## Why is it so hard to prove that e+pi or e*pi is irrational/rational?

The reason why it is so hard to prove is actually very easy to answer. These constants, identities, and variations being referred to in this post, and others like it, all lay embedded in a far deeper substrate than current mathematics has yet explored.

Mathematics has been, and always shall be my ‘first love’, and it has provided for me all of these years. I am not criticising mathematics in any way. It is my firm belief that mathematics will overcome this current situation and eventually be quite able to examine these kinds of questions in a much more expansive and deeper way.

We need to extend our examination of mathematical knowledge, both in depth and in scope, out farther and in deeper than numbers (sets and categories as well – even more below) have yet done. I’ll introduce you to a pattern you may have already noticed in the current stage of our mathematical endeavour.

We all know there are numbers which lay outside of Q which we call Irrational numbers. There are also numbers which lay outside of R which we call Imaginary numbers. They have both been found, because the domain of questioning exceeded the range of answers being sought within the properties each of those numbers. This pattern continues in other ways, as well.

We also know there are abstractions and/or extensions of Complex numbers where the ‘air starts to get thin’ and mathematical properties start to ‘fade away’: Quaternions, Octonians, Sedenions,…

This pattern continues in other ways: Holors, for example, which extend and include mathematical entities such as Complex numbers, scalars, vectors, matrices, tensors, Quaternions, and other hypercomplex numbers, yet are still capable of providing a different algebra which is consistent with real algebra.

The framing of our answers to mathematical questions is also evolving. Logic was, for example, limited to quite sophisticated methods that all were restricted to a boolean context. Then we found other questions which led to boundary, multi-valued, fuzzy, and fractal logics, among a few others I haven’t mentioned yet.

Even our validity claims are evolving. We are beginning to ask questions which require answers which transcend relationship properties such as causality, equivalence, and inference in all of their forms. Even the idea of a binary relationship is being transcended into finitary versions (which I use in my work). There are many more of these various patterns which I may write about in the future.

They all have at least one thing in common: each time we extend our reach in terms of scope or depth, we find new ways of seeing things which we saw before and/or see new things which were before not seen.

There are many ‘voices’ in this ‘mathematical fugue’ which ‘weaves’ everything together: they are the constants, variations, identities, and the relationships they share with each other.

The constants e, π, i, ϕ, c, g, h  all denote or involve ‘special’ relationships of some kind. Special in the sense that they are completely unique.

For example:

• e is the identity of change (some would say proportion, but that’s not entirely correct).
• π is the identity of periodicity. There’s much more going on with $\pi$ than simply being a component of arc or, in a completely different context, a component of area

These relationships actually transcend mathematics. Mathematics ‘consumes’ their utility (making use of those relationships), but they cannot be ‘corralled in’ as if they were ‘horses on the farm’ of mathematics. Their uniqueness cannot be completely understood via equivalence classes alone.

• They are ubiquitous and therefore not algebraic.
• They are pre-nascent to number, equivalence classes, and validity claims and are therefore not rational.

These are not the only reasons.

It’s also about WHERE they are embedded in the knowledge substrate compared to the concept of number, set, category…. They lay more deeply embedded in that substrate.

The reason why your question is so hard for mathematics to answer is, because our current mathematics is, as yet, unable to decide. We need to ‘see’ these problems with a more complete set of ‘optics’ that will yield them to mathematical scrutiny.

Question on Quora

## Getting Hypertension About Hyperreals

(Links below)

This system is quite interesting if we allow ourselves to talk about the qualities of infinite sets as if we can know their character completely. The problem is, any discussion of an infinite set includes their definition which MAY NOT be the same as any characterisation which they may actually have.

Also, and more importantly, interiority as well as exteriority are accessible without the use of this system. These ‘Hyperreals’ are an ontological approach to epistemology via characteristics/properties we cannot really know. There can be no both true and verifiable validity claim in this system.

## Knowledge Representation – Fractal Torus 1

Fractal Torus 1 by Ryan Cameron on YouTube

## Lateral Numbers – How ‘Imaginary Numbers’ May Be Understood

First, allow me to rename theses numbers during the remainder of this post to lateral numbers, in accordance to the naming convention as was recommended by Gauss. I have a special reason for using this naming convention. It will later become apparent why I’ve done this.

If we examine lateral numbers algebraically, a pattern emerges:

### $i^8 = i^4 \cdot i^4 = (1)(1) = 1$

When we raise lateral numbers to higher powers, the answers do not get higher and higher in value like other numbers do. Instead, a pattern emerges after every 4th multiplication. This pattern never ceases.

All other numbers, besides laterals, have a place on what currently is called the ‘Real number line’.

I qualify the naming of the Real Numbers, because even their conceptualisation has come into question by some very incisive modern mathematicians. That is a very ‘volatile’ subject for conventional mathematicians and would take us off on a different tangent, so I’ll leave that idea for a different post.

If we look for laterals on any conventional Real number line, we will never ‘locate’ them. They are found there, but we need to look at numbers differently in order to ‘see’ them.

Lateral numbers solve one problem in particular: to find a number, which when multiplied by itself, yields another negative number.
Lateral numbers unify the number line with the algebraic pattern shown above.

2 is positive and, when multiplied by itself, yields a positive number. It maintains direction on the number line.

