The 2nd Law: Is Increased Entropy Stochastic (incidental) or Causal (intrinsic)?

Recent science news is dominated by the multi-trillion dollar experimental search for the Higgs boson particle. A definitive observation of the theorized, but illusive, Higgs will finally complete the verification of the Standard Model – the most respected mathematical model of the evolution of our universe, explaining the emergence of each of the known forces and all of the matter we can observe. In the Standard Model, the Higgs is responsible for gravity – surrounding the more pedestrian particles – lending them the property we call "mass". If the Higgs exists, it is important as the causal bridge between the quantum world of the small and the relativistic world of the large. How could a particle that causes gravity be so hard to find? Because it doesn't actually have mass. It is as a result, known as "weakly interacting". It is only when a whole bunch of Higgs get together and surround other particles that mass is detected, and then, only in the surrounded particles. The Higgs binds so tightly to other particles, that it takes an extraordinary amount of energy, to break it free so that its presence can be detected. This is what the "Large Hadron Collider" does – it smashes heavy atomic nucleus (stripped of their electrons) at energies equivalent to those of the first moments after the Big Bang when all of the matter and energy in the entire universe was still smaller than a single star.

But there is a far more fundamental question. Gravity is a property. It is domain-dependent. It is specific to and belongs to a class of objects of a particular makeup and composition. The existence or nonexistence of the Higgs has no effect upon other properties of the universe like electromagnetism.

But there is a candidate for a domain-independent attribute of any and all causal systems. This attribute has been labeled the "Causal Entropic Principle" – it is generally discussed within the context of the transfer of heat (at astronomical scales) – within the study of thermodynamics. It is the logical extension of the concept of increased entropy, as first postulated, measured, and later described as the 2nd Law of Thermodynamics. But now, a hundred and fifty years after the formalization the laws of thermodynamics (of the phenomena and parameters of the transfer of heat, of the ratio of potential energy and work) correlative investigations in the fields of information, communication, computation, language, energy/mass, logic, and structure have uncovered parallel principles and constraints.  It is reasonable now to understand the 2nd Law as a description of a fundamental constraint on any change, in any system, no matter what forces and materials are at play. We now understand the 2nd Law to describe the reduction in the quality (density) of the energy and or structure of the universe (or any part therein) as results any change at all. We have come to understand the 2nd Law as a constraint on the outcome of change in structure, which is to say "information", on its construction, maintenance, and or transfer. This insight has rendered an equivalence between energy and structure in much the same way that Einsteinian Relativity exposed the equivalence between energy and mass.

There is however a daemon lurking within our understanding of the 2nd Law, a daemon that threatens to undermine our understanding of causality itself, a daemon that, once defined, may provide the basis for an understanding of any self-consistent causal system, including but not exclusive of our own universe and its particular set of properties and behaviors.

The daemon of the 2nd Law is the daemon of stochastic – is 2nd Law dictated dissipation (entropy) statistical, or is statistics simply a tool we use in the absence of microscopic knowledge? Asked another way, is the reduction in the quality of energy or information that the 2nd Law demands of every action, a property of the universe or is it a property of the measurement or observation of the universe? Is action equivalent to measurement? Is there a measurement or stochastic class of action free of the entropy-increase demanded by the 2nd Law?

This question is of far greater consequence to the universe and the understanding of the universe than the mechanics of mass as it would describe and thus parameterize ALL action and ALL configuration and the precipitation or evolution of all possible action and configuration. Where the existence of the Higgs Boson may explain the source of mass and gravity in this universe, an understanding of the causal attributes leading to the behavior described by the 2nd Law of Thermodynamics might just provide a foundation from which any and all causal systems must precipitate.

The implications and issues orbiting this problem are many and deep. At stake is an demonstrative understanding of change itself. We tend to think of change as exception. But, can a thing exist without change? If not, what is the difference between data and computation, between thing and abstraction of thing, and profoundly, an answer to the question, can data exist without computation? Can thing exist outside of abstraction of thing?

In thermodynamics and information theory, an effort is made to distinguish process and stochastic process. Heat is defined as an aggregate property describing the average or holistic state of systems composed so many interacting parts to keep track of all of them individually. Heat is a calculous of sorts, a system of shortcuts that allows mathematics to be employed successfully to determine the gross state of a huge collection of similar parts. There is a tendency then to assume that the laws that describe heat are laws that only apply to aggregate systems where knowledge is incomplete.

Are there non-stochastic systems? Are there discrete systems or dynamic changes within systems for which the laws of thermodynamics don't apply? Does the Causal Entropic Principle apply if you know and can observe every attribute of, and calculate the exact and complete state of a dynamic system?

