The Ah-Ha! momentThe Ah-Ha! moment

The Ineffable Moment of Cognition

Other Ah-Ha moments
Other Ah-Ha moments

Since the dawn of time humans have gathered. Likely in the beginning doing so meant safety. There are a number of key revelations leading to the evolution of larger groups and integrating innovation. Sometimes the source of innovation was individuals. As local groups increased size and social innovation occurred over time governmental arrangements evolved. Ultimately groups became city states that  became nations. Languages, dialects, speech inflections, etc. all evolved as a function of interactions across those various organizations over time. To the right are various Ah-Ha! moments characterized by the person that experienced them. Necessity, has been observed, is the mother of invention. Ah-Ha! moments are the source of inspiration for many endeavors and creations from the well-spring of human imagination. In every case, an observation of ‘what is’ was filtered by ‘what might be’ because someone somewhere asked a very simple question: ‘what if’.

Human Perceived Reality

Every individual who has ever lived has experienced childhood. At some point growing up, presuming the individual accomplished that, lessons involving gravity took place in one manner or another. You fell or dropped an object. Perhaps it broke on the way back to that ancient camp fire. Perhaps you broke journeying back to that early settlement. The results of your trip and the knowledge you had gained was delayed or worse. Part of the point here is linking all of those various experiences with what is actually transpiring in order for us (e.g. physiologically) to cope and otherwise deal with that environment. Human physiological senses are made manifest by never cells connected by a Central Nervous System (CNS) linking them to our Brains where abstractions are instantly furnished so we might survive, cope, and deal with the implications and ramifications of those experiences.


Humans think that because their abstractions align with reality that they are describing how reality actually is when nothing could be further from the truth. All that means is that reality can instantiate that particular view, it does not mean that view completely describes reality in fact. As you will come to learn all the interferometer experiments ever performed all report essentially the same velocity for the speed of light. Consider the basis source of that phenomena. Can you affix a real common geometric basis for that phenomena? The short answer is it depends on which EIM you employ on whether or not you can accomplish that task. Which is more elegantly simple: dimensional restriction (which does not close to unification) or a process derived from the intrinsic nature of an EIM construct which does close to unification? Which answer has greater power? The reader here would likely think I was daft if I asserted that bullets come out of firearms at the same velocity because of a dimensional limitation on their speed. Perhaps you get the rhetorical point. The proper answer of course is that they achieve that velocity due to the intrinsic nature of the system that produced it. If perchance everything real was comprised of exactly that same system then that result would be pervasively and empirically measured to also be the same. Imagine that.

Once we have any given experiment whose consequences we know, and agree with experiment (e.g. empirical congruence) what we have in reality is a scenario in which reality supports a particular set of abstractions and their logically derived, relative and respective patterns and relationships. It does not mean that what we have done is to describe in totality exactly the intrinsic nature of actual reality. What it means is that reality instantiates that particular point of view. Those two scenarios are not the same thing. As evidence to this is the fact that theoretical physicists commonly come across situations where there are multiple theories all of which have the same consequences and all agree with experiment (e.g. the theories are simultaneously true). The question then becomes which theory “looks more natural”, and that criteria is somewhat subjective. Here is a video of Richard Feynman explaining exactly the same situation, but in 1950’s when he gave this lecture none of us could close our thinking to unification. Now we can.

Now consider what constitutes an expert in such an environment. What criteria does their professional organization support? Do any of those folks comprehend LEEs Empiricism Trap?

The Perplexities of Looking Up At Night

The night sky has enamored humanity since ancient times. From those long ago moments to modern Ah-Ha! moments deep within technological bastions of computers monitoring the latest incarnation of space telescope reporting on its probing missions deep into uncharted territory humanity has sought out to understand this thing we have come to call ‘The Universe’ or ‘The Cosmos’.