When one of the numbers (leaving squaring briefly) being multiplied is negative, the multiplication yields a negative number. The direction ‘flips’ 180° into the opposite direction.

Multiplying -2 by -2 brings us back to the positive direction, because of the change resulting in multiplying by a negative number, which always flips our direction on the number line.

So, it appears as if there’s no way of landing on a negative number, right? We need a number that only rotates 90°, instead of the 180° when using negative numbers. This is where lateral numbers come into play.

If we place another lateral axis perpendicular to our ‘Real’ number line, we obtain the desired fit of geometry with our algebra.

When we multiply our ‘Real’ number 1 by i, we get i algebraically, which geometrically corresponds to a 90° rotation from 1 to i.

Now, multiplying by i again results in i squared, which is -1. This additional 90° rotation equals the customary 180° rotation when multiplying by -1 (above).

We may even look at this point as if we were viewing it down a perpendicular axis of the origin itself (moving in towards the origin from our vantage point, through the origin, and then out the back of our screen).

###### [If we allow this interpretation, we can identify the ‘spin’ of a point around the axis of its own origin! The amount of spin is determined by how much the point moves laterally in terms of i. We may even determine in which direction the rotation is made. I’ll add how this is done to this post soon.]

Each time we increase our rotation by multiplying by a factor of i, we increase our rotation another 90°, as seen here:

and,

The cycle repeats itself on every 4th power of i.

We could even add additional lateral numbers to any arbitrary point. This is what I do in my knowledge representations of holons. For example a point at say 5 may be expressed as any number of laterals i, j, k,… simply by adding or subtracting some amount of i, j, k,…:

5 + i + j +k +…

Or better as:

[5, i, j, k,…]

Seeing numbers in this fashion makes a point n-dimensional.

## Are sets, in an abstract sense, one of the most fundamental objects in contemporary mathematics?

Yes and no.

The equivalence relation lies deeper within the knowledge representation and it’s foundation.

There are other knowledge prerequisites which lie even deeper within the knowledge substrate than the equivalence relation.

The concepts of a boundary, of quantity, membership, reflexivity, symmetry, transitivity, and relation are some examples.

http://bit.ly/2wPV7RN

## Universal Constants, Variations, and Identities #19 (Inverse Awareness)

Universal Constants, Variations, and Identities
#19 The Inverse Awareness Relation

The Inverse Awareness Relation establishes a fundamental relationship in our universe:

Micro Awareness = $\dfrac{1}{scope}$ and Macro Awareness = $\dfrac{1}{depth}$ or $\dfrac {Micro Awareness}{Macro Awareness} = \dfrac{depth}{scope}$ Which essentially state: The closer awareness is in some way to an entity, the more depth and the less scope it discerns. The farther awareness is in some way to an entity, the more scope and the less depth it discerns. (Be careful, this idea of closeness is not the same as distance.) 
 May 15, 2017 | Categories: Discernment, Holons, Holors, Hyperbolic Geometry, Identities, Insight, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Mathesis Generalis, Mathesis Universalis, Metamathematics, Metaphysics, Philosophy, Philosophy of Language, Philosophy of Learning, Philosophy Of Mind, Semantic Web, Semantics, Understanding, Universal Constants, Variations, and Identities, Variations, Wisdom | Tags: knowledge, Language, learning, Linguistics, LogicaUniversalis, Mathesis Universalis, Philosophia Universalis, Philosophy, Philosophy of Language, Philosophy of Learning, Philosophy Of Mind, understanding | Leave a comment 
 Is Real World Knowledge More Valuable Than Fictional Knowledge? No. Here an excerpt from a short summary of a paper I am writing that provides some context to answer this question: What Knowledge is not: Knowledge is not very well understood so I’ll briefly point out some of the reasons why we’ve been unable to precisely define what knowledge is thus far. Humanity has made numerous attempts at defining knowledge. Plato taught that justified truth and belief are required for something to be considered knowledge. Throughout the history of the theory of knowledge (epistemology), others have done their best to add to Plato’s work or create new or more comprehensive definitions in their attempts to ‘contain’ the meaning of meaning (knowledge). All of these efforts have failed for one reason or another. Using truth value and ‘justification’ as a basis for knowledge or introducing broader definitions or finer classifications can only fail. I will now provide a small set of examples of why this is so. Truth value is only a value that knowledge may attend. Knowledge can be true or false, justified or unjustified, because knowledge is the meaning of meaning What about false or fictitious knowledge? [Here’s the reason why I say no.] Their perfectly valid structure and dynamics are ignored by classifying them as something else than what they are. Differences in culture or language even make no difference, because the objects being referred to have meaning that transcends language barriers. Another problem is that knowledge is often thought to be primarily semantics or even ontology based. Both of these cannot be true for many reasons. In the first case (semantics): There already exists knowledge structure and dynamics for objects we cannot or will not yet know. The same is true for objects to which meaning has not yet been assigned, such as ideas, connections and perspectives that we’re not yet aware of or have forgotten. Their meaning is never clear until we’ve become aware of or remember them. In the second case (ontology): collations that are fed ontological framing are necessarily bound to memory, initial conditions of some kind and/or association in terms of space, time, order, context, relation,… We build whole catalogues, dictionaries and theories about them: Triads, diads, quints, ontology charts, neural networks, semiotics and even the current research in linguistics are examples. Even if an ontology or set of them attempts to represent intrinsic meaning, it can only do so in a descriptive ‘extrinsic’ way. An ontology, no matter how sophisticated, is incapable of generating the purpose of even its own inception, not to mention the purpose of the objects to which it corresponds. The knowledge is not coming from the data itself, it is always coming from the observer of the data, even if that observer is an algorithm. Therefore ontology-based semantic analysis can only produce the artefacts of knowledge, such as search results, association to other objects, ‘knowledge graphs’ like Cayley,… Real knowledge precedes, transcends and includes our conceptions, cognitive processes, perception, communication, reasoning and is more than simply related to our capacity of acknowledgement. In fact knowledge cannot even be completely systematised; it can only be interacted with using ever increasing precision. [For those interested, my summary is found at: A Precise Definition of Knowledge – Knowledge Representation as a Means to Define the Meaning of Meaning Precisely: http://bit.ly/2pA8Y8Y May 11, 2017 | Categories: Consciousness, Insight, Knowledge, Language, Learning, Linguistics, Mathesis Generalis, Mathesis Universalis, Metamathematics, Metaphysics, Philosophy, Philosophy of Language, Philosophy of Learning, Philosophy Of Mind, Semantic Web, Semantics, Understanding, Wisdom | Tags: Big Data, Characteristica Universalis, insight, knowledge, Knowledge Representation, Language, learning, Linguistics, Logica Universalis, Mathematica Universalis, Mathesis Universalis, Metaphysica Universalis, Metaphysics, Philosophia Universalis, Philosophy, Philosophy of Language, Philosophy of Learning, Philosophy Of Mind, Scientia Universalis, Semantic Web, Semantics, understanding, wisdom | Leave a comment Does Knowledge Become More Accurate Over Time? Change lies deeper in the knowledge substrate than time. Knowledge is not necessarily coupled with time, but it can be influenced by it. It can be influenced by change of any kind: not only time. Knowledge may exist in a moment and vanish. The incipient perspective(s) it contains may change. Or the perspective(s) that it comprises may resist change. Also, knowledge changes with reality and vice versa. Time requires events to influence this relationship between knowledge and reality. Knowledge cannot be relied upon to be a more accurate expression of reality, whether time is involved or not, because the relationship between knowledge and reality is not necessarily dependent upon time, nor is there necessarily a coupling of the relationship between knowledge and reality. The relationships of ‘more’ and ‘accurate’ are also not necessarily coupled with time. Example: Eratosthenes calculated the circumference of the Earth long before Copernicus published. The ‘common knowledge’ of the time (Copernicus knew about Eratosthenes, but the culture did not) was that the Earth was flat. May 10, 2017 | Categories: change, Consciousness, Insight, Knowledge, Knowledge Representation, Learning, Mathesis