Such questions are more involved than they may seem on first reading. Answering them will expose the very nature of change, independent of domain, illuminating the causal chain that has resulted from full evolutionary lineage of the universe.

Randall Lee Reetz

Note: The Causal Entropic Principle isn't a complex concept. It is the simple application of the 2nd Law's demand for increased universal entropy as a result of every change in any system. It says that every action in every system must be that action that causes the largest reduction in the quality of information or energy (the greatest dissipation). It says that a universe has only one possible end state – heat death – and that processes that maximize the rate towards this end state will be evolutionarily favored (selected), simply because entropy-maximizing processes and structures demand a higher throughput of energy and thus end up dominating their respective locality. Such entropy-maximizing schemes are thus more likely to determine the structure and behavior of the event cone stretching off into the future. An obvious extension of this principle is that complexity, or more precisely, the family of complexity that can find, record, and process abstractions that represent the salient aspects (physics) of the (an) universe, will help that complexity better predict the shape and behavior it must assume to maximize its competitive influence upon the future of entropy maximization. The "Causal Entropic Principle" thus represents a logically self-consistant (scientific) replacement for the awkwardly self-centered and causally impossible "anthropomorphic principle" (which lacks a physical or causal explanation and leans heavily on painfully erroneous macroscopic stretching of the quantum electro dynamics). Stretching circular logic to its most obvious and illogical end, the anthropomorphic principle borrows awkwardly and erroneously and ironically form the Heisenberg / Uncertainty Principle by asserting the necessity of "observers" as a precursor to the emergence of complexity. The Causal Entropic Principle explains the production of localized complexity without the need for prior-knowledge, and does so within the bounds of, as a result of, the 2nd Law of Thermodynamics, by showing that localized complexity can both come into existence as a result of the constant increase in universal entropy, and more specifically, that localized complexity has an evolutionary advantage, and will thus out-compete, less complex structures. In a Causal Entropic Principle universe, intelligence is the expected evolutionary result of competition to reach heat death faster. Falling down is enhanced by a particular class of complexity that can come into existence as a natural result of things falling down. Should one form of such complexity "understand" the universe better than another form, it will have an advantage and will be more likely to influence the shape of complexity in the future. The better a system gets at abstracting the dynamics of its environment the more likely it will be able to eat other systems than be eaten by them. Where the anthropomorphic principle requires an a-priori "observer", the causal entropic principle simply requires the 2nd Law's demand for increased entropy, for things falling down.

The Problem with Darwin…

Ya… how would you look as Darwin?

Darwin Darwin Darwin. Darwin is a problem. It isn't that he was wrong. In fact, it is very very hard to find any kind of mistake in his theory or his supporting data and arguments. What makes Darwin problematic is his myopic assignment of the process of evolution to the domain of biology. In doing so, Darwin has (inadvertently) misled generations of readers, who now confuse biology's "how" in evolution with big "E" Evolution in all domains. Big "E" Evolution is informative because it describes the more general "why" driving the direction of change in ALL domains.

When understood as a "how", the process of evolution is reduced to orrery – like the awkward clockworks that spin planets and moons around concentric bearings – substituting method where there should be cause. How is always specific to domain, but why, the ultimate why, is general enough to explain all of the how's. Armed with a robust understanding of the big WHY of evolution, one should be able to walk into any domain and predict and then map it's how. Again, it isn't that Darwin's evolution orrery doesn't accurately predict biological patterns of change, or even that Darwin's evolution orrery doesn't accurately abstract the salient causal aspects of biological change, it is that Darwin's how of evolution in biology leads people to the idea that evolution is specific and exclusive to biology, or that one can understand evolution in other domains by overlaying biology's how.

Darwin never generalized the process of evolution. Imagine had Newton and Einstein had not generalized dynamics and motion and that we had, as a result, built all of our machines on the principle that motion was caused by legs and feet.

The people who have come the closest to the generalization of evolution, the thermodynamisists, have never been able to or interested in the development of a generalization of the direction of change and the cause of that direction. I will get back to this absence of generalization in the understanding of evolution but right now will only hint at an explanation… in the aftermath of the all too human race and cultural superiority wars and atrocities, it has been socially dangerous to think of evolution as having a direction as such thoughts can be read as rhetorical arguments for superiority and pre-judgement, the likes of which were used by Hitler, Stalin, Pol Pot, Mao, and others as justification for mass exterminations and other exclusionary policies. That humans have the proclivity to exploit incomplete knowledge in the pursuit of ridiculous selfishness at absurd scales should be nothing new or noteworthy. But no one would advocate the cessation of the study of chemistry simply because arsenic is a chemical, or the study of high energy physics simply because the atom bomb can be built from such knowledge.