Calvin & Hobbs looking up
Calvin & Hobbs looking up

The Luminiferous Aether Experiment

As a matter of experience, it should be obvious that humans do not particularly care for change. Ultimately the reasons for that resistance might arguably be traced by to the discomfort felt resulting from established familial neural patterns being reconfigured because of new experiences or learning. All of which took place as a function of (e.g. enabled by) neural plasticity. The salient point emerging from these observations and insights distinguishes mental patterns from those in the real world, where they all collide within the confines of our brains. Some are confused by that. Hold these various thoughts for a minute because looking up at night into the heavens inspires the virtual realm within us because we can’t experience it in any other manner except to look up. Consequently we build instrumentality to assist us with those observations. What is not obvious about any of those endeavors is that instrumentality is intrinsically created to operate relative to and respective of human physiology. As our understanding grew so did the sophistication of not just the instruments but the abstractions they sought to measure or detect.

Circa 1887 the vast majority of scientists believed in something called the Luminiferous Aether, which was described then as a perfectly transparent, perfectly viscous, medium within which all of the stars and planets existed. It was the medium of the Universe. Two scientists: Albert Michelson and Edward Morley, in that year set out to detect this medium with a device they constructed called an interferometer. The device they build was fantastically sensitive. So much so it easily detected the hoof steps of horse drawn carriages passing by their building in Cleveland, Ohio at what is now Case Western Reserve University. Simplistically the device split a beam of light along two paths at right angles and then recombined them exploiting the wave nature of light to display the resulting interference pattern. The point was that if either beam path was disturbed in the slightest manner, for any reason, that device would instantly report that moment because the displayed pattern would instantly be reported  by the device. The device worked perfectly. The only problem was that it never detected the luminiferous aether. It did not matter what time of day, nor night, nor season, nor year. All of which meant it did not matter where the Earth was in its orbit about the sun, nor its rotation, nor even our star’s travel in its parent galaxy the milkyway. The device reported that the speed of light was always the same and that fact stunned the scientific community at the time. It was so not expected that their experiment has been called the most important failure in scientific history.

Fabric Of Industry Drove Technology

In 1804 Joseph Marie Jacquard demonstrated a mechanism to automate loom operation. A number of punched cards were linked into a chain of any length. Each card held the instructions for shedding (raising and lowering the warp) and selecting the shuttle for a single pass. These first steps toward enabling the information age brought with it essential awareness of not just what is empirically before our proverbial noses but what must irrefutably be. Reality instantiates our perceptions allowing us to manipulate our environment in order to survive. True as that statement may be it is also important to realize that evolution made manifest our Central Nervous Systems (CNS) and our brains, which together instantly furnish us with abstractions in order to relate to that instantiated point of view. Because not everyone correctly interprets reality is exactly why we have a jury decide legal precedent. Neural plasticity allows us to learn. Neurons that fire together, wire together. The very direct implication is a great deal more important than simple pattern development. The implication is that those patterns can change, and at the direction of our willingness to perceive and engage the new vision. Programs designed to recognize such patterns and to specifically set new patterns conduct a process here called Neural Network Reconfiguration by Programming (NNRP). Those abstractions our physiology instantly furnishes us is something of a fine lubrication layer between us and reality. It is for these and other reasons that we actually need multiple logically correct views of exactly the same system. What this process and framework brings to the proverbial table/party is the ability to integrate a plurality of viewpoints and ask hard questions of each and drawing on the combined learning across all domains of discourse, their constituent detail sets, and disciplines. What we find highly ironic about all of this, especially in context of the unified Universe, is that it inexorably leads to a conscious universe, even if it is only at our individual scales. That holds some profound considerations.