Universalis, Metamathematics, Metaphysics, Philosophy, Philosophy of Language, Philosophy Of Mind, Semantic Web, Semantics, Understanding, Wisdom | Tags: Awareness, Characteristica Generalis, Characteristica Universalis, Discernment, insight, knowledge, Knowledge Representation, learning, Logica Generalis, Logica Universalis, Mathematica Generalis, Mathematica Universalis, Mathesis Generalis, Mathesis Universalis, Metaphysica Generalis, Metaphysica Universalis, Metaphysics, Philosophia Generalis, Philosophia Universalis, Philosophy of Language, Philosophy of Learning, Philosophy Of Mind, Scientia Generalis, Scientia Universalis, understanding, wisdom | Leave a comment What About Tacit Knowledge? A knowledge representation system is required. I’m building one right now. Mathesis Universalis. There are other tools which are useful, such as TheBrain Mind Mapping Software, Brainstorming, GTD and Knowledgebase Software Products and technologies like TheBrain, knowledge graphs, taxonomies, and thesauri can only manage references to and types of knowledge (ontologies). A true knowledge representation would contain vector components which describe the answers to “Why?” and “How does one know?” or “When is ‘enough’, enough?” (epistemology). It is only through additional epistemological representation that tacit knowledge can be stored and referenced.   May 5, 2017 | Categories: Knowledge, Knowledge Representation, Language, Learning, Linguistics, Mathesis Generalis, Mathesis Universalis, Metamathematics, Wisdom | Tags: Big Data, Characteristica Generalis, Characteristica Universalis, insight, knowledge, Knowledge Representation, learning, Linked Data, Logica Generalis, Logica Universalis, Mathesis Generalis, Mathesis Universalis, Metaphysica Generalis, Metaphysica Universalis, Philosophia Generalis, Philosophia Universalis, Scientia Generalis, Scientia Universalis, Semantic Web, Smart Data, Tacit Knowledge, understanding, wisdom | Leave a comment Universal Constants, Variations, and Identities #18 (Dimension) Universal Constants, Variations, and Identities (Dimension) #18 Dimension is a spectrum or domain of awareness: they essentially build an additional point of view or perspective. We live in a universe of potentially infinite dimension. Also, there are more spatial dimensions than three and more temporal dimensions than time (the only one science seems to recognize). Yes, I’m aware of what temporal means; Temporal is a derived attribute of a much more fundamental concept: Change. One important caveat: please bear in mind that my little essay here is not a complete one. The complete version will come when I publish my work. The idea of dimension is not at all well understood. The fact is, science doesn’t really know what dimension is; rather, only how they may be used! Science and technology ‘consume’ their utility without understanding their richness. Otherwise they would have clarified them for us by now. Those who may have clarified what they are get ignored and/or ridiculed, because understanding them requires a larger mental ‘vocabulary’ than Physicalism, Reductionism, and Ontology can provide. Our present science and technology is so entrenched in dogma, collectivism, and special interest, that they no longer function as they once did. The globalist parasites running our science and technology try their best to keep us ‘on the farm’ by restricting dimension, like everything else, to the purely physical. It’s all they can imagine. That’s why many of us feel an irritation without being able to place our finger on it when we get introduced to dimension. We seem to ‘know’ that something just doesn’t ‘rhyme’ with their version. Time and space may be assigned dimensionality, in a purely physical sense if necessary, but there are always underlying entities much deeper in meaning involved that are overlooked and/or remain unknown which provide those properties with their meaning. This is why the more sensitive among us sense something is wrong or that something’s missing. Let us temporarily divorce ourselves from the standard ‘spatial’ and ‘temporal’ kinds of ‚dimension’ for a time and observe dimension in its essence. Definitions are made from them: in fact, dimensions function for definitions just as organs do for the body. In turn, dimension has its own set of ‘organs’ as well! I will talk about those ‘organs’ below. Dimension may appear different to us depending upon our own state of mind, level of development, kind of reasoning we choose, orientation we prefer, expectations we may have,… but down deep… Everything, even attributes of all kinds, involve dimension. We must also not forget partial dimension such as fractals over complex domains and other metaphysical entities like mind and awareness which may or may not occupy dimension. Qualia (water is ‘wet’, angry feels like ‘this’, the burden is ‘heavy’) are also dimensional. Dimensions are ‘compasses’ for navigating conceptual landscapes. We already think in multiple dimension without even being aware of it! Here’s is an example of how that is: [BTW: This is simply an example to show how dimension can be ‘stacked’ or accrued. The items below were chosen arbitrarily and could be replaced by any other aspects.] ♦ Imagine a point in space (we are already at 3d [x,y,z]) – actually at this level there are even more dimensions involved, but I will keep this simple for now. ♦ it moves in space and occupies a specific place in time (now 4d) 3d + 1 time dimension ♦ say it changes colour at any particular time or place (5d) ♦ let it now grow and shrink in diameter (6d) ♦ if it accelerates or slows its movement (7d) ♦ if it is rotating (8d) ♦ if it is broadcasting a frequency (9d) ♦ what if it is aware of other objects or not (10d) ♦ say it is actively seeking contact (connection) with other objects around it (11d) ♦ … (the list may go on and on) As you can see above, dimensions function like aspects to any object of thought. Dimensionality becomes much clearer when we free ourselves from the yoke of all that Physicalism, Reductionism, and Ontology. Let’s now look at some of their ‘organs’ as mentioned above as well as other properties they have in common: They precede all entities except awareness. Awareness congeals into them. They form a first distinction. They have extent. They are integrally distributed. They have an axial component. They spin. They vibrate. They oscillate. They resonate. They may appear as scalar fields. Their references form fibrations. They are ‘aware’ of self/other. Their structural/dynamic/harmonic signature is unique. They provide reference which awareness uses to create perspective meaning. Holons are built from them. http://mathesis-universalis.com Sacred Geometry 29 by Endre @ RedBubble: http://www.redbubble.com/people/endre/works/6920405-sacred-geometry-29?p=poster Sep 7, 2016 | Categories: Constants, Holons, Holors, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Mathematics, Mathesis Generalis, Mathesis Universalis, Meta Logic, Metamathematics, Metaphysics, Perspective, Philosophy, Scalars, Semantics, Understanding, Variations, Wisdom | Tags: BigData, First Distinction, insight, knowledge, Knowledge Representation, learning, Logica Universalis, Mathesis Universalis, Metalogic, Metaphysics, Philosophia Universalis, Scalar Field, Scalars, Scientia Universalis, Semantics, understanding, Universal Constants, Variances, wisdom | Leave a comment Universal Constants, Variations, and Identities – #17 (Representation) #17 Interiority and Exteriority arise together. (Representation) For every interior representation there is always an exterior representation that compliments it. For every exterior representation there is always a corresponding interior one. Sep 6, 2016 | Categories: Constants, Identities, Mathesis Generalis, Mathesis Universalis, Meta Logic, Metamathematics, Semantics, Understanding, Variations, Wisdom | Tags: insight, knowledge, Knowledge Representation, learning, Logica Universalis, Mathesis Universalis, Metalogic, Philosophia Universalis, Philosophy, Scientia Universalis, understanding, Universal Constants, Universalis, Variances | Leave a comment HUD Fly-by Test Link to video. Don’t take this as an actual knowledge representation; rather, simply a simulation of one. I’m working out the colour, transparent/translucent, camera movements, and other technical issues. In any case you may find it interesting. The real representations are coming soon. Aug 21, 2016 | Categories: Big Data, Holons, Holors, Hyperbolic Geometry, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Logic, Long Data, Mathesis Generalis, Mathesis Universalis, Meta Logic, Metamathematics, Metaphysics, Philosophy, Understanding, Wisdom | Tags: BigData, Constants, Hyperbolic Geometry, insight, knowledge, Knowledge Representation, learning, Logica Generalis, Logica Universalis, Mathesis Generalis, Mathesis Universalis, Metalogic, Metamathematics, Metaphysics, Philosophia Generalis, Philosophia Universalis, Philosophy, Philosophy of Language, Philosophy of Learning, Philosopohy of Mind, Scientia Universalis, understanding, Universal Constants, Universalis, wisdom | Leave a comment Obfuscation In A ‘Nut’ Shell Obfuscation In A ‘Nut’ Shell Distinctions that are no differences, are incomplete, or are in discord. In knowledge representation these ‘impurities’ (artificiality) and their influence are made easy to see.   In groks you will see them as obfuscation fields. That means darkening and/or inversion dynamics. The term refers to the visual representation of an obfuscated field, and can also be represented as dark and/or inverted movements of a field or group. I concentrate more on the dark versions here and will consider the inversions (examples of lying) in a future post. They bring dynamics that are manipulative, artificial, or non-relevant into the knowledge representation. Their dynamic signatures make them stand out out like a sore thumb. Cymatic images reveal these dynamics too. There are multiple vortexes, each with their own semantic contribution to the overall meaning to a knowledge molecule or group. Here is an example of a snow flake (seen below) https://www.flickr.com/photos/13084997@N03/12642300973/in/album-72157625678493236/ From Linden Gledhill. Note that not all vortexes are continuous through the ‘bodies’ of the molecules they participate in. Also, in order to correctly visualize what I’m saying, one must realize that the cymatic images are split expressions. That means to see the relationship, you must add the missing elements which are hinted at by the image. Every cymatic image is a cut through the dynamics it represents. We are in effect seeing portions of something whole. Whole parts are dissected necessarily, because the surface of expression is limited to a ‘slice’ through the complete molecule. (Only the two images marked ‘heurist.com’ are my own! The other images are only meant as approximations to aid in the understanding of my work.) Apr 28, 2016 | Categories: Big Data, BigData, Holons, Holors, Insight, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Mathematics, Mathesis Generalis, Mathesis Universalis, Metamathematics, Semantics, Wisdom | Tags: insight, knowledge, learning, Logica Universalis, Mathesis Universalis, Philosophia Universalis, understanding, wisdom | Leave a comment Men And Their Semantics – Turning Meaning into Legos Semantically speaking: Does meaning structure unite languages? This work is a dead end waiting to happen. Of course it will attract much interest, money, and perhaps even yield new insights into the commonality of language, but there’s better ways to get there. What’s even more sad is that they, who should know better, will see my intentions in making this clear as destructive criticism instead of a siren warning regarding research governed/originating through a false paradigm. These people cannot see or overlook the costs humanity pays for the misunderstandings research like this causes and is based upon. It’s even worse in the field of genetic engineering with their chimera research. The people wasting public money funding this research need to be gotten under control again. I don’t want to criticize the researcher’s intentions. It’s their framing and methodology that I see as primitive, naive, and incomplete. I’m not judging who they are nor their ends; rather, their means of getting there. “Quantification” is exactly the wrong way to ‘measure/compare semantics; not to mention “partitioning” them! 1) The value in this investigation that they propose is to extrapolate and interpolate ontology. Semantics are more than ontology. They possess a complete metaphysics which includes their epistemology. 2) You cannot quantify qualities, because you reduce the investigation to measurement; which itself imposes meaning upon the meaning you wish to measure. Semantics, in their true form, are relations and are non-physical and non-reducible. 3) Notice also, partitioning is imposed upon the semantics (to make them ‘measurable/comparable’). If you compare semantics in such a way then you only get answers in terms of your investigation/ontology. 