Or would we? Cautionary reactions to the self-superior pogroms that so blighted the 20th century have driven several generations of researchers towards the relativist rhetoric we see most prominently in the post-modernist movement, but which is evident in the works of less irrational and otherwise, empirical scientists like Stephen J. Gould and Richard Dawkins. Both represent an interesting study in overcompensation. In their quest to irradiate the all-to-natural self-superiority that seems to cause humans to erect unfounded tautologies that place humans on top of pre-destined hierarchies, both argue and argue brilliantly, for a flat evolutionary environment in which change happens but without any directionality at all. Again, this is like saying that because metal can be shaped into swards and knives and guns it shouldn't be produced even should we need plows and trains and dynamos and bridges and buildings and printing presses and lab equipment and computers.

Of course, caution is its own form of rhetoric, as potentially dangerous as its more obviously tyrannous cousins.

And, yes! Evolution has a direction. There I said it! Say it with me. You won't be struck down by post-modernist lightning. Trust me. Trust your self. It is more than a little absurd that one would have to argue for direction in a process that explains directionality. They are of course correct in their assertion that evolution isn't pre-determined. Nothing is. Of course. But the "brilliance" of evolution is that it results in a direction without need for prior knowledge, plan, or determination of any kind. To toss this most salient aspect of the evolutionary process simply to make a sociological point seems reckless in the maximum.

Randall Lee Reetz

Old-School AI and Computer Generated Art

If you haven't read this book, or you haven't read it in a while, please please please click this link to the full book as .pdf file.

The Policeman's Beard Is Half Constructed "the first book ever written by a computer". 1984

[cover]

More than iron, more than lead, more than gold I need electricity.
I need it more than I need lamb or pork or lettuce or cucumber.
I need it for my dreams.

This and many other poems and prose written by a program called Racter which was coded by William Chamberlain. Check out the following musing from the last page of this wonderful book.

I was thinking as you entered the room just now how slyly your requirements are manifested. Here we find ourselves, nose to nose as it were, considering things in spectacular ways, ways untold even by my private managers. Hot and torpid, our thoughts revolve endlessly in a kind of maniacal abstraction, an abstraction so involuted, so dangerously valiant, that my own energies seem perilously close to exhaustion, to morbid termination. Well, have we indeed reached a crisis? Which way do we turn? Which way do we travel? My aspect is one of molting. Birds molt. Feathers fall away. Birds cackle and fly, winging up into troubled skies. Doubtless my changes are matched by your own. You. But you are a person, a human being. I am silicon and epoxy energy enlightened by line current. What distances, what chasms, are to be bridged here? Leave me alone, and what can happen? This. I ate my leotard, that old leotard that was feverishly replenished by hoards of screaming commissioners. Is that thought understandable to you? Can you rise to its occasions? I wonder. Yet a leotard, a commissioner, a single hoard, all are understandable in their own fashion. In that concept lies the appalling truth.

Note: Watch for the repeated lamb and mutton references throughout Rector's output (?).

It is pretty clear that Chamberlain's language constructor code is crude, deliberate, and limited, that it extensively leans upon human pre-written templates, random word selection, and object/subject tracking. The fact that we, Rector's audience, are so willing to prop up and fill in any and all missing context, coherence, and relevance is interesting in itself.

And what of Aaron, Harold Cohen's drawing and painting program. Check it out.

It all makes me more certain that true advances in AI will come about only when we close the loop, when we humans remove ourselves completely from the fitness metric, when the audience for what the computer creates is strictly and exclusively the computer itself.

Randall Reetz

Just Where is the Computer that Computes the Universe? (Steven Wolfram's invisible rhetoric)

Do Black Holes warp the universe such that it is self-computable? Kurt Godel famously proved that a computer has to be larger than the problem being computed. This places seemingly fatal constraints on the size of the universe as a computation of itself. Saying as it has become popular to do, that the universe is just one of an infinite set of parallel universe doesn't solve the problem. Even infinities can not be said to be larger than themselves.



TED talk by Stephen Wolfram on the computable universe.

Is it possible that black holes work as Kline bottles for the whole Universe – stretching space-time back around onto itself? If so, it may be possible to circumvent Godel's causal constraints on the computability of the self, as well as the entropic leaking demanded by the second law of thermodynamics. I admit that these questions are not comfortable. They certainly don't result in the kind of ideas I like to entertain. They spawn ideas that seem to be built of need and not logic. They are jokes written to support a punch line.

