COMPLEXITY METRIC

A Causal Debunking of the Libertarian Platform

2012-02-04T12:49:00.000-08:00

Note: The following is an excerpt, a single post, from my end of an ongoing discussion/debate with libertarians (full thread here).

Infrastructure doesn't scale down to the local level. Its whole-clothe scale is the entire reason for the need for infrastructure and the criteria by which it is categorized. You can't build infrastructure locally. You can't build a nation at the state level. That thing, that special sauce, that essence that determines the difference between nations is exactly that thing that can't be done at a scale below the scale of the whole nation. It doesn't matter how pissed off you are that you can't keep all of your income, that you should have to pay some of it back to the system that made it possible for your money to have value, your anger isn't going to change the causal reality of economics and infrastructure. There is a classic cartoon image in which a person is sitting on the very branch that he is furiously sawing through. The libertarian philosophy is perfectly illustrated by this cartoon. The whole libertarian position is anti-causal. It flips cause and effect to satisfy a childish tantrum of short sighted selfishness.

I had a friend in Santa Cruz who was obsessed with new age self help fads. We were walking along the ocean one day when she excitedly described a class she was taking at a local continuing education facility. The class was called "Change Your Personality By Changing Your Handwriting". After describing the class exercises, she said, "Oh my, I forgot who I was talking to… why aren't you attacking this whole idea?" I said, "I am thinking, just a second." And then I began… "OK, I've got it. Imagine you are driving your car down the highway and you reach down, tear away the plastic lens in front of the speedometer, grab the red needle, and pull it one way and then the other… what do you suppose will happen to your speed?"

And then I attempted to explain the difference between cause and effect. I tried to explain that in any system, each of the attributes of that system are part of a causal network – that some of these attributes are more cause and some more effect. I explained that, underlying any system, there is a hierarchy of influence, a linear cline on which all of the elements are arranged by their relative influence. In the system that is your car, the speedometer falls very much on the effect end of the influence hierarchy. The speedometer measures and reports the speed of the car. But the speedometer doesn't much effect the speed of the car.

All measurements require a physical linking between the measurer and the system being measured. And yes, measurement always effects the system being measured – the car will in fact change speeds when you drag the speedometer needle one way or the other. But this linking is so heavily weighted towards effect that this backwards linking causality, its effect on the car's speed, would be so slight that you would be hard pressed to build a mechanism sensitive and accurate enough to detect it. That is what makes a speedometer good at reporting. It is designed to be mostly effect and assert very little cause. If you want to cause the car to go faster or slower, the accelerator and break peddles are a far better choice as they were specifically designed to sit at the causal end of the car's cause and effect influence hierarchy.

While I am sure that it is true that statistical correlations can be found that link personality types with certain handwriting attributes, the link is certainly heavily weighted towards effect and away from cause. While handwriting might indeed loosely reflect personality, the conclusion that personality types are caused by handwriting differences fundamentally ignores all of the actual influences that add up to shape the personality of any individual human. That I would have to explain this fundamental aspect of any system to a grown adult with an IQ well above average says a lot about the causal influence hierarchy within the human brain. This basic "design" flaw results almost always in emotionality that supersedes rationality… the libertarian world view for instance.

So, yes, lets imagine a full implementation of the emotionally rich, and rationally poor libertarian platform. Without income taxes, you now have 100 dollars in your pocket where you previously had just 70. But without the infrastructure from which your dollars derive value, the infrastructure that 30 dollars in taxes plan, build, and maintain, you might as well not have any money at all. Without a nation-wide, world-leading infrastructure, the effective buying power of your 100 bucks is exactly zilch. Welcome to the Congo.

Randall Lee Reetz

Prediction Schemes: Classicism vs. Non-linear vs. Thermodynamics

2012-01-26T14:24:00.000-08:00

Thermodynamics and information theory are often grouped with classical dynamics. This is especially true where theory space is cleaved with quantum dynamics and other quote/unquote "non-deterministic" or "non-linear" theories on one side. But such classifications are problematic for several important reasons. Traditionally, the criteria of inclusion within the rubric "classical" has leaned heavily upon the concept of computation from knowledge of initial conditions. in Newtonian (and Relativistic) dynamics, knowing the initial state of a system allows one to calculate and thus predict the state of that system at any time in the future. Accuracy in prediction, from a classical perspective, is gated only by accuracy of knowledge of the original conditions of that system. Enter now, the strange world of quantum dynamics, where indeterminacy and sensitivity to observation turn classical calculations on their head. Non-clasical systems are systems in which determinism actually works against accuracy of prediction. The more you try to increase your knowledge of the initial conditions of a quantum situation, the less accurately you can predict that system's future. Much is made of the philosophical implications of observer "relativity" in an Einsteinium space/time model, but vantage-sensitivity is absolutely classical – the more you know about the initial conditions, the more accurate will be your relativistic predictions. In the quantum world, knowledge is itself, a cost of business attribute. In the quantum world, knowledge perturbs. In the quantum world, a system that seeks to know itself, is a system that is changed. In the quantum world, there are two types of systems, systems that are statistically perturbed, and systems that are locally perturbed. Meaning, you can measure (observe) aspects of a whole system without messing with that system, but should you want discrete knowledge of individual particles within that system, you must pay the price of a system that is forever thereafter disturbed. It is interesting how closely the empirically observed quantum world mimics the limits Kurt Godel placed on absolute knowledge. OK, let us now contrast thermodynamics, specifically the second law of thermodynamics, against both classical or deterministic dynamics and quantum indeterminacy. If one accepts that purpose of knowledge is prediction, is fidelity of calculation to actual future states, than both classical and non-linear theory are self-limitiing. Classical prediction is hampered by limits to the accuracy of observation of the initial state. Quantum prediction is limited by the way systems are perturbed by measurement, the more you know, the more you must include yourself into to prediction calculations, and the more said act is limited by Godel's caps on self-knowledge. One could say that classical prediction is dependent at base upon naiveté, and that quantum prediction is limited by knowledge itself. But what of the second law? The second law allows for absolute knowledge of the end state, of "heat death" or complete dissipation. Unlike all other forms of theoretical abstraction, the second law is absolutely agnostic to initial condition(s). You can use Newton's laws to look into the immediate future of a gravitationally bound system, but the same laws are meaningless in a system perturbed by other forces. Thermodynamic theory doesn't care what forces or materials are at play, it only cares about difference. In fact, thermodynamics doesn't know for the difference between material and force. The second law says that difference will always be less after any change in any system. The second law says that a change in any system will always result in the greatest possible reduction in difference. And importantly, the second law flips determinism on its head by providing perfect knowledge of the final state and doing so absolutely independent of any knowledge of initial conditions. Well that is certainly interesting, a theory that can predict the ultimate future independent of any past or present configuration, or, for that matter, any knowledge what so ever. What can be said of the quality or quantity of action that can be taken as result of this strange sort of knowledge? If success in competition can be linked to accuracy and capacity to predict, than what can be said of competitive success as a function of range of prediction? Imagine one could make and than order all possible predictions from most immediate to most long term. Comparing short-term against long-term predictions, which have the greatest impact on competitive advantage? If someone came into your office today and said, "I can say with absolute confidence that you will die as an artist in Copenhagen", how would such knowledge effect your future decisions and actions? How would absolute knowledge of your ultimate future effect your behavior? What if we were to compare the influence of such knowledge to short term knowledge of the same certainty? What if that same person came into your office and instead declared, "I have no knowledge of your ultimate fate, but I do know that you will not be able to fall asleep tonight". Would you be more (or less) likely to change or conform your plans or to take action based on short term predictions? There might be a tendency to ignore predictions that are far removed in time. One might reasonably think, "Even if I know that I will become an artist and eventually die in Copenhagen, I have a life to live until then, concentrating on long term eventualities interferes with my ability to successfully negotiate success in the short term, in the here and now. But it might also be reasonable to try to conform local goals to long term eventualities. One might eliminate actions that one feels will make it harder to plot a path towards know eventualities. Or, one might take risks they would not otherwise have taken. If I know I will die in Copenhagen, I might as well go base jumping in the Andes or climb Everest sans bottled oxygen. Surely, the heat death of the universe is an eventuality of much greater philosophical remove. What's more, evolution, as a process, seems to work just fine in the absence of any knowledge of eventualities. Can one make an argument that knowledge of universal eventuality gains its owner any special form of evolutionary advantage? Lets pit two entities against each other, one knows of heat death, the other doesn't. Which has the evolutionary advantage?

Randall Lee Reetz, January 26, 2012

Evolution: Refinement vs. Prediction

2011-12-22T10:25:00.000-08:00

Evolution: The changes that will have the greatest effect on the longest future... and what it takes for those changes to survive the present long enough to make it there.

That sentence describes evolution better than any attributed to Darwin. The refinement-on-a-scheme process Darwin described is only the metabolism, the power plant, that fuels evolution. "Fitness" in the present is the necessary evil, not the goal of evolution. Evolution is not the struggle for the right beak shape. That kind of refinement-on-a-scheme only gets you the biggest slice of the local pie. Refinement makes for a powerful now, a perquisite for a powerful then, but it is self limiting. Resources spent adapting to the now are resources not available for adaptation to the future. It is ironic to have to utter these words, but evolution isn't about the here and now. No, evolution is about the biggest there and the longest then. If your purpose is to facilitate the future, you are in the prediction business. So let's re-write our definition.

Evolution: The development and selection of better and better prediction schemes.

However, a prediction scheme is useless unless it can get you from what works now to what will work then. What ensues, is a tug-of-war, a tight-wire-walk, in which an evolution scheme must support both refinement in the now and prediction of the future. The causal implications are complex. Refinement is antithetical to prediction. While the finch is involved in the struggle for a better beak, the larger sphere of resources, the whole of the universe over the longest spans of the future, go ignored and un-tapped. You might argue that a bird doesn't have the capacity to understand the universe or the concept of resources or the maximization of exploitation to which all evolving systems must ultimately compete, and you would be, after a fashion, correct. That is the magic of evolution, the evolving thing doesn't need to understand the process it is engaged in. So long as there are enough individuals and these individuals are each even just slightly different from each other, selection will direct change towards better and better survival and better and better prediction schemes. Changes that promote survival are the easy part. And yet, even though it often works against survival in the present, the capacity to predict will win in the long run.

Darwin can't be faulted for not seeing the big picture. He had to lay down the ground work and the groundwork in evolution is survival. Beak shape is an easily to observe population variance in finch morphology. But beak shape variation is no different than leg length variation, or protean variation, or cognitive and behavioral variation. Critics of evolution in general or Darwin argue that he never actually explained "…the origin of species". Implied in that challenge is a description of a process that results in qualitative changes; animals vs. plants for instance. And this is because he chose to explain his theory through the more overt and obvious adaptations that fall into the category of refinement or fitness in the present. The larger picture of evolution must be told as a conflict between refinement and prediction and that would have been an impossible sell to an already suspicious victorian audience.

Randall Lee Reetz

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

2011-12-13T12:03:00.000-08:00

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…

2011-11-17T10:41:00.001-08:00

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

Causalism

2011-05-07T20:16:00.001-07:00

Though I have been writing about "causality" for years, I continued to label myself an atheist. I really thought the label fit, but that was before I attended to a few atheism events and talks and found that atheists are not, as I had understood, interested in rational thought. The atheists I have met are simply and aggressively apposed to religion. They have an axe to grind, are pathologically obsessed with, focused upon, and have a general need to work bad juju against – religion. The single minded obsessive combativeness exhibited by the atheists that I have met, seems, well, in a word – religious.

Of course I will take responsibility for my mistake, my assumption, it is right there in the word: "atheist", a-theist, anti-theist, against theism. And though I am not a believer, my disinterest in belief does not define my self or my thoughts or more specifically, the way I choose to think things through. Nobody who likes the color red describes this preference as anti-green.

The word "causality" describes a world view in which every system exists as a hierarchy of cause and effect. Even though dictionaries don't yet list the word – a "causalist" is a person who "believes" that all structure and action is the result of physical causality. That describes my way of thinking perfectly.

I am a causalist!

There, I said it. It is now a word. That is what makes the english language so dynamic and alive. If you need a word. Go out and build one. In this case, anyone who understands the word causal will immediately understand the word causalist. 'Wish I could say the same of my spell checker.

I believe that the universe is what it is and acts like it acts solely as a result of physical properties and the way these properties are effected by and effect each-other. No back doors. No end-arounds. No special cases. No miracles. No exceptions. No preferential treatment. Simple. Expectable. Demonstrable. Regular. I believe that thoughts are built of atoms, not the other way around. That atoms and their properties effect thought but that thoughts can't effect the basic fundamental properties of atoms.

Causality is a description of a system as a hierarchy of the things that influence it. Causality strongly implies an asymmetry between cause and effect. A causal system is a system in which some parts and attributes have more influence over the shape and behavior of that system than do others (which are more effect).

A causalist assumes that all systems exist as the result of a history and that this history defines a linearity of construction – first this happened, then this, and finally this. A causalist assumes that this history of a system, exposes a hierarchy of the energies that were required to built it. The most energetic processes shaped the earliest subsystems, and the most recent additions were laid down in much less energetic environments. This makes for stable structures – strongly associated foundations upon which more delicate subsystems are layered.

And, low and behold, when we pick systems apart, we always find this hierarchical strata of causally deposited layers. Always! No exceptions have ever been found.

The other key aspect to the causalist's cosmology is the fact that earlier systems are more similar and systems added later are more diverse. This means that everything shares and is built upon the same past. So no matter if you have gills or feathers, hands or tentacles, eyes or echo-location – you will all be built of cells and these cells, muscle or neuron, blood cell or phagocyte will all be made of atoms and these atoms helium or hydrogen, led or plutonium will always be made of protons, neutrons and electrons, etc. etc.

A world or universe built up from ever more shared and similar parts is a universe that can be known. It is a stable universe that has expectable patterns that exist within the boundaries of limits defined by their own causally stacked history. Everything shares the same history. Everything is built of the same history. Though the present may look diverse and confusing, further inquiry will always reveal patterns and similarities at base, shared by everything. Exceptions and difference is always an aspect of the surface or most recent manifestations of evolution. The base gets more and more similar the deeper or further back you look.

This regularity is exactly why spiritualists and the religious have always been apposed to science and the causal view of reality. It doesn't allow exceptions. You can't win the race cause you prayed longer or to the right god. You can only win the race if you have the physicality and the emotional drive to run harder than everyone else. There are no exceptions. There are no special cases. There is no favoritism. There is no OZ pulling levers. Nobody and no thing to assuage towards your interests.

We know that adding heat to a gas causes it to expand. We know that compressing a gas causes it to get hotter. We know the exact ratio between heat and pressure or volume. With this ratio we can predict the exact changes that will result when we add energy or change the volume of a given amount of gas. It always works the way the math says it should. But of course the same can not be said for the spiritual arts. In fact. There has never been an event that has been shown to have been effected by prayer or thinking (no matter how concentrated, repeated, or "conscious"). Never once has the temperature of a gas or anything else been effected by anything spiritual or religious. This is not just true of gasses and heat. It is true of everything we can measure. We know the entire electromagnetic spectrum. We understand and have defined the parameters that show why this spectrum is bounded on both the cold and the energetic end. We know how gravity is effected by energy, time and distance. We know how quanta effect other quanta. And in no system, caused by no dynamics, have we ever encountered any behavior that can not be explained by simple causality of the things effecting those systems.

It is easy to see why causality would disturb the anxious. There is no way to play a causal system. No way to gain advantage. No free lunch. No favoritism. No exceptions. No para-normal. No meta-physics. No magic. No luck. Just the awesome beauty and incomprehensible complexity that can't help but happen in a universe this big and this full of energy and stuff with this much time summing into an almost infinite number interactions and the constructs can survive. In a causal universe, you get fit by working out – not by chanting mantras. You live longer by taking care of your body and your mind, not by praying for longevity. You gain advantage in sports, business, romance, academia, and culture, by understanding the causal influences effecting these systems, not by sleeping under a pyramid or praying to a 10 armed blue goddess or a sandal wearing guy nailed to a couple of wood beams. You gain knowledge through measurement and building theories that abstract the greatest domain of measurements – not by listening reverently to some guy in a robe who slickly explains away your loneliness and fear of death with a 24 voice choir and 60 foot pipe organ as backup.

It may in fact be true that the human brain has evolved into a configuration that demands religious and spiritual thoughts and that these thoughts can result in a better sense of well-being and that the resulting sense of inner peace gives rise to physical benefits, but this itself is a causal (if Byzantine) system. But any causal assessment of the human penchant for religious and spiritual thought would certainly give it a low score for effectiveness and a high score for self-delusion. Thoughts that make you feel better aren't necessarily the thoughts that increase your knowledge of yourself or the universe. This rift between reality and what our minds would like reality to be is the single most dangerous side effect of evolving a great big layer of grey matter over the top of our lizard brain within. It is important to remember that the lizard brain, an emotion-to-action processing center, is still very much in charge of everything we do. This is non-negotiable. It is true because of physical wiring, not philosophy. Adding to a sober assessment of our scary neural architecture is the fact that the inner brain, the old brain, the brain in charge, isn't sophisticated enough to understand any of the wonderfully sophisticated products (reason, logic, abstract mapping, systems modeling) our more recently acquired layers are able to compute. Be you Einstein or Leonardo, Shakespeare or Confucius, Newton or Feynman, your inner brain is still as dumb as a lizard, and it, unfortunately, is both blind to your brilliance, and directing the actions you take.

A causalist isn't as depressed by this seemingly hopeless understanding as one might expect. A causalist just accepts reality and looks for solutions that work with and are informed by it. If humans have great big thinking machines that are hard to hear above the ruckus and clatter of emotions, the challenge is to build cultural solutions that protect and automate higher order knowledge from the vagrancies of low level emotions. The playing field shifts with this shift in perspectives. Instead of looking for solutions within the arena of emotional thought (meditation, mood music, a harmonic convergence, global conciseness, etc.) the cuasalist, looks for solutions outside of the lizard brain, looks for solutions that accept the lizard brain but work to lessen its control over policy and society. A causalist looks to the infrastructure. A causalist has noticed that people act more constructive when their environment takes care of the simple needs of the lizard brain. A causalist has noticed that clean running water at every faucet, enough food, reasonable shelter, and reliable stability make people with the same lizard brain end up acting more like their grey matter ideas and less like a lizard. No amount of prayer or philosophy or yoga will yield the same productivity improvements and cultural growth as a reliable and supportive infrastructure.

Take the time to look at the statistics that compare a culture's confidence in its infrastructure and its per labor hour productivity or its crime rate. Then try to find a better predictor of a culture's ability to build towards greater and greater progress of knowledge and opportunity. Confidence doesn't build an infrastructure, infrastructure builds confidence. Those of us confident enough to see this hierarchy for what it is must work constantly and vigorously against the grain. We must build the infrastructure that will produce in tomorrow's masses the confidence we are lucky enough to feel today.

It is way way way cheaper to run clean water and nutritious food into every home than it is to deal with the chaos that ALWAYS results when people must live with the fear of thirst and hunger. Going to church for an hour a week isn't ever going to have the same effect on productivity and stability. Even the religious would surely rather pray for more interesting and complex goals than a bowl of rice and clear water.

Accepting the weird irrationality of the human thinking and emotional system doesn't mean that you have to be irrational about your acceptance of it or how you choose to go about building towards a better future.

Randall Lee Reetz (a causalist!)

Compression as Intelligence

2011-03-27T13:02:00.000-07:00

Let me take a stab at defending compression as equivalent to intelligence.

Standard string compression (LZW, etc.) works by understanding and then exploiting the sequencing rules that result in the redundancy built into most (all?) languages and communication protocols.

Compression is necessary in any storage/retrieval/manipulation system for the simple reason that all systems are finite. Any library, any hard drive, any computer memory… all finite. If working with primary in-situ environments was as efficient as working with maps or abstractions we would never have to go through the trouble of making maps or abstracting and filtering and representing.

It might seem sarcastic even to say it, but a universe is larger than a brain.

You have however stumbled upon an interesting insight. Where exactly is intelligence? In classic Shannon information theory, and the communication metrics (signal/noise ratio) upon which it is based, information is a duality where data and cypher are interlocked. In this model, you can reduce the size of your content, but only if you increase the size (or capacity) of the cypher. Want to reduce the complexity of the cypher, well you are forced to accept the fact that your content will grow in size or complexity. No free lunch!

In order to build a more robust cypher, one has to generalize in order find salience (the difference that make a difference) in a greater and greater chunk of the universe. It is one thing to build an data crawler for a single content protocol, quite another to build a domain and protocol independent data crawler. It is one thing to build hash trees based on word or token frequency and quite another to build them based on causal semantics (not how the words are sequenced, but how the concepts they refer to are graphed.

I think the main trouble you are having with this compression = intelligence concept has to do with a limited mapping of the word "compression".

Lets say you are driving and need to know which way to turn as you approach a fork in the road. If you are equipped with some sort of mental abstraction of the territory ahead, or on a map, you can choose based on the information encoded into these representations. But what if you didn't? What if you could not build a map, either on paper, or in your head. Then you would be forced to drive up each fork in turn. In fact, had you no abstraction device, you would have to do this continually as you would not be able to remember the first road by the time you took the second.

What if you had to traverse every road in every city you came to just to decide which road you were meant to take in the first place? What if the universe it self was the best map you could ever build of the universe? Surely you can see that a map is a form of compression.

But lets say that your brain can never be big enough to build a perfect map of every part of the universe important to you. Lets imagine that the map-building map you build in order to create mental memories of roads and cities is ineffective at building maps of biological knowledge or physics or the names and faces of your friends. You will have to go about building unique map builders for each domain of knowledge important to you. Eventually, every cubic centimeter of your brain will be full of domain-specific map making algorithms. No room for the maps!

What you need to build sited is a universal map builder. A map builder that works just as well for topological territory as it does for concepts and lists and complex n-dimensional pattern-scapes.

Do so and you will end up with the ultimate compression algorithm!

But your point about where the intelligence lies is important. I haven't read the rules for the contest you sight, but if I were to design such a contest, I would insist that the final byte count of each entrants' data also include the byte count of the code necessary to unpack it.

I realize that even this doesn't go far enough. You are correctly asserting that most of the intelligence is in the human minds that build these compression algorithms in the first place.

How would you go about designing a contest that correctly or more accurately measures the full complexity of both cypher and the content it interprets?

But before you do, you should take the time to realize that a compression algorithm becomes a smaller and smaller component of the total complexity metric the more often it is used. How many trillions of trillions of bytes have been trimmed from the global data tree over the lifespan of use of MPEG or JPEG on video and images? Even if you factor in a robust calculation of the quantum wave space inhabited by the humans brains that created these protocols it is plain to see that use continues to diminish the complexity contribution of the cypher no matter how complex.

Now what do you think?

Randall Lee Reetz

Evolution: Pendulum Dance Between Laws of Thermodynamics

2010-09-16T17:10:00.000-07:00

For years, I have pursued a purely thermodynamic definition of evolution.

My reasoning is informed by the observation that change is independent of domain, process, or the physical laws and behaviors upon which a system is based. As the science of thermodynamics has itself matured (evolved), the boundaries of its applicable domain have expanded far beyond its original focus on heat. It is generally accepted that the laws of thermodynamics apply to ANY system in which change occurs, that the laws of thermodynamics are agnostic to energy type or form. Furthermore, scientists studying information/communication independently discovered laws that match almost perfectly, the laws of thermodynamics. This mirroring of domains has thrilled logicians, physicists, mathematicians, and cosmologists who are no more and more convinced that information (configuration) and energy are symmetric with respect to change over time.

Even conservatively, the implications of this symmetry are nothing short of profound. If true, it suggests that one can, for instance, calculate the amount of information it would take to get a certain mass to the moon and back, and it means that one can calculate how much energy it would take to compute the design a moon rocket. It means that the much vaulted "E" in Einstein's Relativity equation can be exchanged with an "I" for information (with valid results). It means, at some level, that information is relativistic and that gravity works as a metric of information. Same goes for the rules and equations that govern quantum dynamics.

And this from an eyes-wide-open anti-post modernist!

At any event, the symmetric relationship between energy and information (at least with regard to change) provides a singular foundation for all of physics, and even perhaps for all of ANY possible physical system (equally applicable to other universes with other rules).

It would seem that thermodynamics would provide a more than solid base from which to define the process that allows for, limits, and possibly demands the (localized) accumulation of complexity – evolution!

The Zeroth and First Laws of Thermodynamics work to shape and parameterize action. Given the particular configuration immediately prior they insure that the next action is always and only the set of those possible actions that together will expend the most energy. In colloquial terms, things fall down and things fall down as fast and as completely as is possible. Falling down, is a euphemism for the process of seeking of equilibrium. If the forces attracting two objects is greater than the forces keeping them apart, they will fall together. If the forces keeping them apart is greater than the forces attracting them, they will fall apart. Falling down reduces a system to a more stable state – a state in which less force is pushing because some force was released. Falling down catalyzes the maximum release of energy and results in a configuration of minimum tension.