Charles Babbage’s Difference Engine

Duplication of Charles Babbage's Analytical Engine in IBM CHQ Lobby in Armonk, NY
Duplication of Charles Babbage’s Analytical Engine in IBM CHQ Lobby in Armonk, NY

Circa 1820, obviously before Michelson and Morley began their collaboration, an English polymath named Charles Babbage designed a mechanical machine to solve arithmetic problems. An ancient idea for such efforts that perhaps began with the earliest knots on ropes, depressions in cuneiform tablets, or abacus counting instruments, his device was called a difference engine and used an array of inter-operating gears. These lines of effort ultimately spawned the Information Technology industry and information sciences disciplines. These timelines are salient here because it is important to note that the professional organization for systems engineering (e.g. INCOSE) was not formed until 1990, some 170 years after Charles Babbage’s early work.

Einstein’s Thought Experiments

The failure of the luminiferous aether experiments bothered everyone in the scientific community, including Hendrik Lorentz, and one Albert Einstein. It made no sense to anyone that no matter how the device Michelson and Morley had created always reported the same number. The device was mounted on a massive block of granite floating in a pool of mercury. It was not directly sitting on the foundation of the building and could rotate 360 degrees. In his book entitled Relativity he wrote that by taking time to be a fourth dimension of space “solved certain problems”. He was then and remains today correct, it does.

The Business Of Information

Information system evolved from those early endeavors as the need progressed from solving simple mathematics to more sophisticated problems. Herman Hollerith determined that data in specified locations on a card, arranged in rows and columns, could be counted or sorted electromechanically. A description of this system, An Electric Tabulating System (1889), was submitted by Hollerith to Columbia University as his doctoral thesis. In 1911, four corporations, including Hollerith’s firm, were amalgamated to form a fifth company, the Computing-Tabulating-Recording Company (CTR). Under the presidency of Thomas J. Watson, CTR was renamed International Business Machines Corporation (IBM) in 1924. By 1933 The Tabulating Machine Company name had disappeared as subsidiary companies were subsumed by IBM.

Key Internet Benchmark

As it happens I was assigned as the marketing lead for IBM on the development of a new operating system called then OS/2 Warp and so what I write here are my recollections from 1st hand experience and history. Should anyone question this simply find a copy of the packaging for that operating system circa 1994. The guys in the lab used my machine to capture the graphics used in the iconography on the packaging. Consequently my name wound up on the front of the box. I didn’t know they did that until it was well after the fact, so it was not by design that that happened. In any event it corroborates what I write here. OS/2 Warp was the first commercially available operating system designed to put consumers out on the real Internet in three (3) mouse clicks. The team delivered in 100 days a product that would work in 80+ countries, >23 languages, and required unheralded teamwork worldwide. I point these things out not to brag but to establish a basis for the insights that followed. When a computer connected at the time, it did so usually through a dial in link. Corporate customers had networks but consumers at the time almost never did, that came later usually via cable companies. The point here is that when the consumer computer connects to the network it does so through an ISP (internet service provider). The ISP employs a computer specifically for that purpose and on that computer is something called a ‘translation table’. The translation table lists human readable URL addresses and relates them to computer readable location addresses today in either IPv4 or IPv6 formats.

Moment of Inspiration

I had studied aerospace engineering in school but went to work at IBM. When I left IBM in 2003 my avocations found me tinkering in astrophysics. Circa 2004 I was working on a project involving impact dynamics across the solar system and the details were not adding up. Phenomena at one scale did not mach what nature was demonstrating at other scales. The usual rationalization of oh just switch from Newtonian to Relativistic, or oh that happens at the quantum level, were just not sufficient to bring together the issues in front of me. I had Einstein’s papers scattered on my desk, one of which happened to be in my hand. As I stood up, paper in hand, muttered “well that makes sense” and in that instant, I froze. I repeated that phrase over and over and over again until it became “that makes logical sense”.  In that moment I understood the relationships between logical representation of physics from instantiation of actual reality. I took the concept of Internet translation tables and created what are now here called Translation Matrices. The first layer therein is called the 2D Articulation Layer and juxtaposes Paradigms Of Interest/Nature (POI/N) with Encapsulated Interpretative Models (EIMs) instantiating that POI/N within the context it makes manifest.  I thought to myself that I could not be the only one to have stubbed their toe on this notion and began a research quest to see if anyone had done a full treatment of this subject. That’s when I found one Susanne K Langer whose body of work had dealt with exactly these issues, and astounding as it may be, did so in 1948. The essential take away from all this centers on the implications and ramifications of humans using abstractions created both naturally via our CNS or anthropogenically, (through information sciences/technology). According to Langer, mistaking abstractions for actual reality is epistemologically fatal and we herein now call such mistakes: Langer Epistemology Errors or LEEs in honor of Susanne K Langer‘s body of work. The ensuing original systems review consumed from 2004 until 2019 developing what has become The Emergence Model.