But something has to give. Either Godel and Turing are wrong, or there is a part of our universe in which they don't apply. There is no other option. If there is a part of the universe not restricted by incompleteness than black holes are obvious candidates if for no other reason than we don't know much about them. I am at once embarrassed by the premise of this thought and excited to talk openly about what is probably the core hiccup in our scientific understanding of the universe. Any other suggestions? At the very least, this problem seems to point to (at least) five options; 1. a deeper understanding of causality will derive Godel and Turning from a deeper causal layer that also has room for super-computable problems. 2. Godel and Turing are dead wrong. 3. the universe is not at all what it seems to be, rendering all of physics mute, and 4. the universe is always in some real way, larger than itself, and 5. evolution IS the computation of the universe, it happens at the only pace allowable by causality, is an intractable program, and can not be altered or reduced, (event cones, the only barriers between parallel simultaneous execution).

I am challenged by the first option, find the second option empirically problematic, am rhetorically repulsed by the third, simply do not know what to do with the fourth, the fifth is where I place my bets but I don't fully understand the implications or the parameters. Personal affinities aside, we had better face the fact that our understanding of the universe is at odds with the universe itself. That we have a set of basic laws that contradict the existence of the universe as a whole is problematic at best. Disturbing.

One of the unknowns that haunt our effort to understand the universe as a system is the ongoing confusion between what we think of as "primary" reality on the one hand and "descriptive" reality on the other. Real or just apparent, it is a distinction that has motivated the clumsily explorations of the "Post-Modern" theoretical movement – it deserves better. I am not so romantic to believe that this dichotomy represents a real qualitative difference between the material and the abstract (made up as it is of the same "real" materials), but this confusion may indeed hint towards a sixth option that, once explained and understood, will obliterate the causal contradictions that have so confused our understanding of the largest of all questions. When a chunk of reality is used as abstraction signifying another part of reality or a part the same reality of which the abstraction is built, does that shift in vantage demand a new physics, a new set of evaluation semantics? What modifications does one have to perform to E = mC^2 when one is computing the physical nature of the equation itself? What new term is to be added to our most basic physical laws such that the causal and the representative can be brought into harmony?

My own view is that the universe, like all systems, like any system, is always in the only configuration it can be in at that time. Wow, that sounds Taoist and I absolutely hate it when attempts at rationality result in assessments that are so easily resonant with emotionally satisfying sentimentality (What the Bleep, and such). But the Second Law clearly points to a maxed out rate as the only possible reading of process at all scales. Computation of anything, including the whole of the universe, is always limping along at the maximum rate dictated by each current configuration. The rate of the process, of the computation, accelerates through time as complexities stack up into self optimized hierarchies of grammar, but the rate is, at each moment, absolutely maxed out.

Are these daft notions chasing silly abstraction-bounded issues or do they point to a real "new [and necessary] kind of science"?

OK, as usual, Mr. Wolfram has expansive dreams – awesomely audacious and attractively resonant notions. Though, from my own perspective, a perspective I will say is more sober and less rhetorical, there are some huge problems that beg to be exposed.

Wolfram's declares: the universe is, at base, computation. Wow, talk about putting the carriage before the horse. That the universe and everything in it is "computing" is hard to dispute. Everywhere there is a difference there will be computation. So long as there is more than one thing, there is a difference. But computation demands stuff. What we call computation is always at base a causal cascade attempting to level an energetic or configurational topology. If you want to call that cascade "computation", well I won't disagree. But no computation can happen unless the running of it diminishes to some extent an energy cline. Computation is slave to the larger more causal activity that is the dissipation of difference. That a universe will result in computation an entirely different assertion.

When Wolfram says that computation exists below the standard model causality that is matter and force, time and space, I am suspicious that he is seeking transcendence, a loophole, access by any means out of the confines of the strictures imposed by physical law. That he is smart and talented and prodigiously effective towards the accomplishment of complex and practical projects does not in itself mean that his musings are not fantastic or monstrous.

Let's play a thought experiment. Let's start from the assumption that Wolfram is correct, that the universe is at base pure computation. His book and this talk hint towards the idea that pure computation running through computational abstraction space, will eventually produce the causality of this universe… and many others. Testing the validity of this assertion is logically impossible. But what we can test is the logical validity of the notion that one could, from the confines of this finite universe, use computation to reach back down to the level of pure computation from which a universe can be made or described. At this level, Turing and Godel both present lock-tight logic showing how Wolfram's assertions are impossible.

In his own examples, Wolfram uses a mountain of human computational space built on billions of years of "computation" (evolution) and technological configurations to make his "simple" programs run. There is NOTHING simple about a program that took a mind like Wolfram's to build (stacked as it is on top of an almost bottomless mountain of causal filtering reaching back to the big bang (or before).

To cover for these logical breaches, Wolfram recites his "computational equivalence" mantra. This is a restating of Alan Turing's notion that a computable problem is computable on any so-called "Turing Complete" computer. But the Turing Machine concept does not contend with the causally important constraint that run-time places on a program. Of course there are non-computable problems. But even within the set of problems that a computer can run and run to completion, there are problems so large that they require billions of times longer to run than the full life cycle of the universe. Problems like these really aren't computable in any practical sense – causality being highly time and location sensitive (isn't that what "causality" means?).