The Second Law of thermodynamics dictates that all action results in a degradation of energy, or configurationally speaking, a reduction in density or organizational complexity. Over time the universe becomes cooler, more spread out, and less ordered.

The falling down dictated by the the zeroth and first law result in particular types of chunking determined by a combination of the materials available and the energy reduced. About a million years after the big bang, the energy and pressures of the big bang had dissipated such that the attractive forces effecting sub-atomic particles were finally stronger than the forces all around them. The result was a precipitation of matter as hydrogen and helium atoms in plasma. After a few hundred million years, the mass in these gasses exerted more attractive energy than the much cooler and less dense universe, and precipitated into clumps that became stars. As the fusion cascade in these first stars radiated their energy out into an expanding and cooling universe, the attractive force of gravity within became greater than the repulsive forces of nuclear reaction and the starts imploded upon themselves with such force as to expel their electrons and precipitate again into all of the other elements. These heavy elements were drawn by gravity again into a second generation of stars and planets of which earth is but one lonely example.

You will have noticed that each precipitatory event in our cosmological history resulted in a new aggregate class – energy, sub atomic particles, light atoms, stars, heavy atoms, stars and planets, life, sentience, language, culture, science, etc). The first two laws of thermodynamics dictate the way previously created aggregate objects are combined to form new classes of aggregate objects. The second law guarantees as a result of the most contemporary precipitation event, a coincidental lowering of energy/configurational density which allows still weaker forces to cause aggregates in the next precipitatory phase.

If you still aren't following me, it is probably because I have not been clear about the fact that the lower environmental energy density that is the result of each precipitatory cycle optimizes the resulting environmental conditions to the effects of the next weaker force or the next less stable configuration.

For instance, the very act of the strong force to create atomic nuclei, lowers the temperature and pressure to such an extent that the weak force and the electromagnetic force can now overcome environmental chaos and cause the formation of atoms in the next precipitatory event.

This ratcheted dance between the laws of thermodynamics is the why of evolution, and results in the layered grammars that sometimes or at least potentially describe ever greater stacked complexities that led to life and us and what might come as a result of our self same actions as the dance continues.

Stepping back to the basic foundation of causality, it is important to be re-reminded that a configuration of any kind always represents the maximum allowable complexity. In recent years, much has been made of the black hole cosmologies that define the event horizon as the minimum allowable area on which all of the information within the black hole can be written as a one bit thick surface membrane of a sphere. The actual physical mechanical reason that this black hole event horizon membrane can be described as a lossless "holographic" recording or description or compression of the full contents of the black hole is complex and binds quantum and relativistic physics. Quantum because the energies are so great structure is reduced to the structural granularity of basic quantum bits. Relativistic because at this maximally allowable density everything passing the event horizon has reached the speed of light, freezing time itself… the event horizon effectively holds an informational record of everything that has passed.

The interesting and I think salient aspect of an event horizon is that is always exactly as big as it needs to be to hold all of the bits that have passed through it. As the black whole attracts and eats up any mass unlucky enough to be within its considerable influence, the event horizon grows by exactly the bits necessary to describe it at the quantum level.

The cosmological community (including Sir Steven Hawking), was at first shocked by the sublime elegance of this theory and then by the audacious and unavoidable implication that black holes, like everything else, are beholding to the laws of thermodynamics. The theory predicts black hole evaporation! Seems black holes, like everything else, are entropically bound. There is no free lunch. The collapse of matter into a black hole results in a degradation of energy and informational configuration, the self same entropy that demands that heat leak from a steam engine, demands that black holes will evaporate and that eventually, when this rate of evaporation exceeds the rate of stuff falling into it, a black whole will get smaller and ultimately, poof, be gone.

This is heady stuff. The biggest and baddest things in the universe are limited! But to me, the most profound aspect of this knowledge is not that event horizons can be describes as maximal causal configurations, but that we are shocked by this! All systems are, at each moment, the maximal allowable configuration by which those forces and those materials can be arranged. If they could be arranged any tighter, they would have already collapsed into that configuration.

To say this is to understand that time is not separable from configuration. As Einstein showed, time is physically dependent upon and bounded by the interaction of mass, distance, energy, and change. Cosmologists use limits to understand the universe. The maximal warpage of space-time caused by a black hole's density effectively flattens the allowable granular complexity of the configurational grammar to binary bits held in the minimally allowable physical embodiment. But, lower energy configurations, configurations like dogs, planets, and the mechanism by which I am attempting to explain this concept, are bounded and limited by the exact same causal rules.

The difference between a black hole horizon and an idea? Well it has to do with the stacking of grammatical systems (quarks, sub atomic particles, atoms, molecules, proteans, cells, organs, bodies, culture, language, etc.) that allows for complexities greater than the binary bits, the only stuff allowed to pass through an event horizon. But these stacked grammars that allow us to be us are every bit as restricted to the same maximally allowable configuration rule that minimizes the size of a black hole's event horizon. In a system configured by a stacked grammar, the minimum complexity rule is enforced at the transition boundary between each two grammatical layers.

Things fall, but only as fast as the stacked grammars that govern causal reality will allow. This isn't a metaphor, the speed of diffusion, of degradation, of falling down, is always and in all situations, maxed-out. The exact same physical topology that bounds the size of the a black hole event horizon contributes to the causal binding effecting the rate at which any system can change. This is because at the deepest causal layer, all systems are bound by relativity and quantum dynamics. The grammatical layers built successively on top of this lower binding only serve to further influence entropy's relentless race towards heat death.

[to be continued]

Randall Reetz

The Big Arrow: What Matters and Why

2010-09-02T15:18:00.000-07:00

hierarchy of influence
complexity handling capacity as evolutionary fitness metric
decentralized autonomous node computation topology
localized least energy optimization vs. topology range-finding and exploration for long range optimization
compression as computational grand-attractor
causally restricted abstraction space
causally calibrated abstraction space
self-optimized causal semantics
generalize and subsume schemes
self optimized stacked grammars
causally restricted language
universal simulation environment
context-optimized language generators
context-optimized language interpreters
entropy maximization schemes
balancing local vs. universal evolution schemes
processing economics
network nodes vs. software objects
networks vs. graphs…
generalize and subsume

These are the concepts that bubble up when I ask myself, What matters? and, What matters the most?". I ask these questions over and over again. Have for some 40 years. You can get by not asking these questions, might even thrive, but only because others not so indifferent, have, do, and will ask.

What you are, what we all are, what we will become, and what will come after us, is more the result of the thoughts and actions taken by the few individuals, consciously or not, who have honored these questions, and honored them above all others. To be sure, survival, at least in the present and local, is not dependent upon asking the big questions. In fact, as far as the individual is concerned, asking big questions, almost certainly diminishes fitness and reduces the probability of survival.

Much print is devoted to the question of whether and how socially benevolent behavior evolves . How can moral behavior spread through the gene or meme pool when, at the granularity of the individual, moral behavior frequently allows other individuals to take more than their fair share?

But the same issue is not so controversial or surprising if we shift our focus to competing motivations within a single individual. How do we ever learn to think long-term or wide-focus thoughts when short-term, narrow-focus thoughts are more likely to increase the likelihood of immediate survival?

Weirder still, there is obviously plenty of evolutionary evidence that wide-focus problem solving has bridged routs to new domains. Aquatic animals have become land animals and vice versa. Single-celled animals have become multi-celled animals (presumably though less intuitively, multi-celled animals have evolved the other way, towards single celled animals). Chemistry has become biology and biology catalyzes chemistry. And unique to our temporal neighborhood, biology has sprouted culture that is well on its way towards sprouting non-biological life… the first "intentional" life!

But domain-jumping doesn't sit well with traditional views of evolution. Evolutionists tend to study biology from the perspective of a particular environmental constraint or set of stable constraints. Within the (self-imposed) bubble of these artificially bounded steady-state environments, evolution certainly seems to be a process of refinement seeking. In thermodynamics we describe this class of behavior; "seeking the fall line". In your prototypical energy topology, where peaks mean high energy and chaos and valleys equate equilibrium low energy stability, refinement evolution selects for processes that find their way to the nadir of the local-most valley. When sliding down the (local) least-energy fall line, there is but this one possible result.

The problem with refinement (as an explanation of evolution) is that it describes a sub-type of change that is peculiarly adverse to the kinds of novelty and acceleration away from stasis that one actually sees in evolving systems. Refinement in point of fact is the very reverse of sustainable change. Refinement always seeks a limit. Becoming, for instance, the best swimmer in the sea, sort of insures that you are so specialized that you will have a hard time changing into anything else but a swimmer. Refinement sets you up to be stage, environment, ground (the past)… for other things, the things that are more directed towards the forms of evolutionary change that will define the foreground, the action, the object, (the future).

Limit seeking schemes are schemes in which change decelerates over time. That doesn't sound like a formula that fits the upward accelerating curve of evolution.

This would be a good time to introduce a term I use all of the time, without which, I believe it is impossible to see evolution for what it really is. The term is "hierarchy of influence". A hierarchy of influence is a cline, a stack, a pyramid, that relates each of the factors effecting a system according to the degree to which each will effect the the behavior, output, eventual state, or direction of the system of which each is a part.

I know it isn't politically correct to suggest that some parts of a system are more important than others, so I will just say that some factors of a system will have a greater effect over the future than will others. A hierarchy of influence is an ontology of sorts, or more accurately, a ranking. On the bottom of the stack, you will have those sub-systems or parts or actors that have an effect on almost everything else in the system, and on top you will have those parts that are more the result of or subservient to the rest of the system. If you aren't comfortable with that order, just flip it over! Either way you map it, hierarchy of influence is a powerful tool for the understanding of systems and change.

So, let's look at evolutionary systems through the hierarchy of influence lens. Here as before, we can apply this new lens locally or globally. What leads towards success locally is different than what leads to success globally. As the field of view narrows, a hierarchy of influence favors factors that support refinement. Process at larger and longer scopes support influencers that reach out side of current domains, influencers that seek a universal understanding of all domains, of domain in general, of change itself, and finally, of the very reason for change, for and understanding of the end game and how best to get there.

Now lets apply the hierarchy of influence filter to the super-system we've just described, the system composed of both localized hierarchies of influence and universal hierarchies of influence. In any such super-system it should be clear that the local refinement leaning hierarchies will be demoted to the realm of effectors in reference to deep and wide long-range oriented hierarchies of influence.

Ecologists and Population Biologists are keen to point to the fact that most of this earth's biomass comes in the form of single celled animals and plants. Absolutely true. It is also true that most of the mass and energy in our Solar System is rather unimpressively ordered hydrogen, helium and a smattering of lithium. But the future of biology, of complexity, even of mass and energy is much more likely to be sensitive to complex systems than the simple ones upon which they feed.

But before we throw out "refinement" as a category, let me posit a kind of refinement that is a good candidate for the fitness function or filter we see in evolving systems, systems that get better and better and solving more and more diverse problems at a faster and faster rate.

What if we were to re-cast the concept of refinement to mean the refinement of refinement itself? In stead of refining a particular solution space, we think of refinement in its most general and universal form, a refinement of the definition of refinement. In doing so, we tip the traditional view of evolution on its head. Animals, individuals, species, film of every sort become the environment, the conditions, the topology as background as tool as expendable media for the refinement of the ultimate fitness metric.

I must step in now, interrupt my self, and state the obvious even if the obvious might throw a huge wrench in the logical works of this thesis.

The distinction I have been outlining, between refinement and domain jumping suggests or could lead some readers to think that I am suggesting that domain jumping offers some form of escape from the laws of thermodynamics. I have suggested that refinement evolution simply seeks the least energy fall line. No problem here. But by contrasting refinement against domain jumping, the reader might be lead to believe that I am suggesting a way around physics, a free lunch, some sort of evolutionary daemon that does what Maxwell's couldn't. I am not! Only the next action that takes the least energy can happen next.… no exceptions. Period. Domain jumping must therefore, at every moment and in every context, obey the laws of thermodynamics.

Now, it is relatively easy to see how refinement evolution meets these least-energy constraints, but how is it that domain jumping could ever happen? How would any action ever allow ridge-climbing escape from any concave depression in any energy topology?

Before I continue along this vein of logic, I should probably jump back a pace and clarify what I mean when I say "energy topology". An energy topology is a graphical depiction of the forces acting upon a region of space. Some energy topologies are almost identical to real world space. The undulating surface of the earth under our feet is, at least with regard to gravity, equivalent to the energy topology that restricts motion across its surface. If I am standing on the side of a mountain and moving 1 foot to my left means I will have to haul my body up half a foot vertically, and traversing 1 foot to the right would allow me instead to fall half a foot, than to slope of the ground is a perfect analog of the energy topology with respect to gravity. Left to the whims of time and chance, the energy topology I just described would make it far more likely that I would eventually end up more to my right (lower) than to my left (higher). This is because I would have to use energy to move up the mountain and could actually access energy by moving down the mountain.

Of course there are less obvious energy topologies, energy topologies that do not map to actual terrain. With respect say to choosing a religious belief the energy topology heavily reflects the beliefs already held by one's emendate family, cultural heritage, and other factors. Choice that differs radically from local norms will require lots more energy, than will conforming. If one were to plot the energy topology necessary to choose to become Muslim for instance, a child in a museum family would stand on top of a steep hill, and a child born to a Christian family would stand at the bottom of a deep pit. Energy topologies offer wonderfully obvious illustrations of the forces effecting evolving systems.

Each object or system to be examined acts according to the sum of many energy effectors. Each of these effectors (physical terrain, social obstructions/accelerators, on-board energy reserves and conversion rates, environmentally accessible resources, etc.) can be plotted separately as an energy topology, but causality is the result of the sum of all energy topologies effecting an object of system. To illustrate, lets now combine the above two examples. Lets say that the person on the mountainside, is in the process of plotting their own religious future. To the right the physical mountain rises, to the left it falls into a valley. The person standing there is from the Christian village in the valley below. That person is philosophically attracted to the Muslim faith. But to learn more, they will have to travel up the mountain to a Muslim village a thousand feet higher. In this case, the energy necessary to fulfill their philosophical desire will require them to haul their body up the mountain. And because doing so will also incur the costs associated with going against cultural norms. Obviously, both topologies must be summed in order to compute the likelihood of both possible choices. As I am sure you are realizing, the philosophical leaning of our actor can also be represented by an energy topology. This to must be summed to produce the aggregate energy topology in which our subject must act.

But none of these topologies explain hill climbing. For that we need to compose yet another energy topology, a topology that expresses the energy held as reserve within the individual actor.

So why ask these questions? If natural selection asks them down at the DNA level, and across the vast landscape that is evolutionary time, why should we bother asking them again?

Dimensionality and Postmodern Self-Cannibalism

2010-08-20T09:24:00.000-07:00

"Parenchyma" and "stroma" – two important words in the fight against ambiguity in any discussion of complex subject matter.

Both are medical lexicon and specify the difference between that part of a system (physical organ) that is (chemically) re-active ("parenchyma") and the part of the same system that is (connective tissue) structure ("stroma").

Of course it is true that structure both indicates and precipitates behavior. Equally, activity influences and predicts structure. So, again, things are not so simple as could be hoped. But words like these allow anchoring in critical discussion.

If one can substitute the much more common words "active" and "structural", why bother further confusing this issue with the introduction of the less common and harder to pronounce "parenchyma" and "stroma"?

Well, because understanding is strengthened through multiple contextual mappings. The larger and more varied the link graph, the more obvious become the differences between similar and potentially ambiguous topics or the signs we use as reference.

Also, uniquely, these two words signify the classic subject/object, object/ground, mind/body, I/others, specific/general, instance/class ambiguity in information, language, communication, computation… and existence.

The post modern position, an argument in reaction (over reaction) to the modern or classical "reductionist" (their word) world view is that hierarchical relationships (the kind that would result in a definable difference between a thing and the larger thing of which it is a part) do not in fact exist. The post-modernists present as absolute, that all relationships are "relative" (their word), because they say there is no reliable place to stand by which to judge hierarchy, that relationships are inherently biased to the observer.

What is the baby? What is the bathwater? The postmodernists, frustrated and angry, did King Solomon proud and threw them both out.

If there is anything of use to be learned from this mess it won't come from the (supposedly) blind "all" of classical thinking, or the fruitless "nothing" of the post modernists. I will half agree that relationship is vantage dependent (the answer you get back from the question, "Are you my mother?" depends on who is asking), but this dependence isn't purely local. Vantage can be retooled such that it is, as are spacial dimensions, something that can apply universally at all times and all places at once. By this gestalt, vantage is defined ubiquitously, ridding the hopelessly circular grounding problem at the center of the postmodern argument. When vantage is defined as dimension, it applies equally to all objects. You can switch dimensions at will and not loose the absolute and hierarchical relationships the classicists rightfully found so important.

Yes, the postmodernist (re-invention of the) word "relative" was awkwardly stolen (rather ignorantly) from Einstein. The difference, Einstein made the world more measurable by showing how energy and space-time are transmutable and self-limiting. The postmodernist's naive re-appropriation of Einstein's empirically derived authority, does the opposite – making it impossible to compare anything, ever. The irony here is profound. The postmodernists first stand upon the authority acquired through carful and causal measurement, then they say such measurement isn't possible!

God help the human race.

By the way, if you look carefully at Einstein's two papers on Relativity, you will see the underpinnings of the shiftable but universal vantage that a dimensional grounding provides. There are rules. 1. A dimension must apply to everything and through all time. 2. You can switch dimensional vantage at any time, but 3. You can only compare two things if you compare them within the context of the same dimensional vantage.

Is an attribute a dimension? No. An attribute situates an object in reference to a dimension. An attribute is a measurement of an object according to a property shared by all such objects in that dimension. A property is measurable for a class of objects as a result of the rules or grammar or physics that define a dimension.

The absolute causal hierarchy made all the more impenetrable by Quantum and Relativistic theory makes the postmodern "hard relativist" tantrum all the more ridiculous – especially in light of the fact that postmodernists constantly turn to these twin pillars of physical theory as support of their position. The fatal logical mistake here is the misrepresentation of a property ("relative vantage") as a dimension (rules that provide a stable base from which to define properties – in this case, the novelty of experience guaranteed by the first[?] law of causality: that no two bodies can occupy the same space at the same time).

Randall

Probability Chip – From MIT Spin-Off Lyric Semiconductor

2010-08-17T20:56:00.000-07:00

Photo: Rob Brown

A Chip That Digests Data and Calculates the Odds (New York Times, Aug, 17, 2010) and the Lyric Semiconductor company web page Probability Processor: GP5 (General-Purpose Programmable Probability Processing Platform). Looks like a variation on analog processing accessed within a digital framework. And here is an article from GreenTech Can 18th-Century Math Radically Curb Computer Power? which explains the chip in reference to Thomas Bayes and error correction. The crossover between error correction and compression is profound. Remember; intelligence = compression.

Randall

Old-School AI and Computer Generated Art

2010-08-14T22:50:00.000-07:00

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

The Separation of Church and Labor

2010-08-09T18:36:00.000-07:00

The always entertaining (habitually entertaining?) Jaron Lanier (Rasta-haired VR guru) wrote this opinion editorial piece for the New York Times "The First Church of Robotics" which deals with the inevitable hubris-spiral as humans react to the ever quickening pace of development in robotics and AI. Jaron is always a bit of a fear monger – anything for a show – but he leaves lots of fun emotional/societal/technology nuggets to snatch up and digest.

Lanier sets the stage:

Consider too the act of scanning a book into digital form. The historian George Dyson has written that a Google engineer once said to him: “We are not scanning all those books to be read by people. We are scanning them to be read by an A.I.” While we have yet to see how Google’s book scanning will play out, a machine-centric vision of the project might encourage software that treats books as grist for the mill, decontextualized snippets in one big database, rather than separate expressions from individual writers. In this approach, the contents of books would be atomized into bits of information to be aggregated, and the authors themselves, the feeling of their voices, their differing perspectives, would be lost.

After bemoaning the loss of human trust in human decisions (Lanier says we risk this every time we trust the advise of recommendation engines like Pandora and Amazon), he discusses the tendency amongst AI and Robotics enthusiasts to replace traditional religious notions of transcendence and immortality with the supposed rapture that is the coming Singularity – who needs God when you've a metal friend smart enough to rebuild you every time you wear out?.

Cautioning fellow scientists Lanier pens:

We serve people best when we keep our religious ideas out of our work.

The separation of church and work! Good luck. Most of us don't have an internal supreme court to vigilantly enforce such high moral standards. The whole concept of a "religious scientist" seems to me a non-starter –like a "vegetarian carnivore".

Yet, as a hard atheist, I applaud Jaron's thesis. To me, science is, at base, the act of learning to get better at recognizing the difference between myopic want-driven self interest and the foundational truths that give rise to the largest most inclusive (universal) vantage – and then doing everything in one's power to avoid confusing the two. As we build towards this post-biological evolutionary domain, crystal clear awareness of this difference has never been more important.

Those of us pursuing "hard" AI, AI that reasons autonomously as we do(?), eventually discuss the capacity of a system to flexibly overlay patterns gleaned from one domain onto other domains. Yet, at least within the rhetorically noisy domain of existential musings, we humans seem almost incapable of achieving to this bar. Transhumanists and Cryonicists can identify religious thinking when it involves guys in robes swinging incense, yet are incapable of assigning the "religious" tag when the subject matter involves nano-bot healing tanks or n-life digital-upload-of-the-soul heaven simulations.

Why does it matter? Traditional human ideas about transcendence are exclusively philosophical. The people inhabiting traditional religious heavens (and hells) don't eat our food, drink our water, breath our air, consume our electricity, or compete for our land or placement in our schools. Yet the new-age, digital, post-singularity, friendly-AI omnipotence scheme isn't abstract or etherial… the same inner fear of death in these schemes leads to a world in which humans (a small, exclusive, rich, and arrogant subset of human kind) never actually die, don't end up on another plain, stay right here thank you very much, and continue to eat and drink and build houses and consume scarce resources along side anyone unfortunate enough to be enjoying(?) their first life right now.

I saw the best minds of my generation destroyed by…

Howl, Allen Ginsberg, 1955

Every generation must at some point gather the courage to stand up and give an accounting for its own inventive forms of arrogant blindness and the wastefulness that litters its meandering. When it is our turn, we will have to laugh and cry at our silly and dangerous taking that is the reification of the "life ever after" fantasy. And while we are confessing hubris, we might as well admit our myopic obsession with "search". Google has been our very own very shiny golden cow (is it simply because there aren't any other cows left standing?).

When self interest goes head to head with a broader vantage, vantage wins. Vantage wins by looking deep into the past and the future and seeing that change trumps all. I guess it comes down to the way that an entity selects the scope of its own boundaries. If an entity thinks itself a bounded object living right now, it will resist change in itself or its environment. I can hear the rebuttal, "Entities not driven by selfishness won't protect themselves and won't successfully compete." Entities who see themselves as an actual literal extension of a scheme stretching from the beginning of time laugh at the mention of living forever… because they already do!

The scheme never dies.

Germain to this discussion is how a non-bounded definition of self impacts the decisions one makes as regards the allocation of effort and interest. What would Thermodynamics do?

…Yet all experience is an arch wherethro'
Gleams that untravell'd world whose margin fades
For ever and forever when I move.
How dull it is to pause, to make an end,
To rust unburnish'd, not to shine in use!
As tho' to breathe were life!…

Ulysses, Alfred, Lord Tennyson

Is there something about the development of AI that is qualitatively different than any challenge humans have previously undertaken? Most human labors are not radically impacted by philosophy. A shoe designer might wrestle with the balance between aesthetics and comfort or between comfort and durability, between durability and cost, but questions of to whom or what they choose to pray, or how they deal with death, don't radically impact the shoes they design.

There seems little difference between the products of hindu and christian grocers, between the products of Muslim and atheist dentists, road builders, novel writers, painters, gynecologists, and city planners. Even when you compare the daily labor of those practitioners that directly support a particular philosophy; the Monks, the Pastors, the Priests, the Imams, the Holy Them's… you find little difference.

So why should AI be different? Why should it matter who does AI and what world views they hold? I think it is because the design of AI isn't an act in reference to God, it isn't even "playing" God – it is quite literally, actually being God.

What training do we humans, we mammals, we vertebrates, we animals, we eukaryotes, we biological entities, what does our past offer us as preparation for acting the part of God?

It is true that each of us are the singular receptacles of an unbroken chain of evolutionary learning. The lessons of fourteen thousand million years of trial and error are encoded into the very fabric of our being. We are walking talking reference tables of what works in evolution. Yet very little of that information deals with any kind of understanding or explanation of the process. Nowhere in any of this great tome of reference in the nucleus of each of our cells does there exist any information that would give context. There is no "this is why evolution works" or "this is why this chunk of genetic code works in the context of the full range of potential solutions" coded into our DNA or our molecular or atomic or quantum structure.

And that makes sense. Reasons and context are high order abstraction structures and biology has been built up from the most simple to the most simple of the complex. It is only within the thinnest sliver of the history of evolution that there been any structural scheme complex enough to wield (store and process) structures as complex as abstraction or language.