4) The better way is to leave the semantics as they are! Don’t classify them! Learn how they are related. Then you will know how they are compared. There’s more to say, but I think you get the idea… ask me if you want clarification… Feb 5, 2016 | Categories: Artificial Intelligence, Bad Logic, Bad Science, Big Data, Consciousness, Education, Humanity, Insight, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Logic, Mathesis Generalis, Mathesis Universalis, Philosophy, Psyence, Semantics, Understanding, Wisdom | Tags: BadScience, insight, knowledge, learning, Mathesis Universalis, understanding, wisdom | Leave a comment Typical Knowledge Acquisitions Node Knowledge Representation A typical knowledge acquisition node showing two layers of abstraction. Note how some of the acquisition field detection moves with the observer’s perspective. You can tell, due to the varying visual aspects of the fields and their conjunctions that it has already been primed and in use. This node may be one of thousands/millions/billions which form when acquiring the semantics of any particular signal set. Their purpose is to encode a waveform of meaning. Basically it is these ‘guys’ which do the work of ‘digesting’ the knowledge contained within any given signal; sort of like what enzymes do in our cells. The size, colour (although not here represented), orientation, quantity, sequence, and other attributes of the constituent field representations all contribute to a unique representation of those semantics the given node has encountered along its travel through any particular set of signal. The knowledge representation (not seen here) is comprised of the results of what these nodes do. This node represents a unique cumulative ‘imprint’ or signature derived from the group of knowledge molecules it has processed during its life time in the collation similar to what a checksum does in a more or less primitive fashion for numerical values in IT applications. I have randomized/obfuscated a bit here (in a few different ways), as usual, so that I can protect my work and release it in a prescribed and measured way over time. In April I will be entering the 7th year of working on this phase of my work. I didn’t intentionally plan it this way, but the number 7 does seem to be a ‘number of completion’ for me as well. The shape of the model was not intended in itself. It ‘acquired’ this shape during the course of its work. It could have just as well been of a different type (which I’m going to show here soon). Important is the ‘complementarity’ of the two shapes as they are capable of encoding differing levels of abstraction. The inner model is more influenced by the observer than the outer one, for example. The outer shape contains a sort of ‘summary’ of what the inner shape has processed. Jan 4, 2016 | Categories: Big Data, BigData, Consciousness, Fields, Holons, Holors, Knowledge, Knowledge Representation, Language, Learning, Linguistics, Mathesis Universalis, Semantics, Wisdom | Tags: insight, knowledge, learning, Mathesis Universalis, Metaphysics, understanding, wisdom | Leave a comment Really! Nothing Is ‘Real’ Another example of the ‘neo-snake-oil salesmen’ peddling you trendy pabulum and neo-Babylon confusion. My current project Mathesis Universalis http://mathesis-universalis.com will bring an end to this menagerie of nonsense and subtle programming. I could write a book on this. Don’t believe everything put forward in this… set of perspectives. This is a work in process so stay tuned… updates are coming very shortly. I’m happy that he allows for more than 5 senses as this is a common error made by science and philosophy up to this time. I’ve taken issue with it elsewhere numerous times. Also I’m pleased that he is allowing for Neuroplasticity (Dr. Jeffrey M. Schwartz http://www.jeffreymschwartz.com/ has been leading this new model for over 10 years.) Up to @04:27 I take issue with two important assumptions he makes: 1) That sensory information is the only way we ‘register’ reality. 2) He is a physicalist pure through. If he can’t measure and quantify it, then it doesn’t exist for him… This leads to what is known as causal ambiguity (among other things). http://psychologydictionary.org/causal-ambiguity/ @04:57– He says that memory is stored all over the brain. This is incorrect. The effects of the phenomena of memory are manifested in various areas of the brain. There is no sufficient and necessary proof that memory is stored there! They PRESUME it to be stored there, because they can not allow or imagine anything non-physical being able to store any kind of knowledge. @05:09– “How many memories can you fit inside your head? What is the storage capacity of the human brain?” he asks. In addition to the presumption that memories are stored there, he then ignores the capacity of other areas of the body to imprint the effects of memory: the digestive tract, the endocrine and immune ‘systems’,… even to cell membranes (in cases of addiction, for example)!!! @05:23– “But given the amount of neurons in the human brain involved with memory…” (the first presumption that memories are stored there) “and the number of connections a single neuron can make…” (he’s turning this whole perspective on memory into a numerical problem!) which is reductionism. @05:27– He then refers to the work of Paul Reber, professor of psychology at Northwestern University who explained his ‘research’ into answering that question. here’s the link. I will break that further stream of presumptions down next. http://www.scientificamerican.com/article/what-is-the-memory-capacity/ (the question is asked about middle of the 1st page of the article which contains 2 pages) Paul Reber makes a joke and then says: “The human brain consists of about one billion neurons. Each neuron forms about 1,000 connections to other neurons, amounting to more than a trillion connections. If each neuron could only help store a single memory, running out of space would be a problem. You might have only a few gigabytes of storage space, similar to the space in an iPod or a USB flash drive.” “Yet neurons combine so that each one helps with many memories at a time, exponentially increasing the brain’s memory storage capacity to something closer to around 2.5 petabytes (or a million gigabytes). For comparison, if your brain worked like a digital video recorder in a television, 2.5 petabytes would be enough to hold three million hours of TV shows. You would have to leave the TV running continuously for more than 300 years to use up all that storage.” These presumptions and observations are