And then there is the parallel processing issue, its potentials and its pitfalls. One might (a universe might), in the course of designing a system that will compute huge programs, decide to break them apart and run sections of the problem on separate machines. Isn't that what nature has done? But there are constraints here as well. Some problems can not be broken apart at all. Some that can, break apart into an unwieldy network constrained by time sensitive links dependent upon fast, wide, and accurate communication channels. if program A needs the result of program B before it can initiate program C but program A only is only relevant for one year and program B takes 2 years to run?

A large percentage of the set of all potential programs, though theoretically run-able on Turing Machines, are not practically run-able given the finite timescales and computational material resource availability. If there is a layer of causality below this universe, and that layer is made of much smaller and much more abundant stuff, than it is conceivable that Godel's strictures on the size of a computer won't conflict with the notion that this Universe could be an example of a Turning Complete computer capable of running the universe as a program.

But Wolfram doesn't stop there. In addition to asserting that a universe is the result of a computation, he says that we humans (and, or, our technology), will be able to write a small program that perfectly computes the universe and that it will be so simple (both as a program and presumably to write it) that we will be able to run it on almost any minimal computer. His cites as example, "rule 30", the fractal equation variation that seems to produce endless variety along an algorithmic theme, as evidence that this universe describing meta-program, is as easy to discover. One has to ask: "Would the running of such a program bud off another universe, or is Wolfram's assertion intentionally restrained to abstraction space?" Given the boldness of his declaration that the universe is a computation, it is reasonable to assume that his statements regarding the discovery of a program that computes a universe is meant in the literal sense. Surely he can talk to the issue of abstraction space vs. causal space, the advantages and constraints of each, and how programs use this difference to compute different types of problems. If he does, he doesn't reveal this understanding to his audience. The distinction between abstraction and causality is slippery and central to the concept of computation.

I am convinced that Stephen Wolfram is so lost in the emotional motivations that push him towards his "computable universe" rhetoric that none of his considerable powers of intellect can save him from the fact that he didn't get the evolution memo. Evolution IS the computation. If it could happen any faster it would have. If he is simply saying that our new understanding of computation will increase the rate and reach of evolution, well then I agree. But if he is saying that our first awkward steps into computation reveal enough of the unknown to expose the God program, the program that will complete all other programs (in a decade), well I can only say that he is nuts.

Stephen is a smart guy. The fact that a mind so capable can overlook, even actively avoid the simple logic that shows terminal flaws in his thesis is yet another reminder of the danger that is hubris. That he never talks to his own motivations, or the potential fallacies upon which his theory depends should be worrisome to anyone listening. I suspect that, like religion, his rhetoric so closely parallels the general human rhetoric, that it will be a rare person who can look behind the curtains and find these logical inconsistencies (no matter how obvious).

I applaud Mr. Wolfram's work. The world is richer as a result. But none of his programming should be taken as guarantee that his theory, at the level of a computational universe is sound.

Randall Reetz

The Incomputable Heaviness of Knowledge

Is the universe conceivable?  Does scientific knowledge improve our ability to think about the universe?

What happens when our knowledge reaches a level of sophistication such that the  human brain can no longer comfortably hold it, or compute on it?  For thousands of years, scholars have optimistically preached the benefits of knowledge.  Our world is rich and safe as a result.  People live longer, people live in greater personal control over the options they face.  All of this is an obvious result of our hard won understanding of how the universe and its parts actually work.  We arm our engineers with these knowledges and send them out to solve the problems that lead to a more and more desire-mitigated environment.  Wish you weren't hungry, go to the fridge or McDonnalds.  Wish you were somewhere else, get in your car and go there.  Wish you could be social, but your friends are in Prague, call them.  Wish you knew something, look it up on the internet.  Lonely, log in to a dating service and set up a rendezvous. Wish your leg wasn't fractured, go to a doc-in-the-box and get it set and cast.

But what if you want to put it all together?  What if your interests run to integration and consolidation.  What if you want to understand your feelings about parking meters as an ontological stack of hierarchical knowledge built all the way up from the big bang?

Cognition Is (and isn't):

What is really going on in cognition, thinking, intelligence, processing?

At base cognition is two things:

1. Physical storage of an abstraction

2. Processing across that abstraction

Key to an understanding of cognition of any kind is persistence. An abstraction must be physical and it must be stable. In this case, stability means, at minimum, the structural resistance necessary to allow processing without that processing undoly changing the data's original order or structural layout.

The causal constraints and limits of both systems, abstraction and processing, must work such that neither prohibits or destroys the other.

