that in real time).

So when you actually start to look very closely at things, then it becomes clear that we can only know things to certain limits of accuracy, and some things are beyond prediction at any level (there are actually many different classes of such things already well characterised). So even if you believed that everything was necessarily related in a fixed way to what came before it (rather than in way that contains both influence and uncertainty), then it is still unknowable. In a universe of hard causality choice is entirely illusion, as everything we ever think or do was eternally present in the instant of the big bang. Fortunately, we have a great deal of evidence that the universe is not of that sort; but lots of people don’t want to look at it, for a whole host of reasons deeply buried in our genetics and cultures.

The computational universe is replete with an infinite set of halting problems.

[9/5/20 – in reply to Ilaalaa]

Hi Ilaalaa,

Enjoyed that reply – thanks.

Perhaps if I approach it this way: …

Yes, certainly, there is a lot of power in the notion of polarity.

Binary systems are the simplest possible differentiable structures, and there are many instances of them in reality.

Many things do genuinely have such polar structure.

To change conceptual “tacks” (to borrow a sailing metaphor), Turing showed a very long time ago that any computational structure may be modeled in any other computational structure (at least to some degree of accuracy) if it meets certain conditions (known as Turing completeness). So yes, there is a sense in which any construct may be modeled within the “polar” systemic view.

The view certainly has power. Tom and I have been interacting for about 20 years. We must each find the other’s perspectives sufficiently interesting to keep it going. There has to be a degree of respect there, and there is.

I do think Tom’s polar approach is entirely appropriate to many aspects of reality, and can generate useful models of anything if used at an appropriate level of abstraction; and I am also completely clear that there exists an infinite set of schema that are more complex (more than two poles present).

I have spent some time exploring some of them; and mostly I work with fundamentally polar systems, and the one I use most often is the spectrum of uncertainty, where there is only one thing in all of reality that I am entirely (100%) certain of (that I am some sort of something, but not 100% certain what sort of something – only about 99.9% confident of the major general classes of complexity present in me – and most others, most of the time).

To change tacks again (into a new set of dimensions), all concepts can be traps. If we have concepts that work, we will tend to classify anything close enough as being in that {set}.

That is how neural nets work. We cannot entirely escape it, ever. Creating new distinctions is difficult, particularly when the model in use is, by definition, sufficiently complex (Turing complete) that it can model anything.

Getting into the habit of deliberately trying out new modeling schema is hard – particularly when dealing with fundamental binary distinctions (and all of the distinctions at the core of our neural nets are binary – so in a sense we are all “happiest” there – part of why I find coding so rewarding and peaceful – it is completely binary – it is hard work leaving that for uncertainty and complexity, and making that effort has rewards).

To give you a sense of just how far I have taken that – 42 years ago I was simultaneously active in the rationalists, humanists, theosophical society, fishermen’s association, science groups, management groups, Jaycees, young farmers club, and a range of others (32 in total in 1978).

I am similarly engaged across a very broad spectrum of groups today (actually very busy this week).

In the last 42 years I have explored computational theory, decision theory, modeling theory, complex math, evolutionary theory, relativity, quantum mechanics, modeling systems, nature, politics, AI, … and have on a couple of occasions managed to operate at 12 levels of abstraction, but find communicating even second order abstractions extremely difficult if the other person is not already familiar with similar classes of “things”.

I hope that helps make a little more sense of me, gives a few more clues about the direction and dimensional depth I am trying to point to, and why I push Tom as hard as I do.


I get that is your theory, your truth.

I can see how it might seem to be that way to you.

I can see how what you wrote makes sense to you.

I am working from a different paradigm.

What you wrote does not make sense from the paradigm I use.

The paradigms are different.

Mine is not based on certainty about anything in respect of reality.
I can deal with certainty within sets of modeling constraints (like boolean logic, or various forms of predicate calculus.

And each of those are self consistent systems (much like your polar system).
Within any such modeling system, any other system can be modeled to some degree of utility.

For me, all models have some degree of utility in some contexts.

For me, all attempts to model or understand reality seem very probably to be based on probabilities and evolutionarily sorted sets of Bayesian priors. So we come pre-configured by evolution in both biological and cultural domains to accept and “see” certain sets of models and characteristics in the world we perceive, and to make certain sets of associations with higher probabilities than others.

The exploration of those systems in detail has led to me developing the framework of understandings that I have.

I can see the utility of using simple models under stress.

I can see the utility of developing more complex and accurate models as time and resources allow. That process seems to be potentially infinitely extendable.

I need to get back to mixing and laying plaster – back to this tomorrow if you’re still interested.

[14/5/20 first of 2]


I don’t think my model of my own thinking is 100% correct.

I think it is logically and physically impossible to know yourself with 100% accuracy – for all sorts of different reasons.

I am reasonably confident about the major themes of the systems that seem very probably responsible for much of the experience of being that I have.

As to your supposedly metaphysical question, it doesn’t occur in my schema.

In my understanding, knowing (or confidence) is a sequence of states. We experience a sequence of such states, and have memory of some of them to some degree of accuracy.

We have the experiences we do when we do.

Not sure how “speed” relates to that framework.

[ followed by]


Read what I wrote “that I am some sort of something, but not 100% certain what sort of something”.

Your logic is completely circular (as all logics are) and proves nothing about reality (as no logics do).

Logic, mathematics, are useful tools. They are the best modeling tools we have.

Is a map (a model) ever the territory?


We do not experience reality directly. The evidence sets are overwhelming that what we experience is a subconsciously generated model of reality.
We experience the model, not reality.

We infer about reality from the model.

We have no direct access to reality, only via the model(s) we have.

[Tom responded – you materialist – you bore me.]

We are all made of material.

That material can do some interesting things.

Being clear about the degrees of relatedness is important.

About Ted Howard NZ

Seems like I might be a cancer survivor. Thinking about the systemic incentives within the world we find ourselves in, and how we might adjust them to provide an environment that supports everyone (no exceptions) - see
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