  1. The salient take away is that what Albert Einstein created beginning in 1905 is absolutely 100% logically correct, and therein lay the strategic clue needed to gain the precipice of unification.
  2. Cognition of the implications and ramifications of commission of Langer Epistemology Errors (LEEs), (e.g. mistaking abstractions for actual reality),
  3. Modern Information Sciences illuminating to illustration that something can be logically correct yet remain in reality different. The only requirement is that ‘what is real’ instantiate that logical view.

To understand the motivation behind all this requires a brutally honest assessment of why what it is we think we all know does not close to unification. Part of the answer to why it has taken so long to understand has to do with our evolutionary roots harking all the way back to those ancient camp fires. We have this centralist, flocking, tendency that to characterize might elicit words like conceit or arrogance. Sagan was nice about it, he just said some folks are fully of baloney. Consequently we had to mode shift his baloney detection kit.


Neural Networks And Cognitive Velocity

True vs Truth
True perspective of truth.

How many times have you you engaged someone who simply could not comprehend your point of view? Did either or both of you find truth in the respective perspectives? How did you (both) know?

Cognitive Velocity

First we have to know what constitutes the source of truth we seek to align. Elegant Reasonism epistemologically seeks truth as a philosophical predicate priority entering any constituent domain of discourse, including but not limited to: axiology, epistemology, ontology, science, and supervenience. Rhetorically, let’s presume you have some truth down on paper, and then let’s presume you comprehend and otherwise understand what it is you wrote down. Then let’s even say that truth is in full standards based compliance with the unified Universe. The very direct implication then is that truth also exists within the neural network patterns of your central nervous system (CNS) and Brain. Cognitive velocity then is the measure of how long it takes from encountering a pattern before you recognize its fundamental truth represented by that neural network pattern inside you. The same would be true for any A.I. system.

Exacerbating this issue are contextual truths based on interpretative EIMs which, congruent as they may be, do not close to unification. What does that tell you about the truth that information promulgates? Exactly the point here. Perhaps for the first time you realize that there may be a distinction between what you thought you knew and truth as a function of the unified Universe. The size of that gap is at least a portion of the learning journey you embark upon, if you step on that path. In the immortal words of Morpheus, I can show you the door but you have to walk through it. When you gain a precipice enabling you to juxtapose what is truth in order to see what is true from multiple perspectives, you really need to take slow pause and ask what is enabling you to gain cognition. What unseen, unmentioned capability must exist in order for your to have the ability to perceive that truth and can others follow in your footsteps. The answer here is Elegant Reasonism and absolutely resoundingly yes. Why? In short, fully compliant rigorous application of the process and framework enabling effective mode shifting of POI/N EIM to EIM to established standards. The real test will come when you can wield those skills conversationally. When you can do that, you are then faced with the ethics of how and when you accomplish and deploy that skill, and to that end I very strongly encourage you to do so transformationally, because many are not yet ready to encounter the answers that will result. They think they want to know those answers but they have no idea how fundamental these answers truly are.

Seeing As You Look

Optical Illusions
Can You Mentally Flip These At Will?

When you can flip the plates is perhaps of interest. How long did it take you to do that. At least a second or two perhaps. Now flip the plates back. Now flip the plates back and forth, at will. That’s a different skill.