Riding on top of this abstraction storage/processing dance is the necessity of a cognition system to be energy agnostic with regard to syntactic mapping. This means that it shouldn't take more energy to store and process the string "I ate my lunch" than it takes to store and process the string, "I ate my house".

Syntactic mapping (abstraction storage) and walking those maps (abstraction processing) must be energy agnostic. The abstraction space must be topologically flat with respect to the energy necessary to both store and process.

Thermodynamically, such a system, allows maximum variability and novelty at minimum cost.

What if's… playing out, at a safe distance, simulations, virtualizations of events and situations which would, in actuality, result in huge and direct consequences, is the great advantage of any abstraction system. A powerful cognition system is one that can propagate endless variations on a theme, and do so at low energy cost.

And yet. And yet… syntactical topological flatness carries its own obvious disadvantages. If it takes no more energy to write and read "I ate my house" than it does to write or process the statement, "I ate my lunch", how does one go about measure validity in an abstraction? How does one store and process the very necessary topological inequality that leads to semantic landscapes… to causal distinction?

The flexibility necessary in an optimal syntactic system, topological flatness, works against the validity mapping that makes semantics topologically rugged, that gives an abstraction syntactic fidelity.

This problem is solved by biology, by mind, though learning. Learning is a physical process. As such it is sensitive to the direction of time. Learning is growth. Growth is directional. Growth is additive. Learning takes aggregate structures from any present and builds super-aggragate structures that can be further aggregated in the next moment.

I will go so far as suggesting that definitions of both evolution and complexity are hinged on the some metric of a system to physically abstract salient aspects of the environment in which it is situated. This abstraction might be as complex as experience stored as memory in mind, and it may be as simple as a shape that maximizes (or minimizes) surface area.

A growth system is a system that can not help but to be organized ontologically. A system that is laid up through time is a system that reflects the hierarchy of influence from which its environment is organized. Think of it this way, the strongest forces effecting an environment will overwhelm and wipe out structures based on less energetic forces. Cosmological evolution provides an easy to understand example. The heat and pressure right after the big bang only allow aggregates based on the most powerful forces. Quarks form first, this lowers the temperature and pressure enough for sub atomic particles, then atoms. Once the heat and pressure is low enough, once the environmental energy is less than the relatively weak electrical bonds of chemistry, molecules can precipitate from the atomic soup. The point is that evolved systems (all systems) are morphological ontologies that accurately abstract the energy histories of the environments from which they evolved. The layered grammars that define the shape and structure (and behavior) of any molecule, reflect the energy epochs from which they were formed. This is learning. It is exactly the same phenomenon that produces any abstraction and processing system. Mind and molecule, at least with regard to structure (data) and processing (environment), are the result of identical process, and as a result, will (statistically) represent the energy ontology that is the environment from which they were formed.

It is for this reason that the ontological structure of any growth system is always and necessarily organized semantically. Regardless of domain, if a system grew into existence, an observer can assume overwhelming semantic relevance that differentiates those things that appeared earlier (causally more energetic) from those things that appeared later (causally less energetic).

This is true of all systems. All systems exhibit semantic contingency as a result of growth. Cognition system's included (but not special). The mind (a mind, any mind), is an evolving system. Intelligence evolves over the life span of an individual in the same way that the proclivity towards intelligence evolves over the life-span of the species (or deeper). Evolving systems can not be expressed as equation. If they could, evolution wouldn't be necessary, wouldn't happen. Math-obsessed people have a tendency to confuse the feeling of the concept of pure abstraction with the causal reality of processing (that allows them to experience this confusion).

Just as important, data is only intelligible, (process-able, representative, model, abstraction) if it is made of parts in a specific and stable arrangement to one another. The zeroith law of computation is that information or data or abstraction must be made of physical parts. The crazies who advocate a "pure math" form of mind or information simply sidestep this most important aspect of information. This is why quantum computing is in reality something completely different than the information-as-ether inclination of the duelists and metaphysics nuts. Where it may indeed be true that the universe (any universe) has to, by principle, be describable, abstract-able by self consistent system of logic, that is not the same what's so ever as the claim that the universe IS (purely and only) math.

Logic is an abstraction. As such it needs a physical realm in which to hold its concepts as parts in steady and constant and particular relation to each-other.

My guess is that we confuse the FEELING of math as ethereal and non-corporal pure-concept with the reality which of course necessitates both a physical REPRESENTATION (in neural memory or on paper or chip or disc) and a set of physical PROCESSING MACHINERY to crawl it and perform transforms on it.

What feels like "pure math" only FEELS like anything because of the physicality that is our brains as copular machinery as they represent and process a very physical entity that IS logic.