full of ambiguity and guesswork. Given that we are not reading a thesis on the subject, we can allow him a little slack, but even the conclusions he has arrived at are nothing substantial. More below as he reveals his lack of knowledge next. “The brain’s exact storage capacity for memories is difficult to calculate. First, we do not know how to measure the size of a memory. Second, certain memories involve more details and thus take up more space; other memories are forgotten and thus free up space. Additionally, some information is just not worth remembering in the first place.” He not only doesn’t know to measure memories (which he admits), he cannot even tell you what they are precisely! He offers here also no reason for us to believe that memory is reducible to information! @05:50– “The world is real… right?” (I almost don’t want to know what’s coming next!) And then it really gets wild… @05:59– With his: “How do you know?” question he begins to question the existence of rocket scientists. He moves to Sun centric ideas (we’ve heard this one before) to show how wrong humanity has been in the past. He seems to ignore or not be aware of the fact that that many pre-science explorers as far back as ancient Alexandria knew better and had documented this idea as being false. This ‘error’ of humanity reveals more about dogma of a church/religion/tradition than of humanity/reality as it truly is. @06:29– “Do we… or will we ever know true reality?” is for him the next question to ask and then offers us to accept the possibility that we may only know what is approximately true. @06:37 “Discovering more and more useful theories every day,  but never actually reaching true objective actual reality.” This question is based upon so much imprecision, ignorance, and arrogance that it isn’t even useful! First of all: we cannot know “true objective actual reality” in all of its ‘essence’, because we must form a perspective around that which we observe in order to ‘see’ anything meaningful. As soon as a perspective comes into ‘being’, we lose objectivity. (ignorance, assumption) He doesn’t define what ‘reality’ for him is. (imprecision) He doesn’t explain what the difference between ‘true’ and ‘actual’ might be. (imprecision, assumption) Theories are NOT discovered, rather created (implicit arrogance). They can only be discovered if they were already known/formulated at some time. Also; theories do not stand on their own; rather, they depend upon continued affirmation by being questioned for as long as they exist. We DO NOT store knowledge in our answers; rather, in our questions. [continued…] Oct 6, 2015 | Categories: Mathesis Universalis, Social Engineering | Tags: Confusion, insight, knowledge, learning, Materialism, Mathesis Generalis, Mathesis Universalis, Neo Babylon, Physicalism, Psyence, Reductionism, social engineering, Sophistry, Techno Babble, trendy, understanding, wisdom | 3 Comments A Holon’s Topology, Morphology, and Dynamics (2a) A Holon’s Topology, Morphology, and Dynamics (2a) This is the second video of a large series and the very first video in a mini-series about holons. In this series I will be building the vocabulary of holons which in turn will be used in my knowledge representations. The video following this one will go into greater detail describing what you see here and will be adding more to the vocabulary. This is the second video of a large series and the very first video in a mini-series about holons. In this series I will be building the vocabulary of holons which in turn will be used in my knowledge representations. Aug 31, 2015 | Categories: Knowledge Representation, Mathesis Universalis | Tags: BigData, Holons, knowledge, Knowledge Representation, learning, Mathesis Generalis, Mathesis Universalis | Leave a comment Ontology: Compelling and ‘Rich’ Ontologies are surfaces… even if ‘rich’. (link) Ontology: Compelling and ‘Rich’ They are only surfaces, but they seem to provide you with depth. This exquisite video shows how the representation of knowledge is ripe for a revolution. I’ve written about this in depth in other places so I won’t bore you with the details here unless you ask me in the comments below. Stay tuned! I’m behind in my schedule (work load), but I’m getting very close just the same. I will publish here and elsewhere. I’m going to use this video (and others like it) to explain why ontologies are not sufficient to represent knowledge. Soon everyone will acknowledge this fact and claim they’ve been saying it all along! (In spite of the many thousands of papers and books obsessively claiming the opposite!!!) They do not know that how dangerous that claim is going to be. Our future will be equipped with the ability to determine if such claims are true or not. That’s some of the reason I do what I do. #KnowledgeRepresentation #BigData #Semantics #Metaphysics   #Ontology #Knowledge #Wisdom #Understanding #Insight #Learning #MathesisUniversalis #MathesisGeneralis #PhilosophiaUniversalis #PhilosophiaGeneralis #ScientiaUniversalis #ScientiaGeneralis Aug 6, 2015 | Categories: Big Data, Knowledge Representation, Semantics | Tags: BigData, insight, knowledge, Knowledge Representation, learning, Mathesis Generalis, Mathesis Universalis, Metaphysics, Philosophia Generalis, Philosophia Universalis, Scientia Generalis, Scientia Universalis, Semantics, understanding, wisdom | Leave a comment Nascent Mind, Prescient Knowledge: Instinct And Envisioning It’s at this juncture that concepts begin to coalesce. Within this ‘Holy of Holies’ concepts are born and form/generate their associated continuums. It’s like watching the blue wisping stars newly born in the constellation of Pleiades. https://en.wikipedia.org/wiki/Pleiades This ‘event horizon’ is so crucial to understanding and participating in mind; yet those who should know better simply ignore or overlook it. Tesla’s statement here rings so true that it simply boggles my mind and confirms that Tesla was ‘tuned into it.’ He clearly exhibited these awarenesses on several occasions. He was able to envision many ideas to their completion before constructing them;  and his instinct for somehow ‘knowing’ (flashes of insight) what to do next and where to go with an idea were so profound that it often overwhelmed and incapacitated him. His mind was so fertile that layers of creative impulses were being maintained concurrently. Next to Socrates there are very few who inspire me. Tesla is one of those few. Jun 26, 2015 | Categories: Tesla | Tags: Awareness, Cognition, insight, knowledge, learning, Logica Generalis, Logica Universalis, Mathesis Generalis, Mathesis Universalis, Meta-Cognition, Philosophia Generalis, Philosophia Universalis, Scientia Generalis, Scientia Universalis, understanding, wisdom | Leave a comment Precursors Of Knowledge Precursors Of Knowledge Fractal fields provide a nice framework in which to think about knowledge. They are not all we need for precision, but they are helpful in a generic way. I’ll be posting more on them as the knowledge representations are published, because there are many ‘gaps to fill’ to show how these relate to knowledge. More sources: https://www.youtube.com/watch?v=2nTLI89vdzg https://www.youtube.com/watch?v=1ZVNIZGw4X0 https://www.youtube.com/watch?v=Yp4ogF2w13M https://www.youtube.com/watch?v=8UPD2_gEjvM https://www.youtube.com/watch?v=ArZLXHVVV5I May 29, 2015 | Categories: Fields, Fractals, Mathesis Generalis, Mathesis Universalis | Tags: BigData, Fields, Fractal Fields, insight, knowledge, Knowledge Representation, Language, learning, Mathesis Generalis, Mathesis Universalis, PhilosophyOfMind, understanding, wisdom | Leave a comment Information Visualization Is Not Knowledge Representation (Lynda.com – Overview of Data Visualization) Information Visualization Is Not Knowledge Representation This great video from Lynda.com shows how the processing language/interpreter is great for modeling information. With such a multitude of interesting ways to model data, we find it hard to resist the temptation to call this knowledge, but it’s not! All of the wonderful representations here still require us to interpret their meaning! What if there were a way to present knowledge in which our own understanding is not required to interpret them? What if our understanding of what we have presented to us becomes part of the presentation itself, and in fact, influences what we take from that representation? We obviously need knowledge representation that can provide their meaning on their own for only they can provide a true understanding of their inherent structure and dynamics. You see real understanding is the personalization of knowledge into your own mind. If your mind cannot dialog with that knowledge, it’s not really yours and if your mind does all the work, it’s only information. May 5, 2015 | Categories: Mathesis Universalis | Tags: #Foundations, insight, knowledge, Knowledge Representation, learning, Logica Generalis, Logica Universalis, Mathesis Generalis, Mathesis Universalis, Philophia Universalis, Philosophia Generalis, Philosophy of Learning, PhilosophyOfLanguage, PhilosophyOfMind, Scientia Generalis, Scientia Universalis, understanding, wisdom | Leave a comment Universal Constants, Variations and Identities – #16 (Creation/Discovery) Universal Constants, Variations and Identities #16 Creation and discovery compliment each other and are the means in which the Universe fundamentally unfolds and enfolds itself (Creation/Discovery) We tend not to identify them, because there are so many variations in their harmony. Please do overestimate your thoughts… as you will see they are the beginning of your expression to and of the world. Both Creation and Discovery will work in unison, if we allow them. Discovery is to recognize/relate what is in your world. Creation is to transform/synthesize it too. Each is alone without the other. Creation=Right ‘brain’ (right+mind) Discovery=Left ‘brain’ (left+mind) Their ‘magick’ (sic.) manifests not when you synchronize them; rather, when you harmonize them. (Please take the time to watch the 4 minute video.) Feb 24, 2015 | Categories: Constants, Insight, Knowledge, Learning, Understanding, Wisdom | Tags: change, Creation, Identities, insight, knowledge, learning, Logica Universalis, Mathesis Universalis, Metalogic, Metamathematics, Metaphysics, Metascience, Philosophia Universalis, Philosophy, Scientia Universalis, understanding, Universal Constants, Universalis, Variances, wisdom | Leave a comment Universal Constants, Variations and Identities – #15 (Change/Time) #15 Time is a temporally ‘linear’ (directed) form of change that is not limited by dimension. (Change/Time) Time has been arbitrarily and wrongly assigned to dimension. Change is not restricted to any dimension: therefore time is also not limited to it. I know it’s trendy to see time as a dimension, but dimension is something completely different. Stay tuned to find out what and why. Update: There are many reasons why time needs a proper definition. Here are a few of them: The chemical reactions in the vessel are not really effected by some mysterious thing called time, but by the number of contacts or collisions that take place in the soup of atoms or molecules. That is what the factor ‘T’ really stands for. 1) Eternity may be a somewhat mystical overarching reality outside of the physical universe, but time is not. Nor is time a thing that anybody can do anything to. In other words: it cannot be reified. 2) The universe doesn’t exist in time, but time exists in the universe. 3) The proper definition of time is exactly:  the sequence of events in the material universe. Feb 7, 2015 | Categories: Constants, Insight, Knowledge, Learning, Understanding, Wisdom | Tags: change, insight, knowledge, learning, linear, Logica Universalis, Mathesis Universalis, Metalogic, Metamathematics, Metaphysics, Metascience, Philosophia Universalis, Philosophy, Scientia Universalis, temporal, understanding, Universal Constants, Universalis, Variances, wisdom | Leave a comment Universal Constants, Variations and Identities – #14 (Singular/Plural) Universal Constants, Variations and Identities #14 Singular and plural arise together. (Singular/Plural) There is no singular without a plural representation except in the non-dual. See http://mathesis-universalis.com for more information. #Knowledge #Wisdom #Understanding #Learning #Insight #Constants #Variances #Philosophy #MathesisUniversalis #ScientiaUniversalis #PhilosophicaUniversalis #LogicaUniversalis #MetaMathematics #MetaLogic #MetaScience #MetaPhysics #MetaPhilosophy #Singular #Plural Feb 3, 2015 | Categories: Constants, Identities, Insight, Knowledge, Learning, Mathesis Universalis, Metamathematics, Metaphysics, Philosophy, Wisdom | Tags: Constants, insight, knowledge, learning, Logica Universalis, Mathesis Universalis, Metalogic, MetaPhilosophy, Metaphysics, Metascience, Philosophia Universalis, Philosophy, Plural, representation, Scientia Universalis, Singular, Singular and plural, understanding, Universal Constants, Variances, wisdom | Leave a comment « Older Entries 
 
 
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