New experiences are filtered through the paradigm stacks we have built over the course of our lives inclusive of everything we have learned and experienced and the various abstraction sets through which all of that was filtered. The more fundamental any given paradigm is within that paradigm stack manifesting your worldview, the harder it will be to change or update it. You may intellectually understand it needs to change, but do you have the will to make it happen so that it represents a new metric for cognitive velocity?

Paradigm shifts are not easy to affect to any great effect. This is most especially true for fundamental paradigms, and here I must point out that the abstractions representing core constructs of a given EIM are basic. There are no more fundamental paradigms than those. They can not be parsed to lower levels. The very direct implication is that if you do not understand those then you have no hope of understanding systemic implications or ramifications.

There is in that insight two lessons. One has to do with the systemic implications of whether or not your paradigm stack (e.g. worldview) is in alignment with the unified Universe or not. The other is a bit more subtle and takes mettle to engage. What happens when whatever you are investigating can not be reconciled by those fundamental paradigm sets? What do you do then?

What happens if your fundamental abstraction set establishes patterns and relationships which philosophically do not close to unification? That scenario is one reason that Elegant Reasonism requires the use of at least one EIM that does in fact close to unification. To show you those implications as you enable mode shifting for your investigation (e.g. illuminate to illustration).

Context vs Congruent Truth

Circa 2024 there are eight recognized Encapsulated Interpretative Models (EIMs), enumerated M0 through M7, and each may have any number of iterations depending on how investigators set up their ISO 9001 Unification Tool, or its effective equivalent. Systems engineering principles for all master models there are two views, one logical and one real. I hate bringing this up because inevitably newbies, scientists, and engineers immediately want to jump on the one labeled as real. You really do not want to do that. In the case of The Emergence Model, M5 represents the logical EIM and M6 represents the real EIM instantiating M5. Perhaps ironically, M6 also instantiates M0, M1, and M2. We can illuminate that to illustration by employing M4 and shifting parameter values around. Interesting as all that might be, in context of avoiding commission of Langer Epistemology Errors (LEEs) and civilization not being developed enough to wield measurements effectively enough to work with M6 as a primary EIM, our choice then comes down to employing M5 as the fully compliant primary EIM closing to unification. Part of the point I am attempting to make here is that just because The Emergence Model does in fact close to unification, does  not mean it will always answer every question. What it does is establish context. Remember, in our quest to avoid commission of LEEs we never want to rest on our laurels. There may be a better EIM than anything we happened to have developed. If perchance someone is able to do that, then the advent is positive because the process and framework only get stronger. So my message is if you think a net new EIM is needed, then go for it.

The caution however is maybe a different point. There are ardent defenders of status quo thinking modeling reality. Many are blinded by past successes. Why they are where they are is here irrelevant. Having an EIM that is logically correct for the circumstances we employ it is useful. M1 and M2 have provided civilization with fantastic accomplishments despite the fact that they do not close to unification and nor will they ever because they are philosophical predisposed not to close. Why? Because nothing real can transition the spacetime-mass interface without first conversion to energy under those EIMs, by their own rules. I don’t care how ardent anyone is they will never change that hard cold fact.

The point of this caution is this: pickup your evidentiary bag and look at it objectively also in context of Langer Epistemology Errors. Consider honestly the implications of LEEs Empiricism Trap. Now, quantifying and codifying the gradient between actual reality (where we can not go) and recognizing the abstraction lens set through which we all go on our way to working with the manner reality instantiates what it is we think we know – Does that abstraction set you use close? Yes Or No. Are you using all that congruence and pass successes to justify the context of the EIM you use or actual alignment with the unified Universe? I would argue that if you are not justifying the unified Universe then you are on the wrong page, and I don’t care how ardent you may be.