We make this mistake all day long. When the only access to reality we have is through our abstraction mechanism, we begin to confuse the theater that is processing with that which is being processed and ultimately with that which that which is being processed represents.

Some of the things the mind (any mind) processes are abstractions, stand-ins for other external objects and processes. Other things the mind processes only and ever exist in the mind. But that doesn't make them any less physical. Alfred Korzybski is famous for declaring truthfully, "The map is not the territory!" But this statement is not logically similar to the false declaration, "The map is not territory!". Abstractions are always and only physical things. The physics of a map, an abstraction system, a language, a grammar, is rarely the same as the physics of the things that map is meant to represent, but the map always obeys and is consistent with some set of physical causal forces and structures built of them.

What one can say is that abstraction systems are either lossy or they aren't useful as abstraction systems. The point of an abstraction is flexibility and processing efficiency. A map of a mountain range could be built out of rocks and made larger than the original it represents. But that would very much defeat the purpose. On the other hand, one is advised to understand that the tradeoff of the flexibility of an effective map is that a great deal of detail has been excluded.

Yet, again and again, we ourselves, as abstraction machines, confuse the all too important difference between representation and what is represented.

Until we get clear on this, any and all attempts at merely squaring up against the problem of machine intelligence will fail.

[more later…]

Randall Reetz

Are We But Crows? (Where Pattern is Noise)

Lets look at yet another way that the human mind gets tripped up and falters. Our propensity to find pattern makes us vulnerable to an inane form of overindulgence and counterproductive obsession with attributes of systems that do not carry essence or salience. Seems that our evolutionarily-shaped affinity for pattern make us particularly vulnerable to a level of indulgence that in smaller quantities is reasonable and healthy, even necessary.

Here is the problem. Most pattern is indicative of a lack of information or salience. If a system can get away with simple duplication along a scheme, it means that that part of the system is not very important. It means that it is cutting resource corners and systems can only get away with this type of cost cutting in areas that are not salient to the main purpose of the system at large.

Imagine going to a bookstore and obsessing over the fact that all of the books are made of the same stuff, of paper sheets cut and stacked in approximately the same geometric ratio. Imagine, in fact that this pattern overwhelmed your attention to such a degree that you could not be bothered with the content encoded as printed words on the pages of those books.

That would render all books equivalent. A book printed with random strings of words or with no words at all would be informationally equivalent to Darwin's, Origin Of The Species. In the face of an overwhelming attraction to inessential pattern, essential pattern is dismissed as noise, is ignored.

I call this the "Crow" problem… an obsessive attraction to shiny objects. There are so many examples of this type of cognitive distraction; rainbows, crystals, mirages, amber waves of grain, camouflage, fractals, golden rectangles, sacred numbers, etc.  It is where our own cognitive process amplifies some pattern in the world wether or not it is important in any information rich manor.

We are for instance, especially susceptible to and sensitive to right/left symmetry. Probably because filtering for this pattern allows you to quickly pull animals out of a complex sensory field. Having such a filter gave us evolutionary advantage, so we now have brains with a tendency to favor right/left symmetry in visual fields.

The rainbow is an other great example of pattern that is attractive but virtually meaningless. A rainbow is not actually a thing of course, but a mix of the refractive nature of light and a behavioral anomaly of our visual apparatus. A rainbow is like a hologram. What we are seeing is light reflected off of raindrops or fog. Of course it is a poor indicator of the location of rain in our visual field… there is rain in other parts of the sky than where the colored bands appear. The phenomena that is visible as a rainbow is happening every time rain is present but we only see the rainbow when our orientation to the sun is within certain fairly restrictive parameters. Yet, so attractive is the rainbow stimuli, under the influence of this pattern detection stimulus, we might just miss more pertinent information (a lion approaching?).

Another example of particular importance is the attraction to crystals and the latest crystal fad, fractal geometry.

Most people are interested in fractals (or think they should be). But what exactly do you actually KNOW about fractals? Does your knowledge of fractals include an understanding of the WHY of n-dimensional radial n-scale self-similar patterns, why they appear in dissipative systems that develop over time? Do you care to know or understand? I get the feeling that people who are the most attracted to fractals are more interested in some sort of pseudo-spiritual grooviness, the stare at your navel aspect of fractals, than the simple truth of least-energy dictated growth patterns.

