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

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

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 Incomputable Heaviness of Knowledge

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

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

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

The Life And Times Of Your Average Paradigm

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?

Biology Is Too Slow!

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?

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… ]