We are of evolution yet none of our structure encodes any knowledge of evolution as a process. What we do know about the process and direction of change we have had to build through culture, language, inquiry. Which is fine, if that is, you have hundreds (or thousands) of millions of years and a whole planet smack in the energy path of a friendly star. This time around we are interested in an accelerated process. No time for blindly exploring every dead end. This time around we explore by way of a map. The map we wield is an abstracted model of the essential influences that shape reality in this universe. The "map" filters away all of the universe that is simply instance of pattern, economically holding only the patterns themselves. The map is the polarized glasses that allow us to ignore anecdote and repetition, revealing only essence, salience.

What biology offers in stead of a map is a sophisticated structural scheme for the playing of a very wasteful form of planet-wide blind billiards, a trillion trillion monkeys typing on a trillion trillion DNA typewriters, a sort of evolutionary brownian motion where direction comes at the cost of almost overwhelming indirection.

And again we ask, "Why does it matter?" Imagine a large ocean liner – say the Queen Elizabeth II. Fill its tanks with fuel, point it in the right direction, and it will steam across any ocean. It really doesn't matter what kind of humans you bring aboard, or what they do once they there. A big ship, once built, will handle an amazing array of onboard activity or wild shifts in weather. Once built, a ship's structure is so stable and robust that its behavior becomes every bit as predictable. But if you brought dancing girls, water slides, and drunk retirees into the offices of the navel architects while they were designing the ship, it probably wouldn't make it out of the dry dock. The success of any project is unequally sensitive to the initial stages of its development. Getting it right, up front, is more than a good idea, it is the only way any project ever gets built. Acquiring the knowledge to be a passenger on a ship is far easier than acquiring the knowledge to design or build it.

We General AI researchers work at the very earliest stage of a brand new endeavor. This ship has never been built before. Ships have never been built. In a very real sense, "building" has never been built before. We have got to get this right. Where navel architects must first acquire knowledge of hydrodynamics, about structural engineering, material science, propulsion, navigation, control systems, ocean depths, weather systems, currents, geography, etc., AI researchers must bring to the project an understanding of pattern, language, information, logic, processing, mathematics, transforms, latency, redundancy, communication, memory, causality, abstraction, limits, topology, grammar, semantics, syntactics, compression, etc.

But this is where my little ship design analogy falls short. AI requires a category of knowledge not required of any other engineering endeavor. Intelligence is a dynamic and additive process, what gets built tomorrow is totally dependent on what gets built today. Building AI therefore requires an understanding of the dynamics of change itself.

Do we understand change?

[to be continued]

Randall Reetz

The Scope of Evolution?

2010-07-26T11:55:00.001-07:00

We evolutionists desperately want to quantify evolution. We are embarrassed by the continued lack of measurability and predictability one would expect from a true theory-based science. In the place of true metrics, we defer to the vague, broad, and situationally dependent term; "fitness".

We say that genetic variability in the population of any given lineage will insure that some individuals express traits that provide a survival advantage. Given the particularity of a given environment's mix of resources and challenges, not all individuals will have the genes necessary to make them fit. We say that there is always some small diversity in any population, a variability caused by sexual mixing, mutation, and a whole slew of non-genetic processes that indirectly effect either the actual genes inherited or conditions under which those genes are expressed. We say that this variability across a localized population is enough to influence who will survive and who won't, or most importantly, who's genes will be expressed in the next generation and who's won't. We assert that this process is obvious, observable, and predictable. And of course we are correct. We can and do produce laboratory experiments and field observations in that show that genes predict traits, genetic variability is correlated to population variability, and environmental conditions act as filters selecting towards individuals or populations expressing some genes and against those with others.

Well that all sounds good… model driven prediction, physical mechanistic explanation, solid techniques for observation… like a real science. If, that is, you are content to restrict your inquiry to the how.

If you are content with an understanding of evolution that is restricted to biology. If you are content with an understanding of evolution that blindly accepts as dependent factors, such temporal notions and shifting and immeasurable terms as "environment" and "fitness" and never ever asks, "Why?", then you probably won't need to read any further.

But if you, like me, would like to understand evolution in its largest context; independent of domain, and across all time, then you already know that evolution's current answers, though already correct and verifiable by any standard, is not yet a true science.

When Newton sought to define motion (and yes I know that Einstein perfected it through Relativity and quantum theory), he didn't do so only for an apple falling from a tree… but universally, for all physical bodies in all situations. His equations predict the position, speed and trajectory of an object into any distant future and across any distance. If the same could be said of evolution theory, we would have in our possession theory and or equations that we could use to predict the outcome of evolution across any span of time and in any domain.

Yet, of course we don't. We know all kinds of things about the interaction, within the domain of biology, of germ and progeny, of reproductive selection and mutation, of the relationship between genotype and phenotype, and of the competition over resources and of the crazy alliances and unintuitive and unplanned results of cooperative adaptation (including the tightly wound dance between predator and prey, between parasite and host).

But these processes, no matter how well understood, measured, researched, and modeled, are not what could be called the primitives of evolution. To be primitives, they would have to be universal. They are not universal. Thinking so would be like Newton thinking his laws only applied to cannon balls or things made of metal. So ingrained is the false correlation between biology and evolution that it is often impossible for me to get people to continue a discussion about evolution when I say "Let's talk about evolution in other systems." or "Let's talk about evolution as domain independent phenomenon."

If evolution isn't a "general" phenomenon, then someone representing the "special theory of evolution" will have to show how it is that life evolves but other systems do not. I doubt this requirement can be met. It would mean that some line can be drawn in time, before which there wasn't evolution, and after which there was. The logical inconsistency arises when one realizes that, to get to that line, some process suspiciously similar to evolution would have to have transpired to advance complexity to the level just preceding biology.

Another way to frame the overarching question of the why of evolution starts with the realization that competition within an environment isn't restricted to the various individuals of one species. Nature isn't that well refereed. In fact, nature isn't refereed at all. Nature is a free for all pitting snail against walrus against blue green algae. And it doesn't stop there. The ocean currents compete to transfer heat and in doing so, effect the food available to marine life of all kinds. In a very real sense, in an exactly real sense, a hurricane competes directly with a heron. Even the more stable artifacts of an environment, the topology and physical composition of the geographic features below foot compete actively and dynamically with the biota growing in its fissures and above its slowly moving face. Our old and narrowly-bounded definition of that which fits the category of evolution is plainly and absurdly and arbitrarily anthro-, species-, mammal, or bio- centric, and logically wrong.

Each time I introduce these new and inclusive definitions of the scope of the cast that performs in the play that is evolution, I hear grunts and groans, I hear the rustle of clothes, the uncomfortable shiftings… I hear frustration and discomfort. Hands raise anxiously with questions and protests: "How can non-living things evolve?" "Non-living things don't have genes, without genetics traits can't be transferred to or filtered from future generations!" And the inevitable, "The category containing all things is a useless category!"

I can't say that I don't understand, don't appreciate, or in some real way haven't anticipated and sympathized with these bio-centric apologies. This is how evolution has been framed since Erasmus Darwin and his grand kid Charles first seeded the meme. I will therefor take a moment to address these two dominant arguments such that they can be compared with a domain-independent definition of evolution.

First, lets look at evolution's apparent dependence upon genetics. How could evolution work if not for a stable medium (DNA) for the storage and processing of an absolute recipe for the reliable re-creation of individual entities? You may be surprised that my argument starts with an agreement; evolution is absolutely dependent upon the existence of a substrate stable enough to transfer existing structure into the future. But does that stable structure have to be biology's famous double helix? Absolutely not! In fact, it is causally impossible to find a system within this Universe (or any imaginary universe) in which the physical makeup of that system and its constituent parts does not facilitate the requisite structure to transfer conditions and specific arraignments from any present into any trailing futures. The shape of a river valley is a fundamental carrier of information about that valley into the future. The position, mass, and directional velocity of celestial bodies is sufficient carrier of structural information to substitute handedly for the functional duty that DNA performs in biology. But it is also important to realize and fully absorb the opposite proposition. DNA is not the only way that biological systems reliably transfer information about the present into the future. Biological systems are of course just as physical as galaxies, stars, and planets. The same causal parameters that restrict the outcome of any particular then (as a result of any particular now), that restrict causality to an almost impossibly narrow subset of what would be possible in a purely random shaking of the quantum dice. DNA is especially good at what it does, but it doesn't own or even define the category.

The second argument against an all-inclusive, domain independent definition of evolution – the logical argument against the usefulness of category that contains everything – well let's start by parsing it semantically and rhetorically. On face, there is no way to argue. The category "all" is a category of little worth. There is nothing to be known of something if it can't be compared to something else. But, and this should be obvious, I am not trying to create a category; quite the opposite! My intent is to create a theory of everything. Such a theory would obviously fail if it didn't apply to everything. So, semantically, this "set of everything is a useless set" argument doesn't map to the topic at hand. I get the distinct feeling that the argument is meant pedantically, and purposely, to derail and obfuscate the logical trail I am attempting to walk the audience down. It is a straw horse. It looks logical, but it doesn't apply.

A much more instructive and interesting line of questioning would go to the plausibility of a domain independent theory of evolution, what it would or would not change regarding our understanding of the emergence of complex structures (and their accelerating complexity), how it modifies our understanding of biological evolution, whether or not evolution will stand up to the requirements of a "theory of everything" (how it compares with others), and maybe even the effectiveness of my own description of this idea.

So, why is it important to me for evolution to meet the test of a "theory of everything"? First, I loath the unexplained. If evolution only talks to the mechanism of change within biology, then evolution would necessarily stand upon a stack even more foundational truths, and, as I mentioned earlier, other parallel theories would have to be developed to explain the emergence of complexity in non-biological systems. Either way, a vacuum would remain, exposing a need for the development of a foundational theory or set of theories that would support what in biology we call evolution, what in geology we call tectonics (etc.), what in meteorology we call heat dissipation cells, what in culture we call engineering, cooperative networks, etc.

What makes this whole endeavor so tricky, is that we tend to confuse mechanism with purpose. We get so caught up with the almost impossibly complex molecular mechanism (nucleic acids) by which biology builds complexity, that we forget to look at why it bothers at all. This why, this great big why, is to my mind far more fundamental and interesting and once understood, provides a scaffolding from which to comfortably understand and predict the necessary meta-components that need to be present in some form or another, in any evolving system. And, if you like elegance in a theory, it gets even better. It turns out that a byproduct of evolution as a theory of everything is that it must therefore be based on the two physical principals that have stood the test of universality – thermodynamics and information theory, and it strengthened both of these theories in the one area they were weak – dynamics. Once you understand the motivation and demands of change itself, the particular mechanisms of evolution at play in any one domain are reduced to how, are, no matter how varied, are but skins worn by a beast who's behavior becomes more and more predictable and universal.

All systems have what it takes to evolve. All systems are composed of components that in some small way differ. That difference might be in how the parts are made, or it might be in how the parts are distributed, and it most probably is both. That is all a system needs for the process of evolution to apply. So long as there is a difference somewhere in the system, or in that system's interaction in the greater environment in which it exists, evolution needs must be happening all of the time.

So just what is it that evolving things compete for? Is it food? Yes. Is it safety? Yes. Is it comfort? Yes. Is it stability? Yes, that too. For plants, competition is for solar radiation, carbon dioxide, water, a stable place to eat, grow, mate, and rase offspring. We animals need far more energy than our skin could absorb even if it was all capable of photosynthesis. So we eat things that can. And that is just the way things work. To get ahead, things learn to take advantage of other things. One might even say that the advantage always goes to those entities that can take the greatest advantage of the the productive behavior of the greatest number of other things. If you can't make enough energy, then eat a lot of things that can.

One could imagine taking this line of reasoning to the extremes. Lets define fitness as the ability to sit on the apex of a food chain. Of course you have to keep moving. If you don't stay vigilant and obsessive, always trying to find new and better ways to eat more of the other things, you will succumb to competition by things that do.

… to be continued …

Randall Reetz

Real-Time Observation Is Always More Efficient Than After-The-Fact Parsing

2010-06-23T10:45:00.000-07:00

Non-random environments (systems):

- have evolved (from a more simple past)
- are (variously) optimized to input conditions and output demands
- are sequentially constructed in layers
- are re-constructed periodically
- are derived from the constraints of pre-existing environments

Understanding (extracting pattern rules and instances of these rules) is made more efficient through observations undertaken over the course of an environment's construction period. Extracting pattern after the fact requires the act of inferring construction sequence from existing artifact. The number of possible developmental paths (programed algorithms) that will result in a particular artifact are infinite. Parsing through this infinite set towards a statistically biased guess at the most likely progenitor is lossy at best and computationally prohibitive.

For instance, the best (shortest algorithmic complexity) candidate produced by post construction parsing may indeed be a more likely (least energy) progenitor, but this may not predict the actual causal chain that resulted in that environment. Projections based on a statistically optimal history will diverge from the futures actually produced by the environment.

The only time that a statistical (minimum algorithm) parsing of an environment is guaranteed to match reality is when that parsing includes the whole system (the entire Universe).

Observing the genesis of an environment minimizes the mandatory errors inherent in statistical after-the-fact (Solomonoff) algorithmic probability parsing of a pre-existing system.

Said more succinctly; If you want to grow an optimal system, use algorithmic probability and algorithmic complexity as metrics towards optimization, but if you want to describe a pre-existing system, it is best to build this description by observing it's genesis.

Randall Reetz

DNA replication…

2010-06-16T15:58:00.000-07:00

Yes, this shit is so amazing that it makes a hardened evolution theorist like me cough up some creationist thoughts (don't worry, it will be a temporary affliction).

This animation shows the lagging strand replication process in greater detail. If you are wondering why the lagging strand should have to be built in reverse, it is because the other side of the helix is inverted which would have necessitated an exact molecular machine to have been evolved from scratch, but in reverse! This molecule, "polymerase", is composed of 8005 atoms. The ingenious workaround, to run the strand through the same molecule backwards, though mechanically awkward, is far more likely (less complicated) to have evolved than would have been a mirror image of the whole polymerase molecule (or its function). In fact, it is probable that such a molecule might not even be physically possible given the "handedness" (right/left) of the atoms molecules must be built of. Because of this, I consider the asymmetry of DNA replication machinery to be evidence of the least energy dictated meandering of the evolutionary process.

By pure chance, an particular arrangement of 8005 things would happen once every 8005 to the 8005th attempts (8005 factorial). Of course molecules don't assemble by pure chance. Even if you dumped the requisite atoms into a box and shook it up, the assembly wouldn't happen instantaneously, some atoms would form small groups, and those groups would clump together into larger groups, etc. The atoms of each element have unique properties that effect their aggregation.

But that isn't the full story either because the polymerase molecule is built atom by atom by DNA.

Look at this…

2010-06-16T15:03:00.000-07:00

It is called a Snow Plant. Comes out of the ground like an alien right after the snow melts. This one was just meters up the hill from a trail head on the northeast shore of Lake Tahoe. They are parasites of fungus that grows on the root systems of pine trees. Unreal! [about 8 inches tall and more brilliant than this picture could ever show]

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

2010-05-02T18:17:00.000-07:00

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

Proactive Fix For Deep Sea Oil Platform Blowouts

2010-04-30T15:47:00.000-07:00

If off-shore oil platform developers were required to pre-install a permanent emergency oil blowout collection tent at each wellhead, the disaster unfolding in the gulf of mexico would never have happened.

The above diagram shows the tent as deployed after a blowout. Before a blowout the tent would lay flat on the ocean floor in the ready. When a blowout occurs at the well head (A), a winch (or air filled ballast) (B) pulls the tent up into position over the well head (A). The tent (C) is composed of an inverted V shaped rigid "tent pole" (D) hinged at pivot points (E) anchored at sea floor. Once deployed, the tent presents as an inverted pyramid that catches the oil (G) as it rises (oil is lighter than water). A ten inch hose (H) is lifted from the apex of the tent to the surface of the ocean by buoys (I) along at intervals along its length. The hose terminates at the surface where a tanker is positioned to pump the oil into its hold until such a time as the well head can be sealed.

Using another approach, the rigid poles are replaced by buoys lifting the apex of the tent. Four guy lines anchor the tent's corners to the ocean floor. This option allows for a larger tent and might prove easier to install and deploy.

The entire contraption could also be prebuilt, pre-packaged, and deployed from a GPS guided barge or ship – dropping four anchors or concrete standards at equal radius from the well head and then deploying the collection tent and pumping hose remotely via at-depth gas filled buoys or mechanical winch.

Randall Reetz

Devaluing Survival

2010-04-09T09:54:00.000-07:00

The goal of evolution is not survival. Rocks survive much better, longer, and more consistently than biological entities. This should be patently obvious. Survival is a tailing of evolution and achieves a level of false importance probably because those of us doing the observation are so short lived and thus value survival above almost everything else.

In biology as in any other system, evolution is not concerned with nor particularly interested in individual instanciations of a scheme. A being is but a carrier of scheme. And even that is unimportant to THE scheme which can only be one thing – the race towards ever faster and more complete degradation of structure and energy.

To this (or any other) universal end, schemes carry competitive advantage simply and only as a function of their ability to "pay attention to", to abstract, the actual physical grammatical causal structure of the universe. And why is this important? Because a scheme will always have a greater effect on the future of the universe if it "knows" more about the future of the universe. Knowing is a compression exercise. Knowing is two things. 1. acquiring a description of the whole system of which one is a part, and 2. the ability to compress that description to its absolute minimum. A system that does these things better than another system has a greater chance of out-competing its rivals and inserting its "knowledge" into future versions of THE (not "its") scheme. To the extent that an entity pays more attention to its survival (or any other self-centered goal) than to THE scheme, is the extent to which another entity will be able to out-compete it.

Darwin was a great man with an even greater idea (his grandfather Erasmus even more so). But neither had the chops or the context to see evolution at a scope larger than individual living entities or the "species" within which they were grouped competing amongst each other over resources. There was very little understanding of the concept "resources" during his lifetime – certainly not at the meta or generalized level made possible by today's understanding of information and thermodynamics and as a result of Einstein's work its liberation of the symmetry that separated energy, time, distance, and matter. However, Darwin's historically forgivable myopia has out lasted its contextual ignorance and seems instead to be a natural attribute or grand attractor of the human mind. His sophomoric views are repeated ad nauseum to this day.

Randall Reetz

Building Pattern Matching Graphs

2010-04-05T15:58:00.001-07:00

I talk a lot about the integral relationship between compression and intelligence. Here are some simple methods. We will talk of images but images are not special in any way (just easier to visualize). Recognizing pattern in an image is easier if you can't see very well.

What?

Blur your eyes and you vastly reduce the information that has to be processed. Garbage in, brilliance out!

Do this with every image you want to compare. Make copies and blur them heavily. Now compress their size down to a very small bitmap (say 10 by 10 pixels) using a pixel averaging algorithm. Now convert each to grey scale. Now increase the contrast (about, 150 percent). Store them thus compressed. Now compare each image to all of the rest: subtract the target image from the compared image. The result will be the delta between the two. Reduce this combined image to one pixel. It will have a value somewhere between pure white (0) and pure black (256), representing the gross difference between the two images. Perform this comparison between your target image and all of the images in your data base. Rank and group them from most similar to least.

Now perform image averages of the top 10 percent matches. Build a graph that has all of the source images at the bottom, the next layer is the image averages you just made. Now perform the same comparison to the 10 percent that make up this new layer of averages, that will be your next layer. Repeat until your top layer contains two images.

Once you have a graph like this, you can quickly find matching images by moving down the graph and making simple binary choices for the next best match. Very fast. If you also take the trouble to optimize your whole salience graph each time you add a new image, your filter should get smarter and smarter.

To increase the fidelity of your intelligence, simply compare individual regions of your image that were most salient in the hierarchical filtering that cascaded down to cause the match. This process can back-propagate up the match hierarchy to help refine salience in the filter graph. Same process works for text or sound or video or topology of any kind. If you have information, this process will find pattern in it. Lots of parameters to tweak. Work the parameters into your fitness or salience breading algorithm and you have a living breathing learning intelligence. Do it right and you shouldn't have to know which category your information originated from (video, sound, text, numbers, binary, etc.). Your system should find those categories automatically.

Remember that intelligence is a lossy compression problem. What to pay attention to, what to ignore. What to save, what to throw away. And finally, how to store your compressed patterns such that the graph that results says something real about the meta-paterns that exist natively in your source set.

This whole approach has a history of course. Over the history of human scientific and practical thought many people have settled in on the idea that fast filtering is most efficient when it is initiated on a highly compressed pattern range. It is more efficient for instance to go right to the "J's" than to compare the word "joy" to every word in a dictionary or database. This efficiency is only available if your match set is highly structured (in this example, alphabetically ordered). One can do way way way better than alphabetically ordered lists of 3 million words. Lets say there are a million words in a dictionary. If one sets up a graph, an inverted pyramid, where each level where the level one has 2 "folders" and each folder is named for the last word in the subset of all words at that level divided into two groups. The first folder would reference all words from "A" to something like "Monolith" (and is named "Monolith") The second folder at that level contains all words alphabetically larger than "Monolith" (maybe starting with "Monolithic") and is named "Zyzer" (or what ever the last word is in the dictionary). Now, put two folders in each of these folders to make up the second tier of your sorting graph. At the second level you will have 4 folders. Do this again at the third level and you will have 8 folders each named for the last word in the graph referenced in the tiers of the graph above them. It will only take 20 levels to reference a million words, 24 levels for 15 million words. That represents a 6 order of magnitude savings over an unstructured sort.

A cleaver administrative assistant working for Edward Hubble (or was it Wilson, I can't find the reference?) made punch cards of star positions from observational photo plates of the heavens and was able to perform fast searches for quickly moving stars by running knitting needles into the punch holes in a stack of cards.

Pens A and B found their way through all cards. Pen C hits the second card.

What matters, what is salient, is always that which is proximal in the correct context. What matters is what is near the object of focus at some specific point in time.

Lets go back to the image search I introduced earlier. As in the alphabetical word search just mentioned, what should matter isn't the search method (that is just a perk), but rather the association graph that is produced over the course of many searches. This structured graph represents a meta-pattern inherent in the source data set. If the source data is structurally non-random, its structure will encode part of its semantic content. If this is the case, the data can be assumed to have been encoded according to a set of structural rules themselves encoding a grammar.

For each of these grammatical rule sets (chunking/combinatorial schemes) one should be able to represent content as a meta-pattern graph. One of the graphs representing a set of words might be pointers to the full lexicon graph. A second graph of the same source text might represent the ordered proximity of each word to its neighbors (remember the alphabetical meta-pattern graph simply represents the neighbors at the character chunk level).

What gets interesting of course are the meta-graphs that can be produced when these structured graphs are cross compressed. In human cognition these meta-graphs are called associative memory (experience) and are why we can quickly reference a memory when we see a color or our nose picks up a scent.

At base, all of these storage and processing tricks depend on two things, storing data structures that allow fast matching, and getting rid of details that don't matter. In concert these two goals result in a self optimization towards maximal compression.

The map MUST be smaller than the territory or it isn't of any value.

It MUST hold ONLY those aspects of the territory that matter to the entity referencing them. The difference between photos and text: A photo-sensor in a digital camera doesn't know for human salience. It sees all points of the visual plane as equal. The memory chips upon which these color points are stored see all pixels as equal. So far, no compression, and no salience. Salience only appears at the level of where digital photos originate (who took them, where, and when). On the other hand, text is usually highly compressed from the very beginning. What a person writes about and how they write it always represents a very very very small subset of

Compression as Intelligence (Garbage Out, Brilliance In)

2010-04-05T15:57:00.000-07:00

I am convinced that the secret to developing intelligence (in any substrate, including your brain) lies in the percentage of the data coming in that you are willing (or forced) to toss. Lossy compression is the key to intelligence. Of course there is a caveat… you can't just trash anything and everything.

The first line of the book I am writing about evolution: "What matters is what matters, knowing what matters and how to know it matters the most."

I am convinced that evolving systems can only work towards mechanisms that process salience if they are forced to maximize the amount of stuff they can trash.

If you are forced to get rid of 99.999 percent of everything that comes in, well you will have to get good at knowing the difference between needles and hay and you will have to get good at knowing the difference in a hurry. The "needles and hay" metaphor doesn't map well to what I am talking towards. If the system you are dealing with is so unstructured as to fit the haystack metaphor, you really aren't doing anything I would classify as intelligence. If there is nothing of structure in the haystack you are storing than your compression system should already have tossed the whole thing out.

Many techniques for the filtering of essence, for finding pattern, for storing pattern and for storing pattern of pattern have been developed. The most impressive reduce raw input streams and store pattern from the most general to the most specific as hierarchically stratified graphs.

Being forced to reduce data to storage formats that maximize lossy-ness minimizes necessary storage. But that is just a perk. What really gates intelligence is the amount of a complex system (or map thereof) that can be made proximal to immediate processing. Our brains might be big and mighty, but what really matters is how much of the right parts of what is stored can be brought together in one small space for semi-real-time simulations processing. Information, when organized optimally for maximal storage density, will also be information that is ideally organized for localized serialization and simultaneity of processing.

To think, a system has to be able to grab highly compressed pattern hierarchies and move them into superposition on top of each other for near instantaneous comparison. You can't do this with a whole brain's worth of data, no matter how well organized it is.

Lets say you have to store everything you know about every sport you have ever heard of, and you have to do it in a very limited space. You will be forced to build a hierarchy of grammars in which general concepts shared in every sport (opponents, the goal to win, a set of rules and consequences, physical playing geometries, equipment, etc.), with layers of groupings that allow for the similarities between some sports and so on up to the specifics that are are only present in each individual sport. Keep compressing this set. Always compress. Try all day (or all night) for even more compression. Compress until you can't even get to lots of the specifics any more. Keep compressing. Dump the sports you don't care about. Keep on throwing stuff out.

Now lets say I have some sort of morbid sense of humor and I tell you that you are going to have to store everything you encounter and everything you think about, your entire life, in that same database that you have optimized for sports.

You will have to learn to look for the meta-patterns that will allow you to store your first romance in a structure that also allows you to store everything you know about kitchen utensils and geo-politics and the way the Beatles White Album makes you feel when it is windy outside.

The necessity to toss, enforced by limited storage and an obsession to compress will result in domain-blending salience hierarchies. It is why we can find deep similarities between music and geological topologies. It is why we can "think".

For years people have tried to come up with the algorithms of thought. What we need instead is to build into our artificial systems, a very mean and ornery compression task master that forces over time, all of our disparate sensation streams into the same shared graph.

Once you have all of your memories stored within the same graph, by necessity sharing the same meta-pattern, the job of evolving processing algorithms is made that much easier.

An intelligent system will spend most if not all of its time compressing data. We have a tendency to bifurcate the behavior of a mind into storage on the one hand, and processing on the other. I am beginning to think that the thing we call "thinking" and "thought" is exclusively and only a side-effect of constant attempts at compression – that there really isn't anything separate that happens outside of compression. Is this possible?

Randall Reetz

Computing: What Went Wrong

2010-03-21T11:00:00.000-07:00

The year, 2010. The state of computing? Applications that build obfuscating document types that act as black boxes, hiding and separating information and intent. File systems that store these documents largely blind of their content, of the context of their origination, and of the associations hidden in the meaning that binds them to the flow of the author's life and work.

There are but a finite set of ways that information needs to be associated. Yet almost none of these association types are supported by our computers. If you don't know before hand that everything you want to do will fit into the format of a linear text document, or the grid of a spread sheet, or the fields and records of a data base, well you might as well not even start. If you want some information in one of your documents to reference information in another, well you had better be content with copying and pasting (live links are forbidden in all but the most expensive (and self-restrictive) application "suites".

Why is this true? Why don't we yet have computers that can compute? Mainly because the application layer is the WRONG place for the association of information. The file system is the RIGHT place. Information must be related and associated in a strata far below the application layer. The only authority that should be granted to applications is user affordance – how humans are helped through the assignment, understanding, and management of the associations within their life's data.

To do this, the data (file) management layer needs to be beefed up (and the application layer slimmed down). Where today's file systems only know a document by its wrapper (name, enclosing folder, parent application, document type, size, date, and on-disc storage address), a true data model layer would "understand" and dictate the structure of all of the ways information is related both within and between "documents". In fact, in a data-model driven architecture, documents become arbitrary "collections", "instances", and "presentations" specific to the context of presentation or use. The underlying data and associations between data from which documents are derived remain intact, separate, and agnostic of the documents that serve to reference, blend, display, and associate.

In the proposed data-model driven architecture, applications don't define information association, they must call on the data model to ask which types of associations are allowed and how these associations dictate data type, grammatical hierarchies, and chunking. Applications build documents not as strings of binary, but from pointers into the information content stored according to the meta-archetectural rules of the master data model. A document becomes instead an instance of assembled data and data associations (either frozen or live)… more like the "edit decision lists" that video and music editing professionals use to assemble linear streams of media from multiple sources.

Today's computational model's awkward emphasis on application authority and autonomy promotes an informational ecosystem that promotes informational islands dictated by the whims of application developers.

[to be continued]

Randall Reetz

The Incomputable Heaviness of Knowledge

2009-12-11T17:19:00.000-08:00

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?

Thanks to the tireless obsession of three centuries of scientists, most of the necessary information is there. What's missing is some convenient way to bring it all together. In the past, in the absence of knowledge we inserted some sort of conveniently complete and simple placeholder to fill the space between the beginning of all time, and, say, that part about parking meters. Cosmology = genesis moment - god - parking meter.

The complete historical/causal cone that is physical forces and the environmental conditions through time… well we call it the Universe. Scientifically, this word "Universe" now supports a cognitive mass not unbecoming its meaning. But does this knowledge actually influence thinking? When thinking about the parking meter, is even the most knowledgeable scientist holding the standard model at the cognitive ready? I doubt it. Instead, we simply posit a revised cosmology: genesis - standard model - parking meter, substituting "standard model" for the out of fashion "god".

Even so, I frequently find myself wanting to present ideas that are dependent upon the whole chain of scientific causality. Should I have to re-compose the whole standard model cosmology every time? I frequently do. This leaves very little room for the specific or topical arguments I am trying to convey. And, it is tiring.

Should I assume the reader's mind is standard model primed? Even people well schooled in the full contemporary empirical ontology can not keep the whole stack in the cognitive forefront. But when I decide to be careful, to once again lay it all out as scaffolding to properly support my topic, can I really be sure that I am providing a service? What if there is only x number of things a person can hold in their immediate conscious or rational mind? What if what I want to talk to requires the pre-loading of x+1 concepts?

Let's suppose my suspicions are correct. Let's suppose knowledge-based explanations have already reached this limit. Now what? Do we simply specialize, draw a bite sized boundary around a concept and avoid the whole causal-completeness problem altogether? Or, do we construct cognitive prosthesis to shoulder part of the load? Is pen and paper one such crutch? How about language itself? The computer?

Should I start my essays with "Please pre-load standard model, then proceed …"?

This will mean nothing to non-scientists. Hell, what it means to scientist will vary wildly. Worse still, the stuff I like to think about requires tweaks to the average interpretation of the standard model.

Over time, our understanding of the universe becoming more and more accurate. If this understanding comes in the form of a catalog, it grows linearly with the pace of discovery. If we are cleaver, and if the universe we study isn't randomly ordered, then our knowledge might also optimize towards salience. It is often the case that discriptions shrink over time as knowledge of a system becomes more sophisticated, as patterns are teased from the raw data, much of it can be tossed as redundancy. As an abstraction matures, it becomes hierarchical, a layered dependency stack, each layer a dictated by its own set of rules for the aggregation of the aggregates it inherits from the layer just beneath. Layered grammatical hierarchies evolve towards a minimal optimal size and complexity, but their complexity will always reflect the complexity of the domain they abstract. Any abstraction will be more complex than the absence of an abstraction. Ignorance might not be bliss, but it does require less processing.

The question then becomes, is even the tightest and most elegant abstraction of the universe within the comfortable limits of the human brain?

So, what is it that might limit the human brain? Any brain? At some basic level thinking must involve the assembly or isolation of a the set of data upon which processing in that domain depends. In contemporary computing, that involves sequencing data into a processing cue that can be sent chunk by chunk into the logic substrate of the processing chip. In the biological brain, well we are just now guessing at how that might happen, and it seems that it must be a radically different proposition altogether. In the brain, data is stored within a network web of connected neurons. It does not appear that data is shuttled from one place to another so much as it propagates through networks according to some sort of simple filtering that happens at each branching. In the brain, the data seems to be stored as pathway, something akin to an address scheme like a postal code or IP address.

Either way, knowledge is a physical thing, taking up, in what ever form, some finite and measurable amount of storage space and requiring some finite quantity of processing energy. By these simple metrics, computing (thinking) is as corporal, physical, and bounded as any system. We recoil from such mechanistic assessments of thinking, but there is simply no way around it, at some level, whether it is electro-chemical, or quantum photonic, thinking has to be a physical process and the stuff being thought has to exist physically. More to the point of this essay, the size and complexity of the stuff of thoughts must in some non-arbitrary way map to the size and complexity of the systems they abstract. A complex thought must take more space than a simple thought in the same way that a complex thing must take more space than a simple thing.

At a certain level of complexity, any brain or computer will no longer be able to compute on the representative data set.

Turing postulated as thought experiment. the simplest computational machine. This "turing machine" took as input a string of binary data (ones and zeros).

If we likewise consider knowledge as a graph that associates experience along a range from the most general to the most specific, and intelligence as efficient means of traversing this graph and accumulating salient reductions, then we can then see that any mind is limited and measurable by the number of these graph connections and the effectiveness of its graph crawling agents. Assuming the perfect graph and the perfect graph crawlers one can calculate the best possible intelligence for any set of linked nodes.

To the extent that part of the graph must be used to store the graph crawling agent's behavior, the capacity of the system is reduced. If on the other hand, the graph is so constructed, such that crawling it is the natural (least energy) result of any environmental interaction, then all of the graph is assumed to contain or have the potential to contain knowledge.

Now, still assuming the perfect storage system, lets look at what a graph crawler must do, and what its attributes must be, in order that salience results from simple traversal. There are only two options. In the first, the agent must keep track of the path it takes through the graph. That history of its path through the graph becomes the answer it accumulates as it crawls. In the second, the graph it self must be traversed at least two times. As the agent traverses the graph on its first trip, instead of accumulating a copy of the path it takes, the agent modifies the graph in some way (leaves bread crumbs). The second trip through the graph, this time following the crumb trail, is itself the solution. The job of the second agent is both to sing out the answer as it traverse the marked graph, and to wipe the path clean as it goes.

In both of these examples, it is easy to see that knowledge is limited by how long a path an agent can hold, or how quickly it can sing out its answer. In computation, both the time it takes to accumulate an answer, and its shear size, are the critical limiters. An answer is no good if it is as large as the problem. Abstraction must provide computational advantage over the abstracted.

An analogy can be loosely drawn between intelligence then, and travel. If for instance, it takes 10 days to cross an ocean in a ship, you might consider the option of building a much bigger ship. If you build it to a length of half the width of the ocean, then the same trip would take just half the time. A ship the full length of the ocean would take zero time to make the transit. However, as any map maker can tell you, a map the size of a mountain doesn't provide much advantage.

Now we are getting close to what looks like a good general description of computation. The building of abstractions that are easier to navigate than the objects they abstract. If there are elements within an object, environment, or situation that are important to an observer, and there are elements in that same domain that are unimportant to the observer, then it is reasonable to assume that an abstraction, a reduction, a selective compression can be built such that navigation through the abstraction is more efficient than navigation through the original domain. Colloquially, we can say that an abstraction must therefore be smaller than the domain it abstracts.

However, we frequently fantasize about perfect understanding. As we build better and better abstractions, we work towards this goal of complete and absolute knowledge. All the while, the abstraction grows. More and more of its size represents administrative structure of the abstraction itself (spacers and associate-ers). As an abstraction matures, another factor increasingly contributes to its size; a model of the observer in reference to the target domain. In fact, any realistic measurement of the size of an abstraction must include the computer or brain both constructing and navigating the abstraction. Because we humans come with computers pre-installed, it is common to see abstractions as separate from the machinery that computes on them.

For these (and other) reasons, it is quite possible for a map to grow quickly to many times the size of the domain being mapped. So we must re-state our definition of computation. A simple size comparison between abstraction and abstracted no longer seems appropriate. What matters more, it seems, is the relative expense of building and executing upon the abstraction as set against the expense of executing the same measurements on the original native domain.

There is another complication that must be considered, this being the value of the knowledge that is extractable from a domain. Abstraction construction, navigation and processing costs need only be less then the same effort applied to the extraction of that knowledge from the native domain.

Hopefully, the reader is beginning to see the many parallels connecting what we call computation and evolution. Both are processes. Both utilize finite temporary structures that feed off of themselves to build other finite structures through time. Our understanding of both computation and evolution seem to be limited by our natural focus on the temporary, the here and now, on species and executables, when the larger phenomena, general complexity handling and abstraction maximization are largely ignored.

[more to come]

Randall Reetz

Evolution: Optimizing a Definition of Fitness

2009-12-07T10:41:00.000-08:00

We think of evolution as a process that optimizes organisms (things) through the filter of fitness. Fitness as means - the species - as end. I have long suspected that this interpretation is wrong-headed, and results in conceptual mistakes that ripple though all of science, blinding us to much that could be understood about the Universe, process, and the basic shape and behavior of reality.

So let's flip it. We'll instead, re-frame evolution as a process that uses things (organisms, species, systems, ideas, etc.) as a means (channel, resource, armature, vehicle) for the optimization of fitness. From this inverted vantage, optimizing the criteria of fitness is the goal – species, nothing more than a convenient means.

It always feels wrong to talk of evolution's "goals". Certainly a universe doesn't start out with a plan or agenda. Things like plans and agendas are only possible within advanced abstraction apparatus like a brain or computer. Universe's start out simple and chaotic. Only chance causal interactions played out amongst a universe sized accumulation of matter and force over ridiculous amounts of time will lead to the types of rare and energy demanding structures that can "think" up things like plans and agendas. So when I talk here of "a process that optimizes", I make use concepts and terms that are more generally associated with self, ideation, and will – with the products of advanced abstraction machinery found in humans and maybe eventually in thinking machines. But what I mean to convey is the direction of a process. That processes have direction and that direction is (or can be) independent of the types of advanced computation necessary for things like planing and intent is in fact, the exact conceptual jump that the idea or discovery of "evolution" demands. Evolution = direction without intent.

The directionality we see in evolving systems (all systems) is blatantly and obviously non-random. Our job then is to understand, explain, and ultimately, exploit this understanding. Because we humans have trouble imagining non-random direction coming from systems without a brain, a soul, an agenda, we are left with a slim set of emotionally acceptable options; anthropomorphizing the universe and evolution, inserting a deity, or simply rejecting evolution (or reality) out of hand. The non-emotional option, the science option, evolution, recovers from this dissonance through the application of inductive logic, physical evidence, and frankly, by simply offering a emotionally dissonant option.

The thesis of this essay is the suggestion that evolution might be agnostic to optimization of species and is instead simply using species as a conduit for the optimization of this thing called fitness. That fitness might in fact be more real, and species, ethereal.

This entire domain is so fraught with potential miss-interpretation. I feel a constant urge to over-explain, to be extra careful, to make sure the reader isn't thinking one thing when I mean something else. For instance I feel a need to define the term "species", especially because I am using it in a more general way than is usually required within the boundaries of its original domain, biology. This is because I am convinced that evolution is a universal process, that it has nothing in particular to do with biology or life, that it happens in all systems, all of the time, an unavoidable aspect of any reality.

So when I write "species" I mean the thing or system that is "evolving" – the animal, the planet, the culture, the idea, the group attitude in line at the post office this morning. And in the context of this essay, I use "species" to mean the thing upon which "fitness" acts (as judge, jury, pimp, or executioner). Species is the thing, fitness the criteria that molds the thing.

But by this definition, species is corporal and measurable, suggesting that fitness is… is what? If we are talking about something, shouldn't we have some way of examining it, measuring it, comparing it, holding it in our hands, flipping it over, squeezing it, spitting it open and looking at its parts? That seems a more reasonable proposition for species than for fitness.

We like to think we can man-handle a thing like species, take it to the lab and do lab things. But maybe that is more illusion than truth. We can dissect a frog, but that particular frog isn't really the species "frog". The species "frog" is an average, a canonical concept, a Platonic solid, a moving target, an arbitrarily bounded collection, a gelatinous arrow through foggy potentialities.

I was in route to show that "fitness" is a real thing, but all I accomplished was a picking away at the real-ness of "species". Maybe that will end up being more helpful anyway. The colloquial image of species, even amongst evolution theorists has always seemed more visceral, more thing-like than fitness. We point to a single nervous animal on the savanna and declare, "that is gazelle". Worse, we often fail to make a semantics distinction between that declaration and the categorical; "gazelle is that". That fitness is a much harder thing to point to, really doesn't mean it is less real, or as I have shown, that real-ness applies to either.

Now that I've reduced both species and fitness to the realm of concept, it should be easier to argue my thesis.

Even at the concept level, "species" is a thorny concept fraught with pedagogy and hubris. It is hard to look at a penguin, a porpoise, or a planet and imagine something more amazing, more evolved than its current form. Which probably goes a long way to explain why we have a natural tendency to overlay onto the concept "species" notions of perfect form, of an apex, a pre-determined goal. But this certainly has less to do with species and more to do with the limits of our cognitive facility. It would be absurd to assume that this particular now is in some way special, that forms are complete and that we just happen to inhabit the planet just at the point when evolution has finally and completely finished its big 14 billion year project.

OK, the apologies have been met out, the slippery territory marked, the standard arguments abutted, the inconsistencies delineated, the usual misinterpretations admitted. These are standard precursors to any serious discussion in the study of evolution and bare witness to both the complexity of the subject and the apparent inability of the brain to readily make sense of its many dimensions.

So why should I want to reorder the relative hierarchy of fitness and species? For one, I have always felt the standard Darwinian definition of evolution to be a bit circular. Wow, before that comment ruins my standing, I had better get to work defending Darwin. I am a "standard model" realist. Darwin got most or all of evolution correct. Especially if you restrict your focus to biology. Darwin is the dude! The positions I detail here are meant as additions, as icing on the cake Darwin baked. But Darwin built his theory around life and his bio-centrist focus on evolution restricts and warps the applicable idea-space it scopes. I always say that Darwin explained the how of evolution with regard to biology, and that I am interested in the why of evolution with regard to all systems.

To restrict the scope of evolution to biology, is to somehow draw a line in the sand between life and not-life, a special sauce within life that categorically separates it from all other systems. I can't find that line. So I am left with the responsibility of understanding and defining evolution as a domain independent attribute of any system or system of systems.

Structurally, all systems are ordered as hierarchical stacks. Each level receives aggregate structures from lower (previously constructed) levels and produces from these, new super-aggragates, that it in turn passes to the next higher level. That this process of aggregate layering is historically dependent is obvious. The non-obvious mapping is to energy. The lowest levels of the hierarchy, the earliest levels, represent high energy processes, energy levels that would rip apart aggregates at higher levels. In this universe, all systems are built upon the aggregation processes laid down in the earliest moments, aggregations that occur at the upper limits of heat and pressure – strings, quarks, sub-atomic particles, atoms, molecules. Each corresponding to a matching environmental energy level, an energy level that is cooler and less pressurized than the ones that came before it. The universe gets cooler and more dispersed. Always. The growth of complexity, evolution, is dependent upon this predictable and unavoidable dissipation of energy over time.

Those who would argue that life is special, that evolution is exclusive to it, well they are obligated to draw a definitive boundary between life and everything else, and because life, like everything else, is dependent upon the historical layering of aggregate systems, will have to draw that line historically. They will have to show a moment in time before which there was not life or evolution and after which there was life and evolution.

There are many ways to define life in order that such a line could be drawn. If you say, as most do, that life is that set of systems that incorporate and utilize both R and D Nucleic acids, well there is surely some moment in the past which would accurately delineate those earlier systems which didn't have both RNA and DNA, from the later systems that did. Such a definition is some what arbitrary, but all categorical definitions are. But if you seek instead to hinge your definition of life to the process of evolution, then you are faced with a tautologically intractable problem. Either you must accept the nonsensical proposition that the universe started with RNA/DNA preformed, or the more rational causal proposition that evolution is independent of and proceeded biology, preparing over vast periods of time, the aggregate ingredients necessary for the super-aggregate we call life. If you insist despite this logic, that evolution is a property exclusive to biology, then you are left with the thorny problem of defining aggregation processes happening simultaneous to and independent of biology. Processes that continue to produce atoms, molecules, stars, planets, galaxies, cultures, ideas, sand dunes, ocean currents, etc. And, you must also show how these continuous and omnipresent processes are qualitatively different when they happen outside of systems that use RNA and DNA from those that do. But that isn't enough, you must also show either that no system after biology will ever evolve, of that the entire future of evolution will happen within the confines of biological systems.

The evidence and logic weighs overwhelmingly on the side of life being an arbitrarily bounded category, and evolution defining a process unbounded by domain, history, or complexity. Both of which are difficult concepts for humans to accept. We like to think we belong to a category made exclusive by some secret sauce, some magic that applies in some measure only to life, and which has reached its zenith in the human form or spirit. We like to imagine evolution to be that process that shaped the shapeless gasses of primal soup into the perfect form that we now enjoy. Wow. The ego and hubris drips and pools.

If I may, back to fitness. The above arguments are crafted to shake we humans free of our innate bio/human/self centrism and to show how such hubris works to emphasize contemporary corporal form over timeless ephemeral process, placing a sort of artificial spotlight on species and downgrading the in contrast, fitness. Its only natural. And it is wrong.

The tendency to focus on species is easy to understand. If you are looking at an animal and asking questions about evolution and process it is only natural that the scope of your thinking would be restricted to that animal, that species, that family of life and its struggle to survive. Even when you back your self out to a vantage wide enough to include all of life, the full fan of Linnaean Taxonomy over the full 4.5 billion year crawl, the focus is still thing, still survival, still some sort of cosmic engineering project. It is only when you back all the way out, when you look at all that is, the entire Universe, every moment since the big bang, life and the stuff between, in, and of it, that you might be forced to ask questions big enough to frame the why of evolution.

The why of evolution has to be big enough to comfortably hold all change, all systems, any aggregate and any aggregate chain, not just those that succeed, not just those that are fit, not just things that can be called things… everything! Any process that explains the existence of one system should also be able to explain every other system. Universality, at this depth of scope demands a bigger reason than can be explained by the concept "species". Darwin's big how in biology then becomes a local mapping to a specific domain. It isn't wrong, it just isn't universal. You can know everything about pianos, but won't really understand music until you know enough about enough instruments that you begin to see the formative patterns that unite, from which all instruments are informed.

Species, be it a valid concept at all, must be but a subset, an example, a non-special representative, a member of a perfectly inclusive, and domain independent set. Sets that include everything are not informative as a set. So we look elsewhere. That species, as a label, pointing to the subject of evolution, can equally be applied to any thing, forces us to look elsewhere for that which explains the big why of change. Change must not reside in thing, product, tailings, result, or even detritus. If the big why isn't thing, but has to explain thing, any thing, all things, than the big why must be a process or action or modifier or pressure. Some common attribute of any change regardless of domain. What process is agnostic to domain?

In a word, entropy. In an attempt to determine the maximum work that could be extracted from any source of energy, steam era engineers teased apart the relationship between source and output and found an intriguing and strangely universal leakage. Energy, when used, degrades, diffuses, is no longer as useful or available to the original process. When scientists discovered the same leak, this time with structure, a strange universality began to appear. Energy and information, force and structure, an unexpected symmetry. Then Einstein revealed the exact relationship between energy, time, space, and mass, allowing thermodynamic transforms on all physical terms. Despite initial objections by Stephen Hawking (and others attracted to the notion that nooks and crannies of the universe might provide respite from the second law's rigid causal prescriptions), Leonard Susskind and others have brought both the quantum world of the impossibly small and the black hole world of the impossibly big, together under a shared entropic umbrella. What we are left with, like it or not, is a universal. A universal that is universal to all physical domains and dimensions, regardless of scale. Wow. That doesn't happen very often in nature. That hasn't happened in science. Ever. Significant?

In his 1927 book, The Nature of the Physical World, Sir Arthur Eddington, put it this way:

"The law that entropy always increases, holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equations - then so much the worse for Maxwell's equations. If it is found to be contradicted by observation - well, these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation."

Any theory or assessment of evolution that is not written in response to thermodynamics, information theory, and entropy would seem to be a theory not particularly interested in validity. That the laws of thermodynamics and evolution both direct their unblinking stares upon the domain of change would seem to me an invitation to at least begin to consider the possibility of a concerted union between the two.

[more to come…]

Randall Reetz

The Life And Times Of Your Average Paradigm

2009-11-27T17:31:00.001-08:00

Systems are in constant state of flux, they change all of the time, over time, and even when they don't or can't, the environment around them changes in response to their behavior or simple presence.

Systems evolve. The super-systems in which they live, evolve. It's what happens, it is the only thing that can happen. Stuff constantly adjusts its behavior in response to the stuff around it. And things can not help but mess with the things near them. Change is inevitable. But more than that, change has pattern that can be teased out, measured and described.

These patterns are generalizable and can be found in all systems regardless of domain. All systems evolve. All evolution is similar. What Darwin described in biology, once generalized, can just as accurately describe the interaction of gases or the layered persistent structure of ocean currents, or the way I came to these thoughts and decided to write them down.

An interesting aspect of systems is the way they are made up of layers of subsystems each bound by unique structural and behavioral rules, and all of this can exist simultaneously across many dimensions. These 'layered grammars' are perhaps easiest to see in language, where symbols are assembled in ever more complex aggregates (phonemes, words, phrases, sentences, paragraphs, themes, sections, volumes, collections, etc.), each governed by its own rules of construction. Of course an utterance can be parsed by the layered rules of symbolic grammar (as above) or any other set of layered grammars… take for instance it's semantics or meaning.

But what interests me today is the life span of a system. Though it is problematic to do so, it is often useful to define, at least loosely, the beginning, middle, and end of a system's life span, the arch of its development through time. Individual humans have life spans of course, and from a more distant vantage, so too does a culture, and though the arch of of these classifications hasn't run its course, the human species. From ever wider vantages, one can talk of the stacked life span of hominids, great apes, primates, mammals, chordates, multi-celled animals, eukaryotes, and biota itself.

What interests me here are the patterns can be teased from any life span? More to the point, the patterns that are universal across all life spans. What, for example, is there that can be accurately, and predictively said, of the difference between the first half and the second half of any life span? What is it about the beginning of an individual human's life that is similar to the beginning of the life span of the human species or the beginning of the life span of life itself?

A reasonably robust set of these life span meta-patterns might work well as a way to better define the boundaries that give meaning to the most general concept; "system" ("category", or "thing").

But what I find most valuable about this strategy, is the possibility of predicting the relative age of a system without ever having witnessed the full arch of a life span, as example. Is the system of focus in its infancy, is it a teenager, or is it middle aged, old, or nearly dead? Are there reliable parameters that can be mapped over a system to help us determine such things? I am convinced there are. My confidence in this guess stems from the dramatic symmetries that have been exposed over the past century and a half in the fields of information theory, thermodynamics, classical physics, and quantum dynamics, linguistics, and logic. What this work has exposed is equivalence transforms that show causal connections between energy, mass, time and distance, and importantly, information. This overarching symmetry hints at symmetries in systems themselves and in stacks of systems, and the way systems change through time.

It is this knowledge these profound symmetries, uniting such apparently separate systems, that best describes the most important contributions of the last century of scientific exploration. Wielding this knowledge, we can use the same language and logical tools to examine any system, be it physical, behavioral, or descriptive, or cognitive.

The slippery and ghostly similarities we have noticed across domains, the ones we previously chocked up to metaphor, have been shown in fact to be causal and real (and we have the math to prove it!).

It is frustrating, that the topics I am most interested in, require the assembly of so much preliminary conceptual scaffolding. All these words, and I haven't even gotten to my main point. Here goes.

I talk often of what I call "productivity paradigms". They are ethereal and mercurial economic entities defined by some factor that gives rise to previously unachievable levels of the value of an average hour of labor.

As systems, productivity paradigms should avail themselves to the kinds of 'life span' parsing we would apply to any system. So, we can ask things like: can we determine the relative age of a given productivity paradigm?

And, is it possible to can we know this from the rising or falling rate of growth resulting from that paradigm?

Are these questions, addressed as I have, to a subset of systems, or are all systems productivity paradigms, making my questions universally applicable? Is there such a thing as a non-productivity paradigm? Can a system ever become a system if it doesn't follow some sort of life-span arch? Is productivity, as I suspect it is, a perquisite for the existence and persistence of a system?

Lets assume it is. Now what? How can we extend this assumption in order to acquire something salient to say about a system?

Productivity Stalemate: Post Industrial World Caught With Its Pants Down

2009-11-18T15:09:00.000-08:00

If a hundred trillion dollars* falls down in a forest, and nobody has anything to spend it on, does it make a sound?

In what might be the most embarrassing moment ever completely ignored, the post-industrial west is missing the greatest opportunity… ever.

It snuck up on us, yes. But that doesn't make it any less embarrassing. It still hasn't been acknowledged, sure. But that doesn't mean it hasn't (isn't) happening. What happened? Well, while we weren't looking, the so called second and third world made some money, a lot of money, and they came running to the west to spend it. Why wouldn't they? We're the experts. We know how to put big money to work… right?

Unfortunately, and at the same time, we, the west, the so-called 'first world', well, we slammed into what I call the productivity wall. Sure we were (are) way ahead of the rest of the world. But we aren't moving forward, and haven't for about 15 years. The lack of upward motion has caused the unthinkable to happen – we ran out of things to productively spend money on. We don't have reasonable investments in which to sink new capital. We ran out of ways to ingage new forms of production at the pace demanded by all of the new capital finding its way into our securities and investment markets. It's as if we never in our wildest dreams anticipated the second and third world adding significantly to the global capital pool. We outsourced. We ran up unheard of trade imbalances. We sold bonds by the trillions to China. The world changed. It was right in front of our noses, yet we never saw it, never bothered to model its implications to our increasingly outmoded economic models.

Pants well down. The whole world watching. Just standing here. Clueless.

Money flowing in. Unprecedented quantities of new capital. Accelerating. And here we sit – without any 'shovel ready' places to invest it.

What? you ask. How can this be? Surely there are people who would love to use someone else's money to build something and sell it. Right? And yes, the demand for capital is always there. There is always someone with some big plan and a need to go out an buy some parts, a factory, and the right people to run it. But what if nobody on the other end of the assembly line has any money to buy that new thing you just spent capital to produce? Or more to the point, what if there is nothing about the resultant goods or services that catalyzes the production of other goods and services? What if the only remaining places to spend capital don't make it easier and cheaper and faster to make other things. What if in effect, the existence of your factory and the widgets it produces, doesn't result in any real growth in consumption or wealth? What if you just spent good money to make things that the economy simply can not afford to purchase?

Unthinkable. Or is it? The value of currency, the purchasing power of the people who earn it, these are determined by productivity. Productivity is just the value of an average hour of labor. Productivity changes over time. Usually it increases. Sometimes, as when a new and powerful infrastructure is established – mechanized farming, electricity, telephonic communication, global integrated transportation – it increases in grand leaps. In between these technology driven epochs of growth, there are periods in which the full landscape of opportunity within that domain are exploited. Growth during these in-paradigm epochs slows as the possibilities made possible by that advancement approach its limits.

We in the west have not jumped productivity paradigms in a while. We are running out of productive ways of exploiting the current set of infra-structural advantages. As a result, an odd thing happens, an unintuitive thing happens, we find that throwing more fuel in the economic fire no longer buys greater productivity.

Sure, we can continue to spew out ever greater quantities of goods and services, but if things we spew do not increase the value of that all important average hour of labor, there will not be more money available to consume to our new levels of production.

Production does not equal productivity. Consumption does not equal productivity. Production plus consumption does not equal productivity. Productivity, the value of that average hour of labor, is determined by the effectiveness of the infrastructure.

The classic example of a productivity jump is the introduction of mechanized farming. Mechanized farming has allowed such yield (per hour of labor) that we can afford to feed all of the people with less than 4 percent of us spending our labor on food production. This single fact freed up the remaining 96 percent of us to do other things.

Unfortunately, just as the rest of the world got to the point where it could contribute capital fuel to our economic engine, we ran out of ways to put that capital to productive use.

Holly crap! China and Brazil and India and the Philippines and, and, and, they all have some extra money to pour into global capital markets, and just when they do, we run out of productive ways to spend it!

Has any greater opportunity ever presented itself to a people unprepared to take advantage of it?

So what did the west do instead? We faked it. We gladly accepted the money and spent it on crazy layered real estate loan stocks and layered stock schemes that were nothing but new plays on the same age-old shyster speculation scheme that has substituted for capital investment every time real productivity is elusive. And the real estate boondoggle isn't the first of our fakes. We started with energy deregulation and when the inevitable crash happened there, we moved quickly on to the dot-com boondoggle, and when that crashed, we faked it again with real estate and "mortgage backed securities". And now that this crash caused a global economic shock wave leaving double digit unemployment in the strongest economies and a fallout into the third world we are only now beginning to acknowledge.

And how did we respond to the mortgage securities crash? By faking it again of course. We said, "Sure we acted like shysters, but that was the past, we have changed, give us your money and we will spend it wisely this time!" And what wise thing did we do with that money? Did we go looking for the root of the problem? Did we attempt a wholesale rethinking and scientific understanding of the economy and what makes it work? Hell no! We sent quants back to their million dollar basements and told them to be better, bigger, and faster shysters! And what they came back with was a thing called "micro-second trading".

Micro-second trading is stock trading like any other stock trading, except that it is done and can only be done by high speed computers with exclusive access to the main trading computers operated by the various trading firms (NYSE, NASTEC, NIEKO, etc.) under the auspices of the Federal Trade Commission and other international policy bodies. Micro-second trading exploits a loophole in trading regulation that allows certain exclusive trading organizations access to trading data before the trades are made. Yes you read that correctly. Insider-trading on steroids. The loophole allows this peak into the future before it happens but only for a fraction of a second and only of course to those few companies who have somehow gained physical access to space in the computer server farms that operate the stock exchanges. Imagine what kinds of profits on futures trading you could make if you knew exactly what the future was?

When you read that the trading firms that lost the most money at the end of the real estate fiasco are currently giving out hundreds of millions of dollars in bonuses to their employees, and you wonder how they are doing it, where they are getting the money, well now you know.

And all of it, each of these fake investment schemes, one after the other, happened exactly and only because we, the most powerful, most educated, most economically potent people who have ever lived… well, we ran out of ideas. We came to a wall. We hit the end of the current paradigm and either couldn't figure out how to jump to the next one or weren't as a culture prepared to think in paradigm jumping terms.

I suspect that humans are just not very smart, that in mass, we are limited in the exact ways that the current circumstance and our reaction (or lack there of) so dramatically illuminates. That so many of us exist. That all of us are so well educated. That we live in and by so protected and fecund an infrastructure, and that not one of billion of us were not in a position to see this happening and plan around it tears at credulity.

Or maybe we are all of us so greedy and shortsighted that misfortunes like this happen despite the obvious cognitive capacity of our species? Either way, whether we are more in it or of it, we have to react to it. We have to do something to get productivity up and running again. And to do this we have got to build an understanding of economic systems big enough to include and predict the foibles of which we have recently been apart. Until we have such an understanding, we will not be able to avoid the future missteps as destructive and anti-productive as the bubble/bust cycles that have so plagued the last 15 years.

And what would it have looked like if we had been prepared to productively spend this windfall of new investment money rushing towards us? What, capitalization opportunities, had they been in place, would have allowed us to avoid the malevolently inventive 'creative financial products' that led directly to the string of bubble/bust cycles that have so devastated the global economy? What, one might reasonably ask (though few have) would or should the next (and long overdue) productivity paradigm look like?

I have invented a word, "productclivity" to describe a general framework of a scaffolding of a shadow of a description of an outline of the criteria that might be used to judge a new productivity paradigm. Productclivity is the propensity of a system to produce productivity. It is to economics what fitness is to evolution. In the longest run of time, it doesn't so much matter if you have a good set of legs as it matters that you have a good set of leg building algorithms… a good set of adaptation optimization algorithms, even better. Same goes for economic systems. Any successful scheme (mechanized farming, electric power grid, broadcast television, general purpose personal computing, cell phones, etc.) pales in productclivity comparison to things like public education and national or international research and development programs. Such systems tend to produce a continuity across productivity epochs.

Pop-economists and economy pun-dents are fond of terms like "the multifier effect", which is meant to describe investment and business activity that causes an out-fall of other investment and business activity. Investments in transportation and education and communication infrastructures are said to have this special something that produces productive systems that could not have been anticipated and would not have existed in their absence.

So lets look at the current paradigm. We already have mechanized farming. We have a decent communication system. We have a world class materials market and the transportation system to get those materials anywhere in the world in less than a week (a day if you are willing to pay for air freight). We have a decent data network (the internet) and the gateways, switchers, data storage and servers to make it all zing. We have programmable computers built into the fabric of every part of our daily lives and the things that make our lives long and rich. Through trickier and trickier programming we have automated our manufacturing, factories have become robots in them selves. The result has been a level of productivity unheard of in human history. It has given us time to screw around and the products and services to upgrade our "down time" to the level of "entertainment" and "leisure". What is left? What more could there be? The simple fact that the question seems so reasonable is evidence that we are in this particular problem for the full count.

But there are hints and there is hope that more might come, that there is still something of worth, something, "Not unbecoming men that strove with Gods" (Tennyson). We have the machines, the communication channels, the materials, the transportation, the manufacturing and materials, the educated labor, the social infrastructure (or, um, a bill of rights anyway), and the standard plumbing, mini-malls, and big box stores… everything one might need if one was packing for a trip to next-paradigm land. Which is another way of saying that we know and can list all of the things that make up the current infrastructure, all of the things that work, all of the things that brought us this far, all of the things the next productivity paradigm will need, and won't be.

And this is where I am obligated to insert a cautionary explanation. New paradigms do not, though they are frequently accused, replace that which came before them. But wait, you might say, everyone can come up with with a counter-example or two. Horse drawn carriages were replaced by automobiles… right? Paper mail has been replaced by email (or is doing a good job trying). The computer has replaced ledger sheets. Yes, yes, and yes. But none of these qualify, in my estimation, as paradigm shifts. The fact that they look like paradigm shifts, only results in confusion. In all three cases, the introduction of a new tool, process, or technology expediates or in some other significant way, improves a solution that already existed before. The car, like the buggy, accepted human passengers and transported them from one site to another. Same transform can be applied to most so-called "paradigm shifts". Better, ain't different. Paradigm shifts then, are caused by solutions to problems more fundamental than the problems that structure current solutions. If, for instance, an affordance was invented that gave people all of the benefits of being somewhere else, without actually being transported there, well that technology would qualify as a true paradigm shift.

Does double digit growth in second and third world economies mean they have jumped paradigms? Scooped the first world? Beat us at our own game? N0. Not even close. Lets not loose perspective. No need for hysteria or blame. Non-western economies don't have to jump paradigms, they have only to adopt the paradigms the west had already defined and refined. Their economies are growing fast, true, but this is the simple result of the efficiencies and advantages of moving their production and infrastructure up to modern industrial levels and then amortizing these advantages across the huge number of people (hours of labor) at their disposal Nothing magic, just productivity gains multiplied across huge populations.

In the west, we face a task far more complex. We can not play the same catch-up game being played in the 'rest of the world' (ROW). We already played that game… played it to the limits possible within this paradigm. No, now have to invent the next one, the next (productivity exploding) paradigm. Nothing else will work. This should be obvious by now. Even the notion that we could tap into old paradigm gains in that part of the world with rapidly growing populations of consumers is wrong headed and won't work. Yes, the global consumer base is expanding, yes this is happening in the second and third world. Yes the numbers are astonishing. But in order to sell to the rest of the world, we have to produce at efficiencies only allowable through the use of discounted ROW labor and materials rates. The only way we can get back to growing the rate of growth in the first world, our world, is by playing the paradigm-shift game.

And what does that mean? Given the current state of the first world, what are the parameters that would define a true paradigm shift? We start with the obvious statement; the next paradigm can't be anything we already have or do. More than that, it can't be an extension of or improvement on what we already have or do. It has to solve problems that are more fundamental to, that actually cause, the problems that provide the market and demand upon which the current economic paradigm feeds.

But before we go there, let's add another few items to the "how to tell a real paradigm shift in productivity from simple extension of the current paradigm" list.

First way to tell if what you are doing isn't a true solution is when you notice that the more you do the less you get out… this is the law of Diminishing Returns. When gains in productivity become more expensive, even while the energy or investment required by a new scheme increase. Shale oil, right-now manufacturing, team building exercises, on-line shopping, hybrid drive technology, cloud computing, web 3.0, ultra-sized wind turbines, commuter freeway lanes, customer relations management software, etc. These are all great examples of what I would call skimming; finding ingenious ways eek out the last few percentage point gains available within the current paradigm. Where a new paradigm should result in fold increases in productivity, skimming only yields percentage gains. These drop off to nothing as the full potential of that paradigm reaches its natural zenith.

And then there is the law of scales. This happens as a paradigm matures, when all the easy problems have been solved, and the only remaining solutions end up being solutions that work in ever smaller and ever more isolated domains. Come to think of it, scale is a good criteria upon which to compare true paradigm shifts with the range of lesser influencers. A true paradigm shift will expose entirely new markets, new sources, new methods, new materials, new activities and uses… solutions that scale both vertically and horizontally without apparent limit (at least at first). Stove-piping, the tendency of solutions to only work vertically and for these vertical markets to become narrower and more isolated over time… these are good indicators that the current paradigm is greying, robust, reaching maturity… that all of the easy to reach has been picked, that the investment in taller ladders can not be amortized across any other markets (fruit picking ladders have become so specialized that they are useless to firemen and painters).

In converse, true paradigms tend to be expansive, to open things up, and as I have suggested earlier, they tend to result in what many call a "multiplier" effect; from their seed, other opportunities bud and grow and multiply simply because the paradigm provides such a rich foundation for effective novelty.

OK, back to guessing. What will the next paradigm be? If it has to rooted at a deeper foundational level than current solutions, how much deeper? What does deeper mean?

In science, the trend has been towards theories (understandings) of the laws of nature, and for ways these laws are inherited from yet deeper and more general layers of meta-laws. Work in pure information theory is providing what might eventually work as the foundation of all, indeed any, natural system. Understanding the deepest layer(s) of nature allows one to predict, indeed derive, all of the laws above it (and show why they are the only possible laws). In business, this deeper understanding is phrased "knowing your market". Same thing. The deeper you tap into the causal strata that supports a system, the more control you have over and knowledge of the whole system. The deeper you tap into the causal strata, the more of that system's complexity becomes salient and controllable. In science this phenomenon is called "elegance". A theory is elegant to the extent that it can comfortably inform and predict the behavior of a large number of other theories or theories of theories. Elegance it is argued is a basic attribute of any evolving system. The universe has evolved, therefore it is fundamentally elegant. Any physics, any any descriptive abstraction of the universe will therefore be accurate to the extent that it is an accurate analog of the elegance of the system it describes, the universe itself, and by extension, the evolutionarily stacked layers that describe its history. But getting to elegance isn't easy. The deeper one digs into any historical or causal strata, the less like today do things appear. The promise though, is that an understanding gets more useful and profound the more deeply it is rooted. It might be easier to study legs, but you can get more information faster if you study the DNA snippets that propagate appendages across all of biology. Not only that, but an understanding of DNA in general will allow you to know things about legs that allows you to know things about ears and hearts and intestines and the production of enzymes and metabolism and growth and reproduction and evolution and information and energy and ultimately the topology of causality itself, the arch of possibility.

But digging deeper comes at a cost. Armed only with a good ruler and notebook, you can learn lots of stuff about legs, if you want to go the next bit and understand genetics, you had better build yourself a bunch of awesomely fast computers connected to some awesomely big data storage devices. And you had better find more and more robust ways of handling greater and greater amounts of complexity. The end result might be elegant descriptions but that elegance comes at great cost. The cultural and physical armature humans have had to build, in order to reach back into the causal structure of elegance is anything but elegant. Look for instance at the Large Hadron Collider. This machine is so complex that some theorists have questioned the likelyhood that it will ever actually work or work long enough for to acquire any reliable or demonstrable and supportable data. A whole branch of logic is likewise concerned with the limits of knowledge and thus the limits of abstraction. The data stream flowing from the fully operational LHC will exceed 300 gigabytes per second. Just mastering the technology and logic to store a stream that fast and wide is a challenge no previous generation could have met. Sifting through the resulting mountain of data requires logic armature of unprecedented complexity.

All of the low hanging fruit has been picked. We have measured all of the easy to measure stuff. We have stored and organized all of the easy to measure, store and organize measurements. We have built all of the equipment that that is easy to build. Even most of the stuff that is hard to build. We are increasingly, as a species, up against a complexity wall that keeps us from progress in almost every field of human endeavor.

The next productivity paradigm will have to have something to do with breaking through this wall, something to do with finding some understanding of the very shape of complexity and using that understanding to build a stable tunnel under, ladder over, or door through the complexity that vexes progress today.

Among the myriad of discoveries made over the past century, three of the most profound are the standard physical model, information theory, and evolution. Together these describe the relationship of matter to energy and to space and time, the limits of information, the equivalency of energy and information, the way both degrade over time, and how this guarantees the direction of time. All of which puts bounds around and relates reality and our abstractions of reality. Physics and cognition. The territory and the maps we can make of it. And, importantly, the physicality of maps themselves. But the complexities involved in the manipulation of this level of understanding pushes humans to the limits of their capacity (and beyond). Fewer and fewer of us have the cognitive wherewithal to make effective use of what is known.

What is needed, what is desperately needed is an automation of discovery and cognition. We need machines that do more than just help us acquire and organize the measurements we take. We need machines that work along side of us, extend cognition into realms beyond the easy reach of human minds. We've automated everything else. Cognition is all that is left to automate.

This is the next productivity paradigm. Like it or not, and from personal experience introducing these topics, most people decidedly don't, we have to push forward towards the automation of cognition.

Until then, and in the event we just can't stomach the idea of machine cognition, our only viable choice is to redirect the capital we can't viably spend – and spend it on infrastructure projects in the second and third world where in-paradigm solutions still result in productivity gains. Not to make money mind you, but to accelerate the flattening the world's markets and ready them for the eventual global jump to the next paradigm (when we can stomach it). This is especially true when that money is mostly from the emerging world in the first place. We can't fake it any more, the fake we've been doing is killing the world's economy, the fake is destroying our hard won reputation as innovators and capitalists, the fake is defacing the very idea that is capital.

Randall Reetz

* The International Monetary Fund estimates current Gross International Product (the annual sum of all human labor) at about 71 trillion dollars and rising rapidly. The greatest growth in relative wealth comes of course from the third world, where wealth building is more rapid. Because the vast majority of the world's population hails from the second and third world, small increases in individual wealth result in huge changes in gross wealth. As a result, the new money in the global investment system is coming from the third and second world. The question, the problem, the crisis is the first world's inability to make productive use of this new money.

Ford Doing Better Than Expected (Thanks GM)

2009-11-17T20:42:00.000-08:00

I have been watching and reading the news about Ford's better than expected financials. Each of these reports compare Ford's success to the demise of GM, but none of them link the two. Look, people still need to drive around, and cars still wear out. Which means new cars need to be built and sold. Cars not being sold by GM are cars being sold by other manufactures. It is that simple. Hydraulic really.

In the 1940's an economist named A.W.H. (Bill) Phillips built a hydraulic computer that pumped colored water through system of tubes and reservoirs, controlled by metered valves, and cams to simulate national and international economic monitory flow. It was called the "Moniac".

Less than twenty Moniacs were built, but they were purchased and put into active service by some influential organizations including the British and U.S. governments, international banks, and research institutions like Harvard and the London School of Economics (which subsequently hired Phillips as a professor). It was built as a teaching tool, but found to be an accurate enough predictor of actual economic activity that it looks as if it was employed by governments to play "what if" simulations and inform monitory, fiscal, and tax policy.

The tie-in to Ford should be obvious. Fluids are incompressible – no mater how much pressure you apply, they always take up the same volume. Push a little over here and the fluid has to compensate by leaking out somewhere where the system offers the least resistance. When people hear that a car company is struggling to such an extent that they are shuttering entire devisions (Saturn), they wonder who will honor their new car's warrantee, and they go elsewhere to do their car buying. That elsewhere is foreign manufactures and if it isn't, it is the other domestic manufacturer, Ford.

GM consumers are probably more "buy American" than other auto buyers. Additionally, US reporters are not as likely to track GM exodus to Toyota, Nissan, or Volkswagen.

The comparison of Ford to the other big US manufacturer is too seductive a sound bite, especially considering the government bailout of GM.

But wouldn't be nice to at least ask the question… Is there a connection perhaps, between GM's troubles and Ford's (comparative) success?

Come to think of it, wouldn't the monetary-flow-as-hydrodynamics also work just as well as an explanatory model when applied to the last three boom/bust bubbles (energy speculation, dot-com evaluation, and the securitized real estate boondoggle)? All three came in rapid and linked succession as the investment pressure flowed from the failure of the previous to the "success" of the next. All three can be traced to brand new second and third world money being invested for the first time in first world markets… markets without the requisite productive machinery to support the value of the investment being heaped at them.

And that my friends is as salient an explanation as you will ever find for the reason that booms both happen and why they go bust. New money coming unannounced into an old market that can not effectively scale its productivity to the demands of the new capitalization levels.

A boom/bust event is indication of the need for a new production paradigm. A boom/bust cycle says; the present system can not be scaled beyond its current level… adding capital beyond this current level will not yield commensurate growth.

At such times, the whole system is vulnerable and this vulnerability will not go away until a new technology or infrastructure usurers in a bridge to a new paradigm in which new capital will effectively yield new productivity.

Randall Reetz

Some background info on the Moniac.

YouTube video clip (hilariously confusing)

http://www.youtube.com/watch?v=k_-uGHWz_k0

PDF White Paper

http://www.rbnz.govt.nz/research/bulletin/2007_2011/2007dec70_4ngwright.pdf

Discovery Channel PDF

http://technology.open.ac.uk/t...bissell/Phillips.pdf

Wikipedia

http://en.wikipedia.org/wiki/MONIAC_Computer

New Zealand Institute of Economic Research web entry

http://www.nzier.org.nz/Site/about/NZIER_Moniac.aspx#H51750-1

How Engineers Get Thermodynamics And Information Theory All Wrong

2009-11-02T10:53:00.000-08:00

There is probably no other area of higher education where what is taught is so out of step with what is in fact valid. Engineering programs the world over, in the interest of simplicity and practicality, teach thermodynamics and information theory towards practicality and real-world solutions. What could be wrong with that? What is the negative side of practicality?

Well, usually, nothing. In most cases, cutting corners doesn't invert the causal bedrock upon which engineering is based. The field equations used to abstract relativity, do not usurp or demand a reformulation of E=mC^2. Neither do feynman diagrams mess with or disrupt an accurate understanding of quantum electro-dynamics. But in thermodynamics and information theory, the practical methods taught and used by engineers are based on assumptions that have resulted in an almost universal and wholesale misunderstanding of the base meaning and the causality that animates the bedrock of energy and information dynamics.

In thermodynamics, the problem is probably best described by the idea of "the perfect wall". To cut corners, engineers are taught arithmetic tricks that work in the usual atmospherically-dense and energy-conductive environments in which human's live. Unfortunately, these computational short-cuts do far more then introduce the usual errors of computational fidelity, they actually reverse the meaning of thermodynamics as a science. Thermodynamics as a science is about the way systems interact with the systems they are embedded within. But more than that, thermodynamics asserts the absolute necessity and inevitability of interaction and transference of energy that will result from ANY change within or without a system.

It should therefore be obvious that the teaching and use of practical methods that sidestep the central tenet of a field of science will have an unusually strong an adverse effect on the understanding of that science. Whole generations of engineers are being unleashed into the world with an absolutely backwards understanding of the very dynamic that universally informs all other dynamics. This is more than unfortunate. The growing population of scientists and engineers that march forward from universities with a backwards understanding of thermodynamics interferes with progress in all fields of science.

Same can be said of thermodynamics' sister, information theory. Because everything we do is increasingly keyed to progress in computation, the miss-map between the causal truths that inform information theory and the practical methods taught in their stead, may potentially have a much larger and deleterious impact on our potential as a species.

Where thermodynamics dictates the way energy leaks across the spacial dimensions, information theory dictates how information leaks across time. Purists will say that energy and information are equivalent. Ultimately, this is true. So when energy is measured in its more general form, as information, as bits, then information theory also dictates the lossy transfer of energy across time.

Because the two disciplines show how no system exists independent of other systems, we must concern ourselves with how systems are related through this leaking of energy and information. What can be said absolutely about the way information and energy set up directional relationships between systems with regard to space and time?

The Butterfly Effect; Isn't

In the none academic world, causality suffers a different abuse altogether. It is tempting for people to take notions of system interconnectedness to ridiculous and self-defeating extremes. We loose ground when the perfectly valid logic showing why a system can never act in isolation is illogically extrapolated to, "All systems effect all other systems equally". Making exceptions for speed of light (event cone) isolation, it can indeed be shown that all gravitational systems effect all other gravitational systems… the movement of a butterfly in South America will indeed effect (however infinitesimally) a dam in Montana. But if one were to rank, by degree of effect, all of the systems effecting the gravity fields surrounding a dam in Montana, a butterfly in Argentina would be very very low on the list. Even if one is butterfly obsessed, wants to ignore the one dog on the corner who has more mass than all of the butterfly's in the rocky mountains, there are tens of millions of butterflies closer, each of whom's infinitesimal gravitational pull would none the less have a larger causal effect on our poor dam's future.

This particularly populist breed of cause-and-effect miss-mappings is not the focus of my essay. As wacky as pedestrian notions become, they probably can't significantly derail scientific progress to any great degree. But when entire generations of science students are raised on incorrect understandings of basic science, we are all in trouble. This is especially devastating when the topic of delusion is as fundamental to the causal stack as is thermodynamics, energy and information.

"The law that entropy always increases, holds, I think, the supreme position among the laws of Nature. If someone points out to you that your pet theory of the universe is in disagreement with Maxwell's equations - then so much the worse for Maxwell's equations. If it is found to be contradicted by observation - well, these experimentalists do bungle things sometimes. But if your theory is found to be against the second law of thermodynamics I can give you no hope; there is nothing for it but to collapse in deepest humiliation."

Sir Arthur Stanley Eddington, The Nature of the Physical World (1927)

What determines the causal morphology and behavior of the hierarchy of influence (dictated by thermodynamics and information theory)? If we define the shape of causality we define process itself, and by extension, the shape of reality.

Information Theory specifies ways to measure the capacity of a storage matrix and the reliability of a communication channel. But all of it's metrics are agnostic to the meaning encoded and transmitted. Each bit and each bit pattern are treated as equal. Only frequency and order, not meaning, not saliency, not fidelity of representation.

What would you have to fold into or add to information theory and thermodynamics in order to measure meaning and saliency? Is it there already? Are we missing something in our approach to and use of an already semantically robust set of laws and equations?

Several years ago, the mathematician Stephen Wolfram (founder of the maths software "Mathematica") wrote a book called "A New Kind Of Science". It is a dense and repetitive work over twelve hundred pages long. I tried to get through it and gave up. Feels like a giant fractal, built of some obscure philosophy based on fractals. Not feeling OK with my initial critique, I forced myself to come up with a theory, any theory, that said or not, I could attribute to his work. The best I could do was to suppose that Wolfram was trying to say that science had historically used equations to understand the components of nature that could be accurately described by equations, but the really interesting things about nature were iterative, and open ended, they required logical descriptions that required continuous computation. To bad he couldn't have just said that.

At about the same time, the social biologist Edward O. Wilson wrote a book called "Consilience". He argued for a cross-discipline coming-together of the various branches of scientific exploration, a holism, for the advantages of looking at nature (and those who study it) as the one large and interdependent super-system it is.

Of course dynamic, ever changing, "evolving" systems are systems simple equations (calculated once) will never accurately represent. Traditional thermodynamics and information theory engineering maths and methods work best on simple systems that are or can be thought of as repetitive and isolated. The conditions (input energy, output work) might change, but the conditions of the conditions never do. At any sufficiently salient level, real systems are never that well behaved or that removed from their environments or situations.

Real systems are direction of time dependent. It is more than ironic that the one scientific law that defines exactly why causal systems are non-reversible is used primarily by engineers who choose to use it in ways that ignore the direction of time it demands. I can forgive newtonian or relativistic or quantum physicists for ignoring the asymmetry of time… their maths don't require it. But thermodynamicists? Information theorists?

[more to come…]

Randall Reetz

Cognition Is (and isn't):

2009-10-26T13:53:00.000-07:00

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

If It Doesn't Scale, It Isn't A Solution

2009-10-21T16:08:00.000-07:00

[note: this post is a work in progress]

You've met the private school freaks. They can't believe anyone would put their kids in a public school. What with all of the riffraff, the minority students, the dropout rates, the low performance on standardized tests, the poor state of school grounds and facilities, the struggle for funding for special programs like music, art, and sports, the lack of emphasis on college preparation, etc. Man, look at that list! Those are some strong and obvious arguments against public school education. Or are they?

What people who advocate private or limited solutions fail to calculate is what I call the "boutique effect". If for instance, there isn't enough money in a culture to give everyone a rich and safe childhood and education, it is absolutely expectable that those who are given those resources will excel (at least when compared to the scores of the less fortunate masses).

However, there is a real societal cost to exceptionality, and this goes to my "solutions that don't scale" thesis. With regard to exclusive schools for the rich, that cost has to do with the fact that the parents of rich kids just happen also to be the people with the most political and economic influence. When their kids are not part of the public education system, neither is their protective passion, experience, knowledge… or influence. They don't care about public education. Why should they? Their kids are not dependent upon it.

From another angle, when money goes to elite institutions, it is not being put where it is needed the most. Rich kids already live in information-ally rich environments. Rich kids are already live in safe and calm environments where learning works. Rich kids are much more likely to have direct access to positive role models… their environment is chock full of success stories. Rich kids are not as likely to live in families broken apart by drugs and prison terms and gang deaths and violence and people struggling with a second language or a culture that is not in step with the larger population. Rich kids have educated parents around them who can help them with their homework! Rich kids can afford to think about learning and succeeding, their world is devoid of the concentration-destroying stresses that poor kids deal with all day long.

And the whole reason people can get richer in this country than they can anywhere else, is because our population is more competitive (or used to be) than every other country. Why? Because we did this obscenely radical thing 150 years ago, we decided that everyone had a right to a publicly funded education! Educated people build factories and high tech energy delivery systems, they build transportation systems and are more likely to participate in advancements and the types of change that increase productivity. Productivity is the key. If you can get more value, more product, out of the average hour worked by your population, you can produce more wealth. Education is the radical difference that gave America its high per/hour, per/person productivity, it is why the rich are rich and why they can afford to borrow from the equity that is american productive wealth, even though that borrowing actually destroys wealth on a national scale in the process.

But these are not factors that have anything to do with a valid comparison of private education vs. public education. These are strictly socio-economic factors. The problem is when desperate parents look at the performance divide that exists between public and private schools and concludes that public schools should do exactly what private schools do. Private schools could be significantly worse than public schools and still produce higher test scores, more college acceptances, fewer drop outs, and lower crime rates. All of the intangibles work in their favor. In fact, it is often true that private schools employ teachers with less education and training than their public school counterparts.

Private school programs tend to spend less time on basic subjects (math, reading, etc.) and get better results! That is why they can spend a higher percentage of their student's time on extra-curricular activities (music, art, sports, theater, community projects, etc.). Obviously, if a public school would fail if it decided that it should therefore shorten the instructional time devoted to math and reading. Private exclusive schooling is not a solution that scales. It is obvious that it is a solution that only works for a very small percentage of the population of a society, and that it works only at the expense of the whole country as a whole. There are lots of examples out there of countries with very good exclusive education systems and very very very poor economies embedded within extremely unstable social chaos dominated by poverty. Most central African nations play this game, Myanmar, The United Arab Emeritus, South Africa (before apartheid was upended), Iran, North Korea, Brunei, etc, etc, etc. Exclusivity is the norm in the poorest nations on Earth. If exclusivity worked, these would be the most productive nations.

Lets look at China. Until recently, from a strictly financial perspective, China has done all of wrong things, it has restricted entrepreneurship, it has restricted credit, it has promoted an exclusively top-down decision and influence structure… everything that works against the kinds of fluid business environment that are attributable to a growing and healthy post industrial economy. And yet… and yet, despite all of these huge shortcomings and mistakes, China succeeds like no other country. Why, because it has spent an inordinate percentage of its wealth on its public education system. China's people are well educated by any global standards. Not some of its people. Not the exclusive elite. Everyone. And given China's huge population, that is a lot of educated people to compete en-mass with the rest of the world. When they finally turn the last capitalist stone, when they finally create a legal structure to support personal liberty, property ownership, and unfettered personal expression, watch out! Even without these capitalist standards, China reaps such benefits from its non-exclusive infrastructural investments. Meanwhile, those of us in the west have all but forgotten which factors really matter, and which, in comparison, are just fluff.

But, if you happen to live in a nation that has paid attention to productivity, has produced wealth as a result of a fair and solid infrastructure (transportation, energy, safety, medicine, credit, agriculture, justice, and education… for everyone!), you can play the exclusive game in limited numbers, even though it destroys wealth on a national scale.

Now let's switch gears. Inoculation. How did inoculation get to be such hotbed of superstitious thought? Inoculations have been blamed for hyper-activity, for cancer, for Asperger, and MS, for Attention Deficit Disorder, even for AIDS, etc. What inoculations are never blamed for is the one thing they are most definitely and unequivocally guilty of… preventing pandemic spread of disease! But inoculation programs only work when a certain minimum threshold of the population participate. Each vaccine (/disease combination) has its own special number… correlating to a specific minimum percentage of the population that must be inoculated. If a smaller slice of the population are given the vaccine, an outbreak is certain. When a parent makes the decision not to get their kid vaccinated, what they are really doing is passing the responsibility and risk (if there is any) to the kids who do get vaccinated. They reap the rewords but pay none of the price!

This is a great example of a solution that doesn't scale. While the vast majority of parents accept the shared responsibility a few parents can get by without inoculating their kids. It is a solution. But it isn't a solution that scales. Obviously, it doesn't work if everyone chooses this solution. It doesn't even work if more than a few choose not to inoculate. This type of solution only works because others are not choosing to shirk their share of the responsibility (and risk). In fact, if more and more people choose the non-solution option, there will become a point where everyone will suffer, even those who did take the vaccine. Most of these vaccines only work when the exposure to the pathogen is very low level. If a pandemic took hold, and if many people got really sick, high concentrations of the pathogen could overwhelm the immune resistance afforded through inoculations.

Any of this remind you of the "libertarian" platform? It should. The libertarian program is the very definition of a solution that doesn't scale.

[more to come…]

Randall Reetz

Social Media… Amplifying The Inner Sheep

2009-10-14T20:33:00.000-07:00

In the early days of computing, those involved were pioneers, innovators, original thinkers, the super-passionate, driven by curiosity and the purity of adventure. These were a strong people. Proud. And though it sounds precious to say so, the early computing pioneers were not unlike other gritty pioneers in that they enjoyed being out well beyond the known, striding forward where there was no trail, no strength in numbers, no peer support, no mentors, no accepted pattern.

Now? Well now that computers have become ubiquitous, now that everyone has one, uses one like they use a knife and fork, the pioneers have long since been replaced by Plumber Joe, by the middle of the bell curve, by everyman and everywoman and their kids.

The computer industry is market driven! I hate that it has taken me this long to recognize the importance and implications of this now overwhelmingly obvious and simple fact. The diffusion of computers into the daily routine of the entire population has resulted in a dramatic shift in the demand landscape that informs what computing becomes. The market for computing is its users. The user today, the average user, is a whole different animal than the user/creator that defined its early history. Those of us that jumped in early probably resist the idea that what we care about really doesn't matter anymore. Though it might be true that knowledge and a deeply theoretical bases for that knowledge still matters, from a consumer market demand perspective, we grey hairs are simply invisible. The fact that we nerds ever defined a market for anything at all is the more surprising historical footnote. It is a bittersweet realization, that success of our industry would of mean the marginalization of its founders.

In every grade school class I attended there were a few kids (one or two) who were driven by a passion to know, to understand, to create. The rest, well the rest excelled at a completely different set of skills, getting through the day, unnoticed, blending in. The two groups couldn't be more different. The inquisitive few were internally driven. The rest were driven by the outward demands of success as defined by the curve. The inventive minds competed against their own ability to invent. The rest competed amongst themselves over the coveted 60 percentile that would define passing the class.

The computing market is now dominated by that larger part of the human population that defines success as climbing (which ever way possible) on top of the 60 percent of the population (of other social climbers) that makes up the bulk and center of any bell curve. As kids, these were the people who spent most of their time comparing themselves to the kids next to them. Looking over their shoulder at the other kid's test answers. Studying together so that they knew the base line before they got to the actual test. I say "climb to the top" but the word "top" when describing a bell curve does a disservice to the real meaning of averages. What we call the top of a bell curve is really the center of a frequency distribution. Climbing to the top is really a struggle to get into the center. Like fish trying to avoid a shark, there is a natural human tendency away from being alone, away from the vulnerability that is the open water that is original ideas and behavior. As a result, we constantly seek the protection of others. Each of us, as humans, spend a good deal of our energy trying to determine and then contort our behavior to that which best describes the center of normative behavior and attitude.

The similarities between schooling fish and human socialization pressures are profound. But there is one important difference. Where fish seek the center to avoid the teeth and gut of another species, the predator we humans work so hard to avoid is us, is public ridicule, being seen as different, standing out! We are in a very real sense both sheep and the sheep dogs nipping at the the sheep's legs. It is obvious that evolutionary pressures have conspired to build into our brains at least two modes of processing and that they are, at least at times, antagonistic. One is a great big "what if?" simulator, a novelty machine… the other, a social manors restriction system that cautions at the point of pain, behavior the least bit novel or different.

I have traversed the usual nature/nurture, cultural/evolutionary minefields. What I come to is this; traits that exist universally across most cultures and experienced many times within each individual's life, are most probably behaviors that have a significant genetic/physical component... are common regardless of our developmental environment and experience. Humans are obviously capable of profound novelty and abstract pattern analysis. But there is also a pervasive behavioral overlay of social control of which we are simultaneously, willing participant, and victim. What is confounding is the extent to which each system interferes with the function and success of the other… and that they are so diametrically opposed.

With regard to schooling (and herding) behavior, that which we share in common with fish (and sheep), is an indifference to where the school is, in which direction it is moving, and how fast. Under the social threat that triggers schooling, all that matters is that each of us as individuals finds our way as close as possible to the center. Humans will go along with almost any plan so long as social grouping allows us to avoid being seen as different. Obvious examples: Nazi Germany, Slavery in the southern U.S., the Nanking Sex Trade, etc.

As computers have been made "user friendly" and as the cost of ownership has dropped, this center of the bell curve, this mad fight for self-similarity that defines who we are as a species, this reflection and homogenization of the greater us, has become the market for computing. Which makes sense. Diffusion and all. But the whole history of modern computing is so short, just 40 years now, that it is surprising and a bit of a shock to realize finally that from a market perspective, computing is a mature industry. How could an industry just a generation old have transited already from go-it-alone pioneer to "I'm Love'n It" average?

The implications are huge. In particular, this insight brings social media into sharp ironic focus. Social media brings to computing the same access to community monitoring and control that gossip and storytelling brought to the camp fire. It is to computing what cheating off of your neighbor's test is to being a kid. As a person who likes to think of himself as a pioneer, I have reacted in horror, disbelief, and frustration to what has looked like fifteen years of computer industry regression.

If you accept that computers, like minds, are abstraction (language) machines, then it makes sense to wonder to what extent the human brain has suffered the same evolutionary pressure towards social assimilation and at least plausibly, away from innovation and novelty. To what extent is the rarity of the product of profound human creativity a reflection of actual physical and logical limits on and causal costs to creativity itself, and to what extent is the same rarity a product of evolutionary molded physical properties of the brain that conspire to restrict the production of novelty as a result of even greater survival pressure to promote behaviors that honor social cohesion?

If the current overwhelming trend that sees the computer as more of a social monitoring mechanism, and less a creative tool, is a trend that reflects market demand, then the same questions I am asking of the market pressures that shape the machinery of social media must be asked of the cultural pressures that have through evolutionary time shaped the mind. So long as computation is primarily consumed by human beings, both computer and mind will be shaped by the same evolutionary pressures. As technical barriers are overcome, the industry can and does react more fluidly and with higher fidelity to the demands of its consumers.

At which point, the question becomes; Which heaps greater selective pressure on the evolution of computing, the need for tools that stand in for skills the human brain lacks, or the need for tools that amplify our most attention demanding desirers? Can the two co-exist and co-evolve productively? Again, the question is asked practically of computation and at the same time, philosophically or anthropologically of the human brain and the cultural stew in which each is both product and survival pressure.

Where computing used to take its shape from the fecund imagination of computational luminaries, it has of late been lead instead in the pursuit of the lizard brain in all of us, the sub-conscious urges and fears that inform social mediation behavior. The result is all of this social media dribble, the likes of "Twitter", "13 Seconds", "myface and spacebook" [sic], and numerology based pizza ordering "iPhone Apps." What advantages do such time wasters render? Some argue that social media was the logical communication oriented extension of email and personal web sites, that social media greases mechanisms deeply human and "natural". I remain dubious to these claims. I tend to group the brand of communication that social media seems to breed with more negative forms of group behavior like cults, mass hysteria, fundamentalism, and other behaviors unique to group-think.

And what of pop-culture notions like "collective intelligence", "global awakening, and "cultural consciousness" which seem to be born of transcendent utopian notions (not dissimilar to those that feed religion and spirituality). The adherents of these optimisms appear to be blissfully unhindered by the need for causally logical argument or empirical evidence. If our computers have become social monitoring devices (at the expense of facilities that enable creativity), is there a danger that they will further distort our already distorted sense of truth? If a computer "wants" to agree with us more than it wants to accurately calculate a value, then we might already have crossed the threshold into a world where 2 plus 2 really does equal 5 (if the computer says so, it must be true!).

It would be irresponsible for me not to at this point remind myself to question my own rhetorically close topics.

These questions and trends have profound implications to populist concepts we tend to romanticize but rarely examine in detail. Democracy, plural-icy, consensus, society, culture, community, equal rights, individuality, etc. As the computer industry becomes more and more sensitive to consumer demand, its product WILL become a device that does a better and better job at the automation and magnification of human idiosyncratic behavior, of superstition, mythos, hubris, rhetoric, ego, at any and all of the emotional side effects of evolutionary pressures. Forget about the cold indifference of causal truth that has motivated so many sci-fi stories.

The real villain to be feared in any inevitable future is the computer as hubris amplifier.

Computing's new "social media" face might disturb my pioneer sensibilities, but it reflects the satisfaction of common demand. As any market matures it learns to overcome the physical and conceptual obstacles that so plagued it in its earlier years. Unburdened by things like processor speed and storage density, the computer industry was able to pursue directions more in line with human consumptive desire than with the technical or theoretical goals of computer "scientists". Marketeers trump scientists when the saturation of a product becomes universal.

It all makes sense. I am still depressed by the anti-innovation implications of the mass market dumbing down of computing, but at least I understand why it happened, what it means. Knowledge, even depressing knowledge, should open doors, should allow more efficient planning and prediction. But what exactly are the implications when a creative tool is hijacked by a larger urge to avoid at all costs, change and novelty. What happens when the same mass-market demand pressures that cause fads and trends focus their hysterical drive towards homogeneity onto the evolution of a tool originally intended for and idealized for creative exploration? What exactly do you get when you neuter the rebellion right out from underneath Picasso's brush?, When you force Darwin to teach sunday school?

Just what does it mean when our creative medium becomes sensitive to social interaction? Pen and paper never knew anything about the person wielding them, certainly didn't know how the greater society was reacting to what was being written or drawn.

If the average human feels more comfortable doing exactly what everyone else is doing, seeking the center, would much rather copy the answers off of their desk-mate's test than understand the the course content, well then it only makes sense that, we, the royal "we", would use this computing tool in the same way that we use the rest of the stuff in our lives, to help us find the social center and stay there.

It's not just the marketplace that has shifted towards the demographic center. The schooling mentality has crept into and now dominates computing as an industry. Personnel and management which in the early days of computing was awkwardly staffed by engineers and scientists and groupie hobbyists is now as diverse (homogenous?) a mix of humans as you could find in any industry. Even the scientists are cut from a different cloth. It takes a special and rare (crazy) human being to invent an industry from nothing. When avocations become well funded departments at major universities, the graduates are not likely to be as intellectually adventurous (understatement). As any MBA knows, the success of an industry is most sensitive to its ability to understand and predict the demand of its market. Who better to know the center of the consumer bell curve, the average Joe and Jane, than that same Joe and Jane? Joe and Jane Average now dominate the rank and file workers that make up the computer industry. This means administration, it also means sales and marketing, both of which make sense. Less intuitive, is but equally understandable, Joe and Jane Average have taken over the research and design and long range planning arms of the computer industry. Even where it isn't the actual Joe and Jane, it is people who do a kick-ass job of channeling them.

Does market saturation mean the evolution of computing has reached its zenith? I don't think it does. But, once an industry has reached this level of common adoption, the appearance of maturity and stability are hard to shake. Momentum and lock-in take hold. I have tried repeatedly to sell paradigm-busting and architectural re-imaginings of the entire computing paradigm to valley angles and big ticket VC firms only to realize that I wasn't selling to the current market. Try opening a VC pitch with "The problem with the computer industry is…" to a group of thirty-five year old billionaires who each drove to the meeting in custom ordered european super cars. Needless to say, their own rarefied experience makes it hard for them to connect with anything that follows. This is a classic conundrum in the study of evolution. I presume it is a classic conundrum facing evolution itself. Why should a system that is successful in the current environment ever spend any energy on alternative schemes? How could it? It is hard to even come to the question "What could we be doing better?" when surrounded by the luxury of success.

At the same time, it is unlikely (impossible?) that any system, no matter how successful in the present, will long define success in the future. It might even be true that the more successful a scheme, the more likely that scheme will hasten an end to the environment that supported it (through faster and more complete exploitation of available resources). The irony of success!

But we a are smart species. We are capable of having this discussion aren't we? So we might be prepared as well to discuss the inevitability of the end of the current computational scheme. No? To prepare as a result, for the next most likely scheme (or schemes)? Especially those of us who study language, information, computation, complex systems, evolution. Especially an industry that has so advanced the tools and infrastructure of complexity handling. No? Surely we in the computer industry are ideally situated to have a rational vantage from which to see beyond the success of the current scheme? Yet, for the reasons I have already postulated (market homogeneity and success blindness), and others, we seem to be directionless in the larger sense, incapable of the long range and big picture planning that might help us climb out of our little eden and into the larger future that is inevitable and unavoidable. Innovations springing forth from the current industry pale in comparison to those offered up 20, 30, even 40 years ago.

Speaking of which; I just found the resource list for Pattie Maes' "New Paradigms In Human Computer Interaction" class at MIT's Media Lab. These are video clips of speeches and demos of early and not so early computing pioneers showing off their work prescient work. Mind blowing. The future these folks (from places like MIT, Brown, Stanford Research, the Rand Corporation, Xerox PARC, and other institutions), well, it is sooooo much more forward looking than what has become of computing (or how the average computer is used). Everyone would do well to sit down and view or re-view these seminal projects in the context of their surprisingly early introduction.

I have written quite a few essays lambasting what I see as the computing industry's general loosing of its collective way… at the very least, a slowing down of the deep innovation that drove computing's early doers. Even when potentially powerful concepts ("Semantic Computing", "Geo-Tagging", "Augmented Reality", "User-Centered Cloud Computing") are (re-)introduced, their modern implementations are often so flawed and tainted by an obsession to kowtow to market pressures (or just plain lie or fake it) that the result is an insult, a blaspheme of the original concept being hijacked.

Over ten years ago, I gave a talk at Apple titled: "Apple Got Everything It Has For Free, And Sat On Its Ass For Eight Years While The Rest Of The World Caught Up".

Which is true, at least with regard to the Lisa/Macintosh which Xerox PARC handed them (check out the Star System) and the way they just kind of sat on the WISIWG mode-less graphical interaction scheme while other computer companies (Borland and then, reluctantly, Microsoft) eventually aped the same. At the time of my presentation, Apple had wasted its eight year lead extrapolating along the same scheme… a bigger badder WIMP interface, when they could have been introducing paradigm vaulting computational systems (that would put Seattle on another eight year chase).

But from a marketing perspective I couldn't have been more wrong. I have got to keep reminding myself that I no longer represent the market for computers! I wish I did, but I don't. I am an outlier, a small dot on a very long tail, I am pluto or maybe even just some wayward ice and dust comet to the big ordinary inner planets that trace out wonderfully near-circular orbits around the sun. In later presentations, I explained that Apple's critically acclaimed "Think Different" campaign and the elitist mindset from which it was derived, was the reason they had never garnered more than 2 or 3 percent of the computer market. I explained that Bill Gates' "genius" lie not in his profound insight, but in his ability to understand the motivations that drive the average person… namely to never be caught doing something that someone else could question. That means acting the same as everyone else. That means knowing how everyone else is acting. That means social media!

Nobody (other than wacky outliers like me) wants to be compared to iconoclasts like Einstein or Picasso or Gandhi or Gershwin. Very few people really want to "think different". Most people wouldn't be caught dead risking that type of public audacity. You have got to be pretty confident that you have an answer to the dreaded question "Why are you doing that?" to ever DO THAT (individually creative thing) in the first place.

Pioneers know exactly why they do what they do. They are driven by knowing more than others and by the excitement of being somewhere others haven't been… by being very much outside of the ball of fish that others seek as protection.

But if you want to sell a billion computers instead of just a few thousand, then you want to pay attention to the fish in all of us and not to the smiling and sock-less Einstein's on a bike.

But the larger and longer implications of mass market sensitivity are profound. While it is entirely true that paying attention to the center of the cultural bell curve will allow any industry to exploit more of the total available consumption potential, such behavior does not necessarily produce the paradigm jumping disruption upon which long term progress depends. If your Twinkies are selling really well, you might not notice that your customers are all reaching morbid levels of obesity and malnutrition or that the world is crumbling around the climate changing policies upon which your fast food empire is based.

The satisfaction of human center-of-the-fish-school urge is not necessarily the best recipe for success if success means more than short term market exploitation. In the long run, potential and satisfaction are decidedly not the same thing; they are, as a matter of fact, very often mutually antagonistic. Rome comes to mind. What comes to mind when I mention the phrase "dot com" or "mortgage backed securities" or "energy deregulation".

The mass market topology that has driven computing and communication towards a better and better fit with the demands of the largest and most homogenized consumer base the earth has ever witnessed could very likely work against the types of creative motivations that might be necessary to rescue us from the bland and the average, from the inward facing spiral of self-sameness that avarice alone yields. I am increasingly worried that the computer's seemingly endless potential to be warped and molded chameleon-like to perfectly satisfy our most basic evolutionary proclivities, to amplify unhindered, urges made strong against real scarcity in the natural environment, has already so distracted us within our egos and desires that we might not be able to pull our heads out before we get sucked completely down and into our very own John Malkovich-ian portals of endless identity-amplication.

And why does it matter? Because, like it or not, progress in every single field of human endeavor is now predicated on advancements in computation. More profound than anything else science has discovered about nature is that information is information. Information is domain agnostic. Which means that advances in information processing machinery benefit all information dependent fields of inquiry. Which is every field of inquiry! Which also implies that all fields of human inquiry are increasingly sensitive to the subtle ways that any one computational scheme effects information and the scope of information process-able within that scheme.

At any rate, it is alarming (if understandable) to me that the trending in this industry is towards a re-molding of the computer into ego amplifier, pleasure delivery system, truth avoidance device, distraction machine, Tribbles (as in "The Trouble With…"). The more insightful among us may want to place a side bet or two (if only as evolutionary insurance) on more expansive futures. Some of us are not so distracted by the shininess of these machines or by how they are getting better and better at focusing our attention at our own navels, to see futures for computing that are more expansive than the perfect amplification of the very human traits least likely to result in innovation or progress. There is still time (I hope).

Randall Reetz

Are We But Crows? (Where Pattern is Noise)

2009-09-25T12:33:00.000-07:00

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

A Plan To Re-Invigorate Long-Term Capital Markets

2009-09-20T12:10:00.000-07:00

Human behavior favors the immediate. Nobody willingly chooses to wait when an option allows instant or near-term gratification. This tendency naturally results in imbalanced systems. The recent investment market crash is evidence of what happens when short-term behavior is at odds with the medium and long term needs of a healthy economy.

To make matters worse, our tools evolve naturally in directions that mimic human proclivities, catalyzing the very natural and human obsession with the immediate. As investment securities markets are more and more influenced by and accelerated through the use of automation technologies (the computer and global communication networks), they trend naturally towards an over-valuation of short-run returns and under value long-run returns. Even if traders or fund managers start off with long-range, future-looking, wide-perspective goals, the competitive pressures placed on them simply for sharing trading facilities with companies that make money by trading on shorter and shorter time frames forces them towards similar behavior. When you are competing for money, and that money is changing hands in shorter and shorter cycles, money available for long range investments and the types of businesses and infrastructure plays becomes scarce. You either join the race towards the immediate, or you go without.

However, a thriving economy absolutely depends upon the continuous and long-range capitalization that actively supports basic science and the steady infrastructure improvements that build, promote, and maintain complex supply chains that constantly evolve towards greater productivity.

Though a healthy and vibrant economy profoundly depends upon capital fluidity, upon responsiveness to investment demand, the recent trifecta of market boom/bust cycles (energy, dot-com, and real estate securitization) has shown that revenue schemes that do nothing more than move money around can exert too much influence on the entire market landscape that shapes our national and international economies.

Three times in a row we have witnessed first-hand how second tier capitalization (business that make their money by repackaging investment risk) tend to quickly and fatally overwhelm the total investment market. These securitization schemes do better in the short term than standard capital markets because the value they trade is not directly tied to the success of the actual businesses and infrastructures that they capitalize. In market competition for investment dollars, abstraction schemes provide an artificial advantage that is impossible for real businesses to overcome.

If investors have the option of making a quick bet against market stability, an option that is not in and of itself dependent upon actual consumer or business to business demand for actual product or service, of course the capital will follow the quick and the fake over the slow and the real. This is a natural and predictable attribute of the behavior of capital markets.

So what is to be done?

There are many potential solutions and solution categories. Greater regulation of markets. Tariffs and taxes that are then redirected through government advisory boards that seek to determine the areas of funding that will have the greatest impact on future productivity. New kinds of markets and financial products that somehow reword long range investments. Public education directed towards society-wide changes in social morality and long range responsibility to future technologies and infrastructures. Switching to a benevolent dictatorship and appointing exactly the right leader with exactly the right understanding of productivity building economic mechanisms, and the will to make it so. Each of these options has deep potential for failure. Most are simply impossible or entirely romantic.

After some thinking, I came up with a plan that just might work.

Lets say the government set a Target Average Investment Period (TAIP). This TAIP (for sake of argument, lets say it is set at 'two years') would be the time delay before any investment you make could be evaluated, cashed in, or traded. It is an "Average" because you can make any number of investments but the average duration of your securities each time you invest has to be at least as long as the current TAIP setting. Some algorithm or official committee (Fed Board?) sets the value of the TAIP at some set interval (every year?) or, as is true of the Fed Rate, whenever the governing body decides the economy demands an adjustment.

In practice, what it means is this: If you purchase a thousand dollars in 1 year stock (one year 'less' than 2 year TAIP) you must offset this purchase with investments worth at least one thousand dollars in a 3 year stock (1 year 'more' than the current TAIP). An investor can offset securities purchases with periods shorter than the TAIP with any combination of investments longer than the TAIP so long as the total average of all purchases made at that time is equal to or greater than the the current TAIP setting.

In this way, securities are not simply tied to a company or fund or product, but also to the duration of the investment. If you want to partake in microsecond trading, cool, just as long as you offset those short run investments with an investments of equal value at the opposite end of the TAIP.

You don't just buy IBM, you buy IBM at duration. An investor can choose any combination of purchases (all of IBM or short term in IBM and long term in Intel). Alternatively, financial entities can be as creative as they want to be in designing investments products so long as the end result conforms to the current TAIP setting.

The government would fine-tune the TAIP the way it now fine-tunes the prime lending rate. Hell, if it works like I think it will, this adjustment will be more important and more reliable than prime rate manipulation.

Mostly, this scheme has the benefit of promoting the types of long-range investments that a strictly free market tends away from. And, it does so without restricting short range trades or the full range of trading period fluidity or investment products.

Randall Reetz

There's No App For That!

2009-08-29T09:55:00.000-07:00

There are now about ten thousand downloadable iPhone "apps". The tailings of a mad geek-scramble of mini-application coding and cloud-mashing, the gold rush of the 2000's. Low hanging fruit in the nerd orchard that is Silicon Valley.

Every C or Java savvy software engineer, hacker, and video gamer under 35 is trying to second guess the fickle fad-addled twenty-something market of multi-task-ers that will pay a buck or two for the opportunity to buy pretty-code-as-trinket, binary-pet-rock, boolean-back-scratcher, brickabrack-party-favor. The wave of the future? Gold rush for the new killer mini-application?

A month ago, I spent a couple of weeks in Tahoe camping with my parents and my sister's family. I don't really know how it happened, but I started saying "There's An App For That" (Apple's iPhone byline), every time someone said something of that didn't quite ring true. Pretty soon, my 9 year old nephew caught the bug and began mocking truth stretchers the same way. I don't know why this tickles me. As a student of social trends, my attention gravitates to behaviors that to-easily resonate, those memes that are to the human mind what complexity theorists call "grand attractors" (the attributes of an environment or system that have the greatest and most rapid effect on action and outcome… in our solar system it's the sun, not Pluto). We humans are embarrassingly susceptible to certain patterns of language and inane cultural cues.

Back to the "app". The word is of course diminutive for application. Where applications are big do-everything information workshops, apps, are single purpose narrowly focused seemingly useful algorithmic hacks that each do some particular information access task in some sort of (usually) intuitive and fluid way. But each of these apps, as useful as it may be in a given and highly particular situation or context, is like one of the 10,000 little doodad accouterments you can find in a fine cooking equipment store… they might be nice, they might indeed do the job better than anything else could, but you wouldn't want to have to find them in a kitchen with 10,000 other tools hanging from hooks and stuffed into drawers.

Imagine a robot as swiss army knife. That is what a thousand apps are in a devise that isn't anything more than drawers and hooks for the storage of applications. The swiss army knife is really just two pinions from which swing a whole bunch of tools. It knows nothing of those tools, just how to store them and swing them out for use.

In the same way that a cooking store is better when it has in stock every tool you could ever want, the more tools it has, the harder it is to find what you are looking for, the usefulness of any one iPhone app is diminished with the addition of each new app. In the parlance of cooking there is a hierarchy of tools by complexity: kitchen, work station, major appliance, appliance, tool, and utensil. If the OS is an kitchen, and the application is the appliance, then an app is something small like a tool or a utensil. A garlic press, like most kitchen tools has a single purpose. It is a highly specialized devise, the design of which has been fine tuned through multiple design and test iterations to smoothly and reliably function as the user would expect in highly specialized and somewhat exceptional situations (once in a while). There just aren't that many things other than garlic that you want to peel, smash, and extrude. Compare this to the average utensil - knife, fork, spoon - which is meant for repetitive use across a range of activities. You have to go find a tool, but a utensil stays in your hand, or right near by all day long. You probably only have one of each of your tools, but you have multiple copies of each of your utensils. There are an almost unlimited number of potential tools, yet very few types of utensil.

It should be clear that iPhone apps are much more tool-like than utensil-like. And because most apps aren't very flexible or reconfigurable, they aren't in them selves appliances. The entire iPhone, as a devise, is often called an appliance. In this sense, it is of the class of appliances that is more akin to a food processor - the user can switch blades, for different tasks - so maybe in this sense, the blades are like apps and the iPhone truly is an appliance.

And that suggests an even more apropos metaphorical comparison… the people I know and their food processor. Almost nobody I know uses theirs. It sits there in the cabinet while they laboriously chop their vegetables by hand. Taking the thing out, collecting all of the parts, setting it up, finding the correct blade, installing that blade, plugging it in, preparing ingredients for processing, cleaning it afterwards, drying it, putting it all away…forgetaboutit!

The iPhone has a distinct advantage over the food processor - it has a primary use - as a phone - which keeps it within reach and always at hand. In the sense that an iPhone is a telephone, it is a tool - a tool that can transform itself into a multi-use appliance!

My argument isn't whether or not it is a good appliance, or whether the tools that can be attached (apps) are useful or well integrated, my argument goes to the difference between a well appointed kitchen, and a well staffed kitchen. Do you like food, or do you like cooking. My assumption is that there are far more eaters than their are cooks. Sure, everyone likes a great kitchen. Through the normal attrition that is gradual consumption, your kitchen slowly ends up containing more and more tools, but most people would, had they had access to more money, gladly trade in the whole kitchen in exchange for well prepared meals in a nice restaurant or brought to you in front of your TV.

If I had to dig a ditch, a good shovel is better than a bad one, but what the hell am I doing digging at ditch? Just how great would a shovel have to be before digging a ditch becomes something I choose to do?

I remember when personal computers became available. I watched grown men, highly successful, executive level professionals, choose to type their own letters simply because the technology was so cool and new. The same guys who wouldn't be caught dead typing their own letters on an IBM Selectric typewriter were firing their secretaries, and hand typing their letters in a far more complicated word processor on an IBM PC, just because they could change the font and the the color, size and style of the text. I am a big fan of fairness and equality, and shutter to think of the opportunity squandered during the age of woman as secretaries, but I can hardly conceive of the size of the gap between a word processor and a human secretary.

I shouldn't pick on the iPhone, in the sense that it is an information appliance, it isn't any different than any other computer. Just stores applications for later execution. What I am picking on is fact that a computer of any form factor, is just too stupid to act a anything other than filing cabinet. If you want a machine or appliance that will help you figure out what app to launch, well, there is no app for that, and there probably shouldn't be. The iPhone has taken the store-access-launch metaphor to the slippery silky extreme you would expect of Apple. This may in fact and ironically be exactly why it is becoming so clear where computers need to go next and how far they are from the fundamental technologies that will be necessary to go there.

[ more to come… ]

Complexity is Self-Limiting… Evolution Says "So What!" But At What Cost?

2009-08-20T10:54:00.000-07:00

Complex systems tend towards greater complexity. That is one way, in fact, of defining evolution. But complexity is also self-limiting in obvious and unavoidable ways. What gives?

How, specifically, does an understanding of complexity's natural limits, recast an assessment of where human society is, where it might be going, and what of this potential do our own limitations in understanding complexity and its limits… well, limit?

We tend to gravitate towards a rather cleaned-up image of the future, all stainless steel and gleaming glass, and sexy robots that can't say "no" (puffy clouds, white wings, and lutes?). To be fair, this sparkly and perfect view of the future is something we reserver for "The Future". Excepting for Sunday mornings, we are refreshingly realistic about the process of getting through all of the calendar-able pedestrian futures to the final "The Future"… sometimes even positing an apocalypse or two along the way. Its as though we understand that things of great complexity and stability must be constructed, and that building is a messy and chaotic process, our self-delusion begins and ends with the absolutely fatal assumption that there is some end to the construction process, after which everything will be grand and glorious and perfect in the sense that no major construction will ever again mar the sublime and pristine quite and elegance we have built.

Right. OK.

In light of the magnitude of our self delusion, it seems down right naive to apply the phrase "drink the Cool-Aid"… in some very real sense, we must, each of us, have Cool-Aid factories right smack in the middle of our brains!

The actual future, the sober future, the one we seem hell-bent on ignoring, is a future of greater and greater and more and more constant change. A future we can never get to. A future that will surely go on one day without us. There were after all, a whole bucket-load of futures before we existed, before we declared ourselves the supreme center of everything, the final future. Ultimately, of course, there is a final and absolute future to any system. If you paid attention during your thermodynamics or information science lectures, you know that there will come an ultimate future which can not support any complexity at all.

For now, we will ignore that final future-of-all-futures (heat death)… there are "miles to go before we sleep".

As complexity marches forward and "upward", evolving systems are increasingly characterized by construction and change. A static system, one that can't react to its own constantly increasing experience, is a system that isn't as complex as one that can learn and adjust itself to accumulated knowledge. The romantic vision of a completed and peacefully static future is as laughable as it is understandable.

Some fantasies drive us towards success and influence, and others towards catastrophe and insignificance.

The difference between these two forms of fantasy are, to my mind, the difference between paying attention to the greater reality that is the whole universe (its physical laws, material properties, and configuration), and paying attention instead only to the reality hacked together within our own emotionally contorted and narrowly self-centered minds. The distance that separates the two is probably a good measure of the speed with which nature will replace us with some other form of complexity generating scheme with a more accurate natural mapping of reality to abstraction of reality.

A self-centered and locally weighted perspective is both expectable and self defeating. What works in the short term often gets in the way of what works in the long run. This is one of two oxymoronic misreading of process clouding our understanding of evolution that increasingly threatens our potential as a species. The other (related) self-obfuscation we don't seem to be able to avoid, and central to the thesis of this essay, is the dream-like way we tend to imagine the future as some silicone-enhanced sexed-up version of some glazed-over and romantic version of a past that never was.

What we know, how we comprehend what is around us, is a function of the iterative process of matching the stream of incoming sensation to what we have stored as experience. What comes to be known is always heavily effected by what was known before. Leaning is a local affair. Systems always end up knowing more about the things closest to them. The closest thing to a system is itself! This is a topologically and causally unavoidable fact, leading to difficult to circumnavigate self-centered understandings of the universe around us. I am convinced that evolution ultimately (in the longest run) favors systems that can overcome this local-centrism…though to to this, a system must literally work against itself in the short term. Success in the long run is dependent on the development and protection of genetic structure that frustrates success in the short run. This big-picture learning must be accomplished through the development of an ever more accurate internal analogue (process-able map) representing the most inclusive and location agnostic understanding of the entire universe. This too is an ever receding target, we can chase but never completely capture. Evolution is this back and forth dance between what matters to a system in the hear and now and the capacity to pay attention to, model, and process that which is salient about the entire universe… context in the largest sense.

I don't want to veer too far away from the thread of this essay, but it is important to keep in mind the counter-indicated admixture defined both by the immediate local needs of any given individual and the larger, decidedly non-individual scope of evolution. A decidedly cooperative mixture that is, none the less, achievable exclusively through the lives of and genetic/cultural information carried forward exactly and only by individuals.

In any given population of individuals at any given locality, there exists a range of differences that enable some individuals to make more efficient use of the resources in their surroundings, and some individuals to be better equipped to contend with and exploit the resources of their children's inherited environment. Those better matched to the current environment will out-compete those with a better match to the environment of the future. Ultimately, of course, what matters is the capacity of the entire mélange to both survive in the present and present morphotypes that meet the demands of the future. The demands of the present vs. those of the future are often at odds with each-other. A successful evolutionary scheme must "waste" a sizable chunk of its structure and energy on strategies that may have no immediate positive effect on fitness (and might in all actuality hinder success in the moment). Maintaining a long range understanding of evolution itself, and our place in it, is the example of this dangerous opposition that best fits the scope of this essay.

It seems obvious to me that the amount a system must "waste" anticipating changes in the future of its environment is inversely relational to the accuracy of its internal mapping of the universe in total. Systems that know nothing of the universe, must produce a great variety of random solutions. A very expensive prospect that best fits very very very simple individuals produced in absurd numbers. Atoms, molecules, single celled organisms.

Understanding the process, "THE" process, evolution, is probably the most salient predictive mechanism an organism might seek to internalize. We seem to have limited capacity as a species to model and abstract and then effectively navigate an abstraction of this "THE PROCESS". Especially when it comes to understanding the limitations and usefulness to "THE PROCESS" of any one scheme, species or individual.

The spirit of this essay isn't Nietzschein pessimism or a catastrophist's Cassandra; "I told you so!". I am an eternal optimist, so these words are intended instead as a wake-up call, and offered up as a Windex Wipe to the foggy lens through which we view reality… in the hope that we use it, adjust our behavior, and rectify the self-defeating distance between what is and what we want to see.

Nature doesn't stand still. Not at least until the very end. Heat death isn't at all like my fantasy of an endless Mediterranean resort vacation. Any system that bets its future on stasis, no matter how advanced, is betting against its longevity or influence on the real future.

I've compiled a list (below) of some of the most obvious side effects that haunt complexity, that push back against its growth. If we illuminate these barriers we might be better equipped to consider ways to get around them, and we might discover something of how systems get better and better at finding cheats in the march towards greater complexity.

For a system to be complex, it must have structure and difference within that structure. A crystal has structure, but its lack of capacity for internal differentiation means it can never be complex. But differentiated structure isn't enough, it has also to have some way of protecting and maintaining that structure, that shape or behavior over time. Shit happens. A complex system must employ some set of mechanisms in a constant fight against entropy. Without which, a system's complexity will be short lived, and short lived complexity isn't very complex at all.

Which brings up an important and much ignored aspect of an evolving system. We have a tendency to over emphasize the moment, the present situation or system. Nature on the other hand doesn't care about the individual or the moment except as a vehicle for the transmission of structure into the future. What matters isn't how complex a system is today, but the potential of a given configuration to influence the greatest complexity in the longest future across the widest expanse of the material universe. Many aspects or measures of complexity cross over between the here and now and the deepest future… but not all and not always.

Back to our list.

1. One way to maintain structure is to build yourself out of stuff of great material integrity – say titanium, stainless steel, or diamond.

2. Another is to adopt a vigilant and obsessive Mr. Fix-It program of self maintenance. Yet another option is to replace yourself with a pristine copy before you dissolve into an entropic heap.

3. A simple cousin of this replacement scheme is playing the numbers game… make sure there are so freak-n many copies of you in the first place that one or two of you make it into the distant future by virtue of the dumb luck of large number.

4. Or, you can choose to live a life of extreme isolation – limit your interaction with other systems and you limit the deleterious effects the second law dictates.

5. Then there is wall building. Wall building is a self-made form of the isolation scheme… instead of finding a place to hide in a pre-existing landscape, dig yourself a tunnel or build yourself a wall or a mote or a shell or a nest or fast legs or wings with which to run away with.

And then there is the problem of resource acquisition. Anything of value to a complex system tends to be reactive. Reactive things are destructive. Installing your self within a reactive environment means you have more access to energy and materials, but it also means you have to spend more energy and structure just to protect yourself from your environment. As your energy demands increase so too does your need to locate yourself closer and closer to more and more reactive and ever changing environments. A cave full of grain is great at first, but as you eat your way through it, its original attractiveness decreases. Better to install yourself at the mouth of a river, next to a mid-ocean vent, or on the floor of a flood plane. As your complexity increases, so to does your appetite for energy and materials. Access means proximity. Proximity to greater and greater concentrations of energy demands protection. Protection is expensive in terms of the self-protective physical structure and its maintenance.

Worse still is the negative feedback that metabolic waste presents. The more you eat, the more you go. The more you go, the harder it is to find food. As complexity increases, guess what happens to the magnitude of this problem and the need therefore to spend more and more energy on waste removal schemes?

The focus of this essay are the aspects of complexity (and complexity's demand for energy and structure) that put counter-productive limits on strategies that would otherwise allow for greater and greater complexity… and how evolving systems find work-arounds. The fact that we are here at all is proof that evolution finds a way.

What interests me is the way increases in complexity puts increased demand on energy and material resources, and how these processes are self-limiting and at the same time actually define the purpose that drives evolution.

In the particular, real systems manifest great creative variety in the fight for the extension of structure and integrity over time. For instance, once brains appear, trickery and guile become the standard approach to wall building. You don't need to go the long and arduous course of developing poison and some specialized hollow teeth through which to deliver it, if you can just tweak your skin coloration or shape to mimic those who have. Or you can become invisible by adopting a color and texture scheme that mimics your less vulnerable or edible surroundings. In essence, trickery schemes are the same as isolation or wall building except the wall you are hiding behind is within the brain of another creature (either it's already there or you build it in your foe's brain through behavioral conditioning).

But here is the rub. No matter which scheme a system adopts in the maintenance of structure… that scheme hardens their structure, making it more difficult and expensive to adapt to an always changing environment. In a very real way, what makes you stronger in the present makes you vulnerable over time.

Example: When Teflon was developed it was obvious to its creators that its extreme inert-ness, its aversion to chemical interaction, would make it an ideal lining for any reaction container (including frying pans and irons). But this same property made it almost impossible to figure out how to affix Teflon to the surface of a container (it took over 10 years to solve this problem).

On the opposite end of the isolation spectrum is metabolism. When a system seeks a means of extracting and drawing energy or structure from its environment, it needs to maximize its reactive interface to that part of its environment that has the most entropic potential. In earth biology, this usually manifests as an active interface to oxygen and or sunlight – both of which are highly corrosive to structure. In order to both exploit the energy of these highly reactive sources, biology has adopted a myriad of selectively self protective (and expensive) mechanisms. Playing with fire is an attractive AND expensive proposition. Simple systems have no option but to hide from highly reactive environments – to dig themselves into deep cracks in the earth. Only a system of great complexity has the structural and behavioral leeway to adopt the complex and selective mechanism necessary to both use and avoid concentrated reactive resources.

As a system becomes more complex it reacts faster to internal and external change. It evolves faster. This is a circular definition of "complexity"… configurations that facilitate faster development of configurations that facilitate faster development of configurations… ad infinitum. The capacity to do things faster always comes at a cost. To mitigate that cost, the system must learn to be efficient and effective in its environment. This means going with the flow. This means fitting in. This means doing what the environment is already doing. This means not fighting the system. To work with a system (instead of against it) means internalizing and abstracting a model of the environment's most salient structures. If you have some knowledge of what a lion will do when you enter a clearing it is sitting within, you have a better chance of surviving the encounter. If you have legs and eyes, your very structure is an acknowledgment of the physical constraints of your environment.

An accurate assessment of this whole concept becomes increasingly complex as we realize how system and environment blend in a co-evolutionary super-system.

In science fiction, the future is presented in one of two ways. Either the world has devolved into some filthy post-appocolyptic entropic mess, or it is a perfectly complete stainless steal and glass uber-infrastruture with everything in its place and everything perfectly maintained. Both projections are impossible, but the hermetically sterile one is the most problematic as it seems to resonate more completely with human emotional projections.

The problem is this; the more complex a system becomes, the faster is its capacity to change, leading to a system that is constantly in flux, constantly reworking itself, constantly under construction. Try to find a day in a modern city devoid of numerous construction cranes marring its skyline. This situation will only become more intense as human society evolves.

Biological systems have learned to accommodate the constancy of change, deterioration, ware and tear, construction, etc., through complex molecular mechanism of growth and repair played out at the (largely microscopic) cellular level. Furthermore, these anti-entropic mechanisms are largely automatic and do not therefore overly burden the larger and more overarching consciousness and behavioral control mechanisms (our mind).

Though humanity has reached a level of complexity that supersedes the capacity of its infrastructure to effectively carry its own complexity demands, we don't seem, as a species to be able to see this problem as systemic.

[more to come…]

Biology Is Too Slow!

2009-08-09T22:26:00.000-07:00

Humans are pumping a lot of energy around. When it comes to energy we don't mess around. We like our energy highly concentrated. We dig it up, refine it, convert it, and pump it through wires or pipes or the air like there is no tomorrow.

Nature is adaptive. Right? Nature finds a way. Right? So where are the animals and plants that suckle upon high power lines, that find their adaptive way into fuel tanks and batteries? Surely they could. Surely the same nature that goes gaga around mid ocean heat vents and can learn to metabolize the worst toxins we can throw into ponds... that good old adaptive nature should find a way to co-evolve with 50 thousand volt transmission lines.

And there are other (new) tits for nature to suckle. I fully expect our air to become less and less transparent to radio transmissions. If we can build devices that can grab radio energy right out of the air.… surely airborne molds and other microorganisms can do so. Are they? Doesn't look like it. What weird life forms would be best suited to radio-metabolism? Plants grab photons in the visible (radiation) band. Photosynthesis (in plants) is a respiratory affair - requiring oxygen and nitrogen for the primary reactions, but they also rely on heavy and rigid structural support to get up into the air where they can maximize their surface interface and solar exposure. Actually, when you think about it, a plant would be more efficient if it spent no energy fighting gravity, and instead laid flat on the surface of the land. Plants must only grow into the air to compete away from shade the shade of other plants and to increase respiration surface area.

Anyway, and this is a bit of an aside, but would there be a way for lighter than air super-colonies of single celled animals to maximize access to radio energy without the need for the heavy structure and vascular transport terrestrial plants employ? Maybe the radio scenario is ludicrous. Surely there is lots of background microwave energy constantly streaming by. Surely radio waves have been around as long as biology has been around. If radio was a good source of energy, nature would have already found a way. Maybe big bang radiation doesn't pack much of a wallop. Is it possible that communication intended radio is more energetic? More localized. Easier to exploit. I can imagine some type of group-dynamic in which individual floating animals or proto-animals learn to orient themselves such that they become a reflective parabola or fresnel lens concentrating radio energy to a focal point where other animals absorb the energy in some sort of symbiotic bio-community. Many other scenarios are conceivable.

Are plants learning to seed near highways to take advantage of air movement and carbon dioxide? There are a million ways in which human activity effects environments in ways that provide energy and stability clines. Surely life is reacting in step.

The pace of culture is so much faster than most organisms can genetically respond. The smallest organisms with the shortest life spans that have the greatest populations spread over the largest geographies are the organisms most likely to take advantage of our frenetic environmental messings.

Are they? Is anyone paying attention?

What is computing?

2009-08-01T14:46:00.001-07:00

This is the most important question of our time… yet so rarely asked. Computing technology increasingly shapes every aspect of human behavior, culture, resource use, health, commerce, and governance. A passive stance on the question that effects all other questions is increasingly dangerous to the future of all humans, of life, of evolution itself.

In the 60's we created NASA, an elaborately funded research program to uncover the knowledge and develop the technology to "go to the moon". Yet one would be hard pressed to justify the cost to society of contraptions that do nothing more than take a few people to a near-by rock… almost nothing of the NASA program can be used outside of the narrow focus of getting a few tens of miles off the surface of Earth (at tens of millions of dollars per pound).

Ironically, and inadvertently, the practical mathematics, programming, and computational techniques developed and honed by NASA in the pursuit of its expensive and arguably impractical goals may be the only pertinent contribution to show for the tens of trillions of dollars spend on this ill-concieved and irrational "research" program.

Talk about putting the cart before the horse… akin to building a global library system and book binding before developing a written language.

We are surrounded by lifeless rocks. We didn't need to send a few Air-force test pilots to the moon to figure that out. The practical scope of our chemically propelled rockets hardly avails us to the nearest little frozen or boiling neighbor planets in this corner of this one little Solar System. Ever attempt a phone conversation with 40 min. gaps between utterances?

The interesting stuff in this Universe (at least the small corner we have access to) is right here on our little Earth. It is us… and more than that, it is not so much what we have done, but what we will do and how what we will do effects what other future things will do because we set them into motion. That is our job. In a very real way, we are the first things that understand the job description despite the fact that it has always been there and has always been the same. This understanding should give us a leg up on the process. Should.

There are two kinds of knowledge: the first, historical, the second, developmental. When we go somewhere, we do nothing more than uncover that which already is. Compare this to development, where we create things that never were. In this universe, if there was a force that was prescient in creating one star or planet, that same force must have been prescient in the creation of Earth. We don't have to go to Mars to find the forces that created Earth. And we certainly don't need to send humans over there even if we do want intimate knowledge of a place like Mars.

At any rate, computing is a universal process. Computing is agnostic to domain. You can compute about particle physics and you can compute about knitting. Computing is an abstraction processing medium. Computing is what brains do. Computing is not restricted to the category that is biological minds. Learning how to compute is learning how to discover. The goal becomes the unknown… becomes un-prejudiced developmental discovery. The machinery of pattern matching… of salience… of the perception of essence across domains.

I am obsessed with this biggest "why" of computing. I don't think the computational "why" can be separated from the biggest "why" of existence in general... of evolution… of the march of complexity.

The convergence of thermodynamics (the way action effects energy dissipation) and information science (the relative probabilities of structure and the cost of access, processing and transference) guide my approach to these questions. Least energy laws dictate the evolution of all systems. Computing is evolution. Abstraction systems allow prediction. Prediction grants advantage. Advantage influences the topology of the future. The better a system gets at accurately abstracting it's environment, the more it will influence the future of abstraction systems. Computing is the mechanics of evolution... always has been. Are we designing computing to this understanding of the methodology of complexity handling?

Lets suppose we gave the scientists at NASA a choice. We ask them, "What technology represents a greater potential towards the eventual understanding and even physical exploration of the Universe, rocket engines or computers?", What would be the rational and obvious answer? If we ever hope to get any real distance in this universe it won't be by burning liquid oxygen and kerosene. Most things in this universe are millions of years away even at the speed of light. Rocket engines hardly move at all when compared with even the too-slow speed of light. Getting anywhere in this universe will demand tunneling beneath the restrictions that are space and time… no rocket engine will ever do that for us. I am not an advocate for space exploration, but if I was, I would be pushing computation over rocket propulsion.

It is time to advocate a culture wide push towards the advancement of an ever-expanding understanding of computing. To the extent we succeed, all of the future will be defined by and fueled by our discoveries. If we choose instead to spend our limited and most expensive money towards rockets we had better hope the universe can be understood through the understanding of explosions and destruction and spending long periods of time floating in space. Come on people! Think!

[ more to come… ]

Solar energy conversion… can it hurt the Earth?

2009-06-05T11:11:00.000-07:00

Note: before anyone accuses me of being anti-green, let me explain my general motivation and then the specific intent of this post. I don't think there is a more potent problem facing humanity (and all life) than the current man-caused spike in global temperature. If we do not act appropriately and quickly and at unprecedented scale, biology faces near-total destruction. The scale of this problem demands that our solutions be equally large. Large solutions of any kind will have both intended and unintended consequences. We must strip emotion and sentimentality from our assessment and design process. We must dump our pre-conceptions and deal with the physical dynamics as they are (not as we would like them to be).

Global heat delta as solar/wind is converted?

Almost every time solar energy is harnessed by human-built converters (to electricity or work), this energy is transmuted down the thermodynamic ladder faster and more localized than would "naturally" occur.

And its digression towards heat is localized (thermodynamic oxymoron I am aware). At the very least, the global atmospheric energy distribution budget is disturbed. Energy that used to go towards other dynamic dissipative systems (ocean and air currents, the fresh water cycle, etc.) is now siphoned off and downgraded to heat at a faster rate. This is especially true of systems like solar to electricity cells which convert some sunlight that would otherwise have bounced out into space.

Even wind and water current converters (turbines) pull kinetic energy from a large system, and localize (time and location) the thermodynamic degradation in non-natural ways.

In both cases, heat that would have dissipated down stream over a long period of time is removed instantly (much of which is immediately lost to heat in the conversion process) and sent to highly localized dissipative devices (lights, heaters, stoves, computers, washing machines, TVs, and industrial equipment). The placement of these end of the line dissipative devices is determined by human desire and not the simple thermodynamic least-energy topology represented in natural systems.

As we get better and better at exploiting solar energy to our own energy needs, more and more of the solar energy that drives large scale atmospheric phenomena will be removed from the standard atmospheric causality chain. What impact will this have on weather patterns? On ocean currents? On global temperature and temperature distribution? On annual seasons? On precipitation patterns?

Our planet's heat budget is to some extent regulated by the off-planet radiation of heat through infrared (and other) radiated wavelengths. How do our current human uses of electricity effect this radiated/mechanical heat fraction?

As compared to hydro-carbon oxidation?

To be sure, the oxidation of hydro-carbons (burning oil and gas) has a more radical effect on heat balance. But this has more to do with the fact that undisturbed oil and gas are only "potential" energy until we bring them to the surface and burn them. Solar energy conversion is not typically considered in light of thermodynamic process because it is assumed that this is energy that is used naturally anyway. But natural uses of solar energy drive planet wide dissipative engines upon which all life is distributed and timed.

To what extent will drastic increases in solar energy conversion effect these essential processes? Especially as humans continue to use more and more energy?

Is this a tipping point effected system?

I know that current solar conversion is probably such a small slice of the total earth-solar energy budget that these questions must seem daft. However, as we have seen in many natural systems, small changes can catalyze huge and unexpected out-fall effects. Disregarding "tipping point" sensitivity, how will ever increasing capture of solar energy for human use effect Earth-scale dissipative systems that support biology as it is currently represented?

Engineering done well

Here is what I suspect. We put solar conversion panels up where solar real-estate is cheap... on roofs or in deserts where other (agricultural) uses of that energy is not reasonable. These locations are locations where there is reason to have highly reflective surfaces. A well designed solar converter reflects as little energy as possible. Either way, I suspect that solar panels have different reflective behavior than other surfaces. Plants appear green because they absorb red (longer wavelength) light. Plants differentially reflect green and blue light. Solar panels are usually placed where plants aren't. But even if they replaced plants, their reflection/absorption properties would be different than plants. A plant converts solar to chemical energy in a respiratory process that absorbs carbon from carbon dioxide in the air and strips the carbon releasing pure oxygen.

Photovoltaic panels are not respiratory systems. This fact alone changes the environmental atmospheric equation.

But let us instead concentrate on panels that replace only other non-biological surfaces of various reflective and heat storage indices. The whole point of a well designed solar panel is to convert solar photonic energy to heat or electricity (or hydrogen) which can be transported or transmitted to other locations for immediate use (conversion back to heat through a chemical or mechanical process that results in work). This process differs from natural processes in important ways. It is usually faster degradation to heat. It is often localized differently than natural dissipative processes. And (if well designed and engineered) it is more absorptive than natural surfaces.

Randall

Motivation [anti-] matters...

2009-05-31T14:46:00.000-07:00

Recently, I stumbled across a post to a public online science discussion group. But, it wasn't the subject of the post that interested me. The subject was speculation about the existence of anti-matter galaxies "at the fringes of the universe". What makes this person's post worth commenting upon is the almost immeasurable difference between scientific thinking and non-scientific thinking. So… it's worth an short examination.

First what we think we know about anti-matter:

Every empirically derived model of the universe (standard model included) shows almost no remaining antimatter after just a short percentage of its current age. The same models show an almost 50/50 split at the first moment… and then a quick period of mater-antimatter annihilation resulting in the current matter domination (with a whole mess of residual dark matter and dark energy). Remember, antimatter isn't nether-worldly, it's just matter that is in some fundamental way, symmetrically inverted. An antimatter electron would, for instance, have a positive charge. Thats all. No magic, no otherworldliness, anti-matter is still matter… is every bit "material".

Now the question of rhetoric:

What fascinates me when discussions like this erupt is the "why" that drives the original post. Contrarianism is a cornerstone of Scientific thought. But when the motives driving contrarian ideas are not scientific, you can expect scientists to assign the standard "crackpot" label. Every time I investigate such a claim, every time I ask and get an answer to the question "What drives your interest in making this contrarian claim?", I get an anti-scientific answer. I get an answer that reveals a spiritual world view that necessitates some fundamental strangeness at the base of a "theoretical" framework or "cosmology". The strangeness is necessary to support a "physical" explanation for the meta-physical emotional experiences and needs the contrarian finds personally satisfying. It is endlessly fascinating to me that anti-scientific thinkers seek constantly to justify their emotional-experiential world view atop some sort of awkward and illogical re-imagining of science derived knowledge. In contrast, you will never see a scientist go to spirituality in support of his theory or experimentally derived data set. No scientist has ever or will ever work a verse from the Bible, or a witticism attributed to Buddha, Mohammad, Krishna, Confucius, or L. Ron Hubbard into a proof or theory. The anti-symmetry of these two behaviors is worth a well intentioned pause for thought.

The inward apologetic focus of spirituality is the opposite the outward focus and motivations of science. Science (scientists) are motivated by a desire to understand the universe… as it is… for what it is. A scientist tries all day long to disregard what it feels like to think or want or need, expects that their own personal emotional gestalt is forever slanted by evolutionary selection towards culture, gender, species, and bio-centric mechanisms that are physically embedded and unavoidable. A scientist is motivated to see beyond personal experience to the fabric from which it is derived and of which, perspective is just a tailing, a side effect. It is important here to specify the scientific classification of the self and self-experience. Science is frequently accused of being anti-self. This is the farthest from the truth. To science, the self and subjective experience is every bit as existent as any thing else in this universe. But in the same way that Copernicus re-figured the ontology of the Solar system, placing the Sun in the center and demoting Earth to the less central and less exclusive role of Planet, science views the self and experience as non-special, as one of, as a physical manifestation of order and causality specific to place and time and circumstance. The self, to a scientist is effect. It is weather, not atmosphere. It is concerto not violin. It is road trip, not station wagon.

A scientist says "My mind is flawed. My mind tells me things that it wants to hear. How can I construct methods and means to see the difference between what is and what I experience?" A scientist doesn't seek physical justification for flawed thinking. A scientist just plain expects it, deals with it, looks beyond it. A scientist posits causality at base. Builds an inverted pyramid of causality. At the lowest point in this pyramid, this hierarchy of influence, are the most basic of physical processes. We humans and our thoughts appear high up at the top of this ever expanding pyramid of influence and causality… meaning, what we do and think is much more effect than cause. Scientists expect and accept this. We don't seek means of rearranging the structure that built us to fit our emotional experiential needs. We just look for what is.

So, I have asked the author of the originating post; "What motivates your interest in the existence of anti-matter galaxies?"

Note: A whole slew of fringe (mathematically consistent?) theoretical models have been introduced by legitimate scientists that allow for the existence of contemporary pockets of anti-matter in a matter dominated universe such as ours. These alternative models (and far crazier ones as well) are introduced to test the validity of more dominant models, as a means of falsifying. But this process of constantly looking for error is motivated by an interest in discovery of the truth about what is. Again, this search for "What Is" is fundamentally different than a search for an explanation or justification for "What I Feel".

Randall

Some background information:

The early universe was opaque to light (for about 300 thousand years). The energies released (that still exist) were generally of a much higher frequency then visible light… gamma radiation. Plus, the universe was too hot and dense (millions of times hotter and denser than the first moment of an atomic bomb detonation) for atoms to form, so photons wouldn't stream past atoms as they do today, and instead interacted with the dense soup of nuclei and electrons. When the universe had expanded and cooled to the point necessary for atoms to form, photons (of all energies) were free to fly unimpeded as they do today… the universe was finally transparent. Then it was another 500 million years before stars were formed and ignited before the first location-specific photons began to flood out into the universe (the stuff we can see with our eyes, telescopes, and directional sensors).

Because of the expansion of the Universe the big bang (matter anti-matter) created gamma rays are now huge radio waves (many meters in wavelength). This is the cosmic background radiation… the hiss on your analog radio and TV.

Now, what an event horizon is, and what one can see, are two very different things.

It is important to remind our selves that seeing isn't an active process. Seeing is a passive act. Sure, the photons that hit our retina are active, but the only thing active about our eyes is that they react to photons that hit them. We don't "look" out into the cosmos. We passively receive stray photons that were created or reflected off of stuff at some distance (which always translates to some time in the past)… and only photons, which happen to be streaming along exactly in a path that intersects one of our eyes. Our eyes don't suck information in, they just sit and wait for what ever comes their way. The best we can do is point them in a particular direction.

The event horizon is the theoretical spherical limit to how far anything can go within a given period of time from when it was released. Typically when we are talking about an event horizon we are talking about a boundary dictated by the fastest anything can travel in space-time, which is the speed that light travels in a vacuum. Given the fact that this universe began as a singularity (as one point of zero spacial diameter), we are (as is everything) always at the center of that first primordial point. That is the really great, if somewhat confusing, thing about an expanding universe… where ever you are, if you are within this universe, you are at the the exact epicenter of the big bang that started it all.

This rule is true no matter how fast you are going or when you started going that fast. Distance itself is an attribute of space-time and space-time was created by the big bang. There is nothing remotely detectible, like distance (or time for that matter), that is or ever will be, outside of space-time.

Even stranger, if Einstein was correct (and everything we have ever measured seems to say that he was), energy and matter are directly tied to and dependent upon space and time. Add or subtract from any of these four and you directly effect the quantity of at least one of the other three.

The photons that bring us information about things far away (long ago) left a universe that was less and less like the one we live in today the longer ago they were made. The limits to what we will ever be able to "see" no matter how good our telescopes get, are dictated by when the universe became transparent to light. This is when light became directional. There is radiation all around us that isn't directional… or rather it was created before the universe allowed radiation to stream unimpeded in a strait line. This radiation is considered "noise" as it is incoherent (each photon is unrelated to each other photon). In this sense, it is like temperature, you can know things about the average of all of the photons (average wave length and amplitude) but anything you can measure about any one photon is missing any information that would tell us anything about source location.

That is the bugaboo about knowing anything about the very earliest universe. There was a very long period of time right after creation (scientific semantics) that we can never know much about. We can derive quantities as averages, but we can not know anything about specific spacial events or trends. The moment the universe went transparent is a boundary, before which we can only guess at location-specific layout of the universe. For all practical purposes, in this universe, the moment of transparency (the moment the universe got cool enough to allow the formation of atoms) is the only "event horizon" of any interest. This photon transparency horizon (300 thousand years after the big bang) has nothing at all to do with the theorized matter anti-matter annihilation epoch which occurred between about 10^-32 and 10^-12 seconds after the big bang.

Note: It is calculated that the observable matter dominated universe (photons, neutrons, protons and electrons) is the result of a 1 part in 1 billion majority of matter to anti-matter. The statement made earlier to the effect that "electrons are supposed to be positively charged" is complete hooey. Anti-matter is created everywhere in the universe that energies are high enough for fusion (in stars, supernova, and at black hole horizons). Such newly created anti-matter is annihilated the moment it contacts matter and this produces photons in the x-ray spectrum.

Future Salon speakers Jaron Lanier and Eliezer Yudkowsky square off

2009-03-21T17:30:00.001-07:00

Hey all (?),

Have any of you ever experienced the awkwardness of nervous "nerd" laughter... well the link below will provide a good example of what this is like. The link is to the Future Salon and in particular a video stream about half the way down the page entitled:

"Future Salon speakers Jaron Lanier and Eliezer Yudkowsky square off"

It is video conference phone call split screen debate between this Yudkowsky guy who is the head scientist at the Singularity Institute, and Lanier who has been the genius hippy in red dread locks since his early pioneering work with Virtual Reality and artificial vision systems.

Before you click the link, let me frame the debate.

These two guys represent the two extremes of a subtle range of viewpoints on evolution, AI, and human consciousness.

On one end you find the "Hard AI" camp (here represented by Yudkosky) which believes that intelligence is simply an emergent property of the physics of this universe and the evolutionary process, and so, should yield its secrets to scientific investigation and by extension, should be evolve-able and build-able or extend-able through directed pragmatic human effort.

On the other end of this polemic you find the "humanists". The humanists have trouble with the idea that consciousness is reducible to units that could be mechanized in a substrate other than biology or that intelligence could result from the computational gestalt in use today. Though his professional life consists of working on the kinds of computing problems many would label "AI", Jaron is one of these "humanists".

Jaron's main criticism of the hard AI camp in this debate is that their strong attachment to finding a way past death and their a-priori belief in the possibility of reasonably building self evolving intelligence together become so rhetorically invasive that they can no longer do objective investigation or engineering... that their beliefs and desires make them "religious".

Yudkoski could make an even stronger case against the same tendency towards the religiousness of the humanist position as it is based upon the extreme human-centrism that is the notion that consciousness is unique and magic in that it stands alone as something special to humans or biology... but he doesn't. I can't tell if he just doesn't realize that Jaron is by far the more religious of the two... or that he is just two nice to do so.

To me, this is not the logical scientific debate both seem insistent upon presenting, but between a Southern Baptist Minister and a Catholic Priest who are both under the self-delusion that they are more atheistic and objective than the other.

If you can stand the awkward nerd-fest mannerisms (Saturday Night Live could have a field day with these two characters), this little debate goes a long way in illustrating some of the deep philosophical polemics that seem to pop up anew with each new technology or cultural innovation and each new generation.

I can't win. Even in AI... in the field that best matches my own interests, I am a loner. I represent interests and motivations not expressed by anyone else.

I respect both of these researchers. Each is passionate and extremely well prepared for this debate and bring to it a lifetime of concerted thinking, experimentation, and theory. The debate is a spectacle: like a 1960s Japanese monster movie. And just as herky-jerky awkward. Very illuminating on so many many levels. This video could be the basis of a graduate thesis on science in the shadow of post-modern thought (confusion?).

From my perspective, Jaron is a nothing more than a (very bright) priest who can't stop doing science in the basement, and Yudkoswsky is nothing less than a scientist that can't help wanting to build a God.

Randall Reetz