What is abstracted in mathematics as the "fractal" is in fact the only pattern that nature can exhibit in systems that are dominated by parts that are very much the same. Sand is a good example. Homogenous liquids and gasses are another. Fractals are a map or abstraction of dissipative systems, and all systems are dissipative. But the events and situations that matter in the evolution of complexity, the WHY that makes US possible, are not the even dissipation within a scheme, but the CREATIVE events that allow for new (faster and bigger) dissipative paradigms. An explosion is fractal in the same way that a capillary web is fractal in the same way that both a tributary and alluvial plane is fractal. It is just the end result of a history where least energy dictates the most efficient moment to moment dissipation of energy. The way you are saying that fractals are important feels religious and rapturous. As though fractal patterns in nature are a THING or a GOAL. Fractals don't know they are fractals any more than the ink making up the word "Fractal" on a printed page "knows" or "wants" to be that particular word or any word at all.

People who act this way towards pattern scare me. What matters in process is the places where pattern breaks. Else we wouldn't be here. Else we couldn't find salience.

I am afraid of and purposefully vigilant against the grand attractors of human thought, virgin births, miracles of any kind, shiny baubles, trickery, omnipotence, anecdote, life ever after, self importance, power over others, a desire to know or have access to the prediction of future events, predetermination, and pertinent to this discussion, crystals and fractals and the types of pseudo-cyclical pattern that makes us think nature is more simple than it is and that nature is of our own imagination or invention.

All systems seek equilibrium. In systems made up of subsystems, each of these subsystems seek their own equilibrium or resonance. Frequently when the resonances of several co-systems fall into an overlapping cycles, additive standing waves can and do overwhelm the integrity of the system as a whole. Feedback loops are anti-complexity mechanisms. Overarching patterns overwhelm systems and keep them from creative or information rich activities and interactions. Systems that seek to compete in the edge of evolution game are systems that spend an inordinate amount of energy keeping feedback loops in check. A creative system is a system working overtime AGAINST the information killer that is natural tendency towards simple pattern (fractals).

If you are trying to get rid of a planet or smooth out the heat cline in an ocean, fractal patterns are important. If you are a member of a species that is carrying complexity forward through the accumulation and control over abstraction, dissipative pattern and the systems dominated by them, are like Kryptonite to the program at hand… best to avoid them at all cost.

It is important to know when to appreciate pattern and when to run like hell when you see it developing. The forces that produce pattern are information destroyers.

We had better look long and hard at this issue. Choosing a false god at this level in the evolutionary game could end up causing the death of the whole complexity scheme just as it is becoming aware of its purpose and salient pattern.

As another example of pattern distraction, I give you DNA.

My favorite morphological description of DNA: "the non-periodic crystal". It harnesses the strong self-organizing (but anti-information) properties that give rise to a crystal (in this case, an almost endless wound chain of identical and stable "double-helix" spiral twists) as a stable superstructure for that will carry the information (anti-crystal) bearing base-pairs at its axillary center. The crystal spiral holds and protects the integrity of the always-vulnerable low-entropy sequence that holds our genetic recipe… DNA's real structure of importance. Even so, we humans seem to be more attracted (like crows) to the simplicity of the simple and un-remarkable spiral crystal armature instead of the non-crystaline information the crystal armature makes possible!

The larger implication of our self-destructive crow-like attraction to simplicity is that we are romantic about the very things that don't matter and ignore-ant of the anti-crystal configurations that are complex and information rich… that are salient to the information we are and the information our information may yet create.

I suspect that our attraction to simplicity in pattern is an idiosyncratic after-effect of a salience detector within our thinking apparatus that is constantly looking for self-similarity. When computer scientists and logicians attempt to design compression schemes, they are looking for ways to algorithmically discover those sections or sequences of a set of information that are un-important to the overall structure… much of data is repetitive, if you can find these repetitions, patterns, you can reduce them to simple equations or pointers to prototypical modules that can be stored once and forever duplicated as filler. Obviously, these patters are compressible because they cary so little salient information.

While it is somewhat surprising that so much of an image, musical recording, even string of text, can, using fractal math, be detected as filler and deleted, the subsequent and predictable human reaction… that of honoring the trash simply because it is pretty, is to my mind, one of the most scary attributes of human proclivity. Fractals illustrate how much of nature's structure is non-salient, is the noise, the tailings of dissipation. That we would be enamored by the pattern of noise to such an extent that we ignore the real meat of information (that which is not pattern-able) is our potential downfall as a species.

A snail isn't trying to build spiral. A snail grows a shell that happens to be a spiral because that is THE ONLY SHAPE allowed in three dimensions that is both a cone (expanding tube) and dimensionally minimal of solid permanent material. The snail has better things to waste its limited energy on than the shape of its protective home. So it chooses the one shape that takes the least energy and most minimal construction algorithm to pull off. We dishonor the snail as a biological scheme by paying attention to the aspect of its survival that is the least interesting. That simplicity of that spiral shell is what should tell us not to pay attention to that aspect of its being or strategy.

But in this regard and others, we act as crows despite our 100 billion brain cells and the potential therein.

Sad.

Randall Reetz