Game Theory

Eye Exam Diopter Device
Eye Exam Diopter Device

Consider rhetorically whether or not you can apply mathematics within the virtual realm of an online game and then the distinctions between that environment and a scientific laboratory environment. The answer is that they are both using the same equations; its just that the former manipulates the values employed in order to make their avatars possess the characteristics they do, whereas the latter adheres to values empirically established by science. In essence what you see is a function of the filters in place. Now imagine what would happen if those filter sets were swapped out enmass in order to allow you to directly perceive the entire electromagnetic spectrum, for example. Now let’s take this imaginary case a step further, suppose that the entire model establishing fundamental interpretative context of reality were swapped out. That’s exactly what Elegant Reasonism does. Do specific patterns and relationships change Encapsulated Interpretative Models (EIMs) to EIM? Yep, they absolutely do. Does fundamental context change EIM to EIM? Yep, it sure does. Does that mean we can not describe a given phenomena as it is made manifest by one EIM for another EIM unless we are in that other EIM and can then juxtapose the two contexts relative to the same Paradigms Of Interest/Nature (POI/N)? Correct, that’s exactly what happens. This is exactly the set of circumstances established and otherwise enabled by the 2D Articulation Layer of Translation Matrices.

Insights must be presented in full cognizance of the means by which they were developed or they will be taken out of context.

The Challenge Going Forward

The primary challenge manifesting itself is that everyone believes new information should be presented in existing context. No one was more surprised than me or us that EIMs are the mechanisms making fundamental interpretative context manifest. If we presume that Langer Epistemology Errors (LEEs) are a bad thing and that we should not commit them then that establishes a very fine line we should strive not to cross, but in doing so creates a liberating situation for investigators. Please allow me to elaborate. When we erroneously commit LEEs we fall into the impression that we are working directly with reality and that that is just that (e.g. the end of the road). However, when we realize that what we have just proven with a given paper or investigation only establishes logical congruence within a logically correct EIM’s set of phenomena or behaviors reflected by a given set of abstractions all of which are instantiated by a reality that may also instantiate other EIMs; well, then we are free to explore those other situations and EIMs. When we follow the process and complete the framework, especially the 2D Articulation Layer, we enable essential mode shifting across the POI/N central to our investigation. If perchance you want to believe that The Emergence Model, for example, is hogwash and you want to go develop your own – go for it. You will of course have to justify your quest across all concept sieves, scales, constructs, and then match all of that to the unified Universe (which necessarily means you are going to have to show why what you are working on is better than what we already have). Our original systems review notes are all here and online for your reference and review. So is our User Library. There is no hard rule requiring use of The Emergence Model, but there is a hard rule requiring at least one EIM employed by every investigation close to unification. If subsequent EIMs are developed that also close to unification then that eventuality only serves to increase the effectiveness of what we have here.

It is our experience that insights should only be delivered in context of cognizance of the process and framework used to develop them. Any other articulation of such insights will lack fundamental interpretative context and communications will break down. That is to say insights in context of the unified Universe must be delivered to an audience that understand the means used to derive them. Only then will communications about those insights be effectively delivered (e.g. have needed traction). This warning is something global enterprise, executive management, administrators and leadership should take very seriously.



The quest to understand unification has been sought after in a variety of different domains, but they have all missed an essential point: that unification demands and requires the credible reintegration of everything real. This is not a discussion exclusive to astrophysics or any other specific and isolate domain, but one in which the relationship between them all is rendered with clarity, no matter how restful the relationship might be. We have shown to the satisfaction of our stakeholders linkage spanning domains of discourse ranging from art appreciation via Susanne K Langer‘s body of work, to subjects like economics via Ludwig von Mises body of work. The point here is the ground work has been laid and rendered that unification is real and it is here now. The rest is up to you to carry on and build on what we started.

We look forward to your mode shifted insights. Sic’em…



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By Charles McGowen

Charles C McGowen is a strategic business consultant. He studied Aerospace Engineering at Auburn University '76-'78. IBM hired him early in '79 where he worked until 2003. He is now Chairman & CEO of SolREI, Inc. ORCID: