This collection of books is a small, but growing example of the millions of books, journals, periodicals, and academic papers we are currently tracking and indexing. We are updating this library constantly. Please return often and review this library as it evolves.
This library is the first step on our way to making Mathesis Universalis (the long-sought search for a unifying principle in all that we know and experience) a reality. Soon our knowledge representations, in their many forms, will be accessible from the pop-up dialogues which appear when you click/tap on a book’s entry in the overview you see. Other types of knowledge sources; such as social media activity, websites, E-Mails, audio, video,… are also going to be included in our tracking and indexing system.
I, Carey G. Butler, have been working on this idea since 1989 during my study of Foundational Mathematics and Complex Analysis. I then moved to Germany in 1990 to continue my study (this time in the original German language) of many German mathematicians and philosophers such as Carl Friedrich Gauss, Bernhard Riemann, Gottfried Wilhelm Leibniz,… During that first year I began to formalise the idea as I began to learn the German language more intensively.
The journey has been a long one and was finally conceptually refined in March of 2009. The journey has taken many, many turns in the years since. I have made several key discoveries in mathematics, philosophy, and linguistics along the way which I, due to my concerns about priority, have not yet published. A few of these discoveries are documented elsewhere though, but I have been very careful to withhold many aspects of their details until I was able to find and/or adapt current technologies to bring them to a useful expression and application in their fullness. I was confronted with many obstacles and challenges, but I never gave up. For more information about my plans, please visit our website at Mathesis Universalis in English or Mathesis Universalis auf Deutsch.
As it stands, we could have created this library application a year ago. It is, in itself, nothing very special for programmers who know how to build applications like it. However, as we developed and tested the predecessor to this application, it soon became very clear that the sheer volume of data being manipulated was creating increasing demands on the conventional technology we were using at the time. Our concerns about processing time, network speed, and infrastructural demands forced us to step back and create a better foundation which could be scaled to any degree. We have spent the last 8 months (August 2021 – April 2022) building a ‘symphony’ of cloud applications and an infrastructure which is now fast, reliable, and scalable.
Towards that aim, this library represents the ‘orchestration’ of a collection of cloud apps we created or have forked and modified for our purposes that is distributed over several servers. Its backend is primarily driven by a distributed Couchbase database to store and to manipulate the massive amount of data. Also other kinds of databases are implemented for temporary storage or for the frontend’s presentation and housekeeping.
We are currently developing a Progressive Web App which will use this library as one of its sources to present our knowledge representation.
Finally, after 13 years of investment of all kinds and, on the 8th birthday of one of my most important discoveries (‘We Have a Heartbeat‘),…
Often they do it, because those who destroy others’ lives are themselves miserable or have destroyed their own lives.
Another reason is to advance objectives that are held by the person or held by the people the person works for. Alphabet agencies like CIA, NSA, NSC, BND, MOSSAD, UNO,… there are even documented examples of Microsoft, Apple, Google, Twitter, and Facebook having exhibited this behaviour.
They usually harbour some form of disdain for others or humanity as a whole. Or they are incapable of human properties like empathy (pathology of some kind).
Humanity is comprised of many spectra; those of ideologies, values, goals, methods, knowledge, power,… These spectra, when placed upon their side like a sine wave (which is actually a spiral), look like Bell curves of some type. There are many variants of these curves.
Note how each Bell curve exhibits specific properties. Among those properties are the distribution of an inherent ‘population’. The population of the curve could be anything, not just people. They also have outliers. Those of the population which exist on the extreme left or right of the curve.
If we had a particular set of properties to examine, we may place the distribution of this property into one or more of these curves. Let’s take banksters, who can be, and usually are very destructive.
We would have at least 5 curves to describe their population.
Intelligence: where they usually (always exceptions to outliers) occupy the upper portion of the curve (where it gets real small).
Empathy: where they usually occupy the extreme lower part of the spectrum.
Control fetish: where they are usually found in the middle of the spectrum.
Hoarding: again in the centre.
You could continue in this vein to describe them so uniquely, that even language can’t keep up with its ‘granularity’ (increasing specificity). Things like available resources, socialising debt, privatising profit, corruption, warmongering, demographic changes, jail time, manipulative tendency, fear,…
That is where language is then transformed into knowledge.
As you see, people who destroy other’s lives can easily be found using this method.
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.
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 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.
Words are symbolic indications and/or conveyors of meaning and are not that meaning in themselves.
Meaning is found, stored, and manipulated in our minds. This is why different languages are capable, in varying degrees of usefulness, to convey meaning which is very similar to that found via the symbols of any other.
It It is also the reason why there are words indicating meaning that are not found in other languages; or, if found in a different language, the other language requires more of its own structure, dynamics, and resonance to convey the same meaning.
For example: the words ‘déjà vu’ in French are found in German ‘schon gesehen’ and in English ‘already seen’, but these phrases do not convey the full meaning found in the French version. To counter this deficit, their meaning in other languages must be ‘constructed’ out of or ‘fortified’ by the careful use of longer strings of symbols. This additional construction and/or fortification may even fail at times. This is often where the word phrase from a different language is simply added to the language in which the concept is missing.
This same situation is found in the literature of many languages. The words used to convey meaning are condensed and may contain more meaning than is usually the case. In this regard, even the person reading/hearing the words may not possess the competence necessary to catch this condensed meaning in its fullness.
Mathematical expressions, albeit more precise, are also indications of meaning. They are more robust in their formulation, but at ever-increasing depth or scope, even they may fail to reliably or conveniently convey meaning.
Our understanding of what words mean is not always accurate, but where our mutual understanding of the meaning of words overlaps, and the degree to which they overlap, is where their meaning can be shared.
Our own personal understanding of words is measured by our ability to apply their meaning in our lives.
There is also a false meme, which I would like to clarify.
“Knowledge is Power!”
It is wrongly said that ‘Knowledge is power’. The truth is another: Knowledge is the measure of usefulness of what we understand and is the only true expression of its ‘power’.
The value of Knowledge is found in its usefulness and not in its possession.
Yes, in knowledge representation, the answer is the interior of a holon.
Ontologies go ‘out of scope’ when entering interiority. The common ontological representation via mathematical expression is 1/0.
When we ‘leave’ the exterior ontology of current mathematics by replacing number with relation, we enter the realm of interiority.
In the interior of relation, we access the epistemological aspects of any relation.
As an aide to understanding – Ontology answers questions like: ‘What?’, ‘Who?’, ‘Where?’, and ‘When?’. Epistemology answers questions like: ‘Why?’ and ‘How do we know?’
In vortex mathematics 1/0 is known as ‘entering the vortex’.
There are other connections to some new developments in mathematics involving what is called ‘inversive geometry’.
Example: (oversimplified for clarity)
If we think of say… the point [x, y, z] in space, we may assign x, y, and z any number value except where one of these coordinates gets involved in division where 0 is not allowed (up to this point in common mathematics) as a denominator. x/z is not allowed when z=0, for example.
Now, if we are dealing with interiority, numbers are replaced by relationships, such as [father, loves, son].
What if the son has died? Is the relationship still valid?
The answer to this question lies within the interior of those involved in the relation.
They are wonderful tools to explain much of our world, but lack ‘The Right Stuff’ to handle the metaphysical underpinnings of anything near a Philosophy of Mind, Philosophy of Language , or a Philosophy of Learning.
This is, because Category Theory specialises on roughly half of the Noosphere. It does a wonderful job on exteriority, but cannot sufficiently describe nor comprehensively access interiority.
Therefore, as is the case with Semiotics, has limited metaphysical value with respect to philosophy in general.
For example:philosophies of mind, language, or learning are not possible using only category theoretical tools and/or semiotics.
4.4.2 Knowledge is the Terminal Object of Visualisation states:
“The ultimate purpose of the visualisation process is to gain Knowledge of the original System. When this succeeds (when the diagram commutes) then the result is a ‘truth’ relationship between the Knowledge and the System. When this process breaks down and we fail to deduce correct conclusions then the diagram does not commute.”
I want to also comment on Figure 3 (which also exposes missing or false premises in the paper), but I will wait until I have discussed the assertions in the quote above which the authors of this paper reference, accept, and wish to justify/confirm.
1) The purpose of a representation is NOT to gain knowledge; rather, to express knowledge. Also, truth has nothing to do with knowledge except when that value is imposed upon it for some purpose. Truth value is a value that knowledge may or not ‘attend’ (participate in).
1a) The ‘truth value’ of the System (‘system’ is a false paradigm [later, perhaps] and a term that I also vehemently disagree with) does not always enter into the ‘dialogue’ between any knowledge that is represented and the observer interpreting that knowledge.
2) The interpretation of a representation is not to “deduce correct conclusions”; rather, to understand the meaning (semantics and epistemology) of what is represented. ‘Correct’ understanding is not exclusive to understanding nor is it necessary or sufficient for understanding a representation, because that understanding finds expression in the observer.
2a) ‘Correct’, as used in this paragraph, is coming from the outside (via the choice of which data [see Fig. 3] is represented to the observer) and may have no correspondence (hence may never ever commute) whatever to what that term means for the observer.
The authors are only talking about ontologies. That is a contrived and provincial look at the subject they are supposing to examine.
There may (and usually are) artefacts inherent in any collection and collation of data. The observer is forced to make ‘right’ (‘correct’) conclusions from that data which those who collected it have ‘seeded’ (tainted) with their own volition.
‘System’ (systematising) anything is Reductionism. This disqualifies the procedure at its outset.
They are proving essentially that manipulation leads to a ‘correct’ (their chosen version) representation of a ‘truth’ value.
I could tie my shoelaces into some kind of knot and think it were a ‘correct’ way to do so if the arrows indicate this. This is why paying too much attention to a navigation system can have one finding themselves at the bottom of a river!
The paper contains assumptions that are overlooked and terms that are never adequately defined! How can you name variables without defining their meaning? They then serve no purpose and must be removed from domain of discourse.
Categorical structures are highly portable, but they can describe/express only part of what is there. There are structure, dynamics, and resonance that ontology and functionalism completely turns a blind eye to.
The qualities of Truth, Goodness, Beauty, Clarity,… (even Falsehood, Badness, Ugliness, Obscurity,…) can be defined and identified within a knowledge representation if the representation is not restricted to ontology alone.
In order to express these qualities in semiotics and category theory, they must first be ontologised funtionally (reduced). Trying to grasp them with tools restricted to semiotics and category theory is like grasping into thin air.
That is actually the point I’m trying to make. Category Theory, and even Semiotics, each have their utility, but they are no match for the challenge of a complete representation of knowledge.
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 taughtthat 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
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.
Answer: Philosophy is more fundamental than mathematics.
This is changing, but mathematics is incapable at this time of comprehensively describing epistemology, whereas, philosophy can.
Hence; mathematics is restrained to pure ontology. It does not reach far enough into the universe to distinguish anything other than ontologies. This will change soon. I am working on exactly this problem. See http://mathematica-universalis.com for more information on my work. (I’m not selling anything on this site.)
Also, mathematics cannot be done without expressing some kind of philosophy to underlie any axioms which it needs to function.
Implication is a ‘given’ in mathematics. It assumes a relation which we call implication. Mathematics certainly ‘consumes’ them as a means to create inferences, but the inference form, the antecedent, and the consequent are implicit axioms based upon an underlying metaphysics.
Ergo: philosophy is more general and universal than mathematics.
Often epistemology is considered separate from metaphysics, but that is incorrect, because you cannot answer questions as to ‘How do we know?” without an underlying metaphysical framework within which such a question and answer can be considered.
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 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.
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.
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.
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.)
The Creation of ‘Care’
The 8th Principle of Natural Law: Care
The ‘container’ in which all of the principles of natural law exist. What we care about on a daily basis acts as the driving force of our thoughts and actions.
Care+Knowledge+Action (Feeling, Mind, Being)
This is the reason my mother named me ‘Care-y’. She told me as a child when I asked her why she named me Carey that I would be the one who cares.
The parasitic pre-mature globalists want us to forget and/or abandon our heritage. They have limited talents and can only ‘create’ by destroying. They must force us into artificial diversity instead of allow us to naturally form a global civilisation.
They tell themselves they are special,but they want us to ignore the fraud, cronyism, deception, obfuscation, division, Cultural Marxism, social engineering, propaganda, murder, coercion, war, poisoning,… they have used to usurp the positions they have attained and given each other.
They are a blight upon humanity which has infected every single human endeavour known to man including science, mathematics, philosophy, education, and technology.
We would be living in the clouds and at night be looking into the sky to witness the construction of planetary ships and space stations being being built to take us to unknown vistas if it weren’t for their ‘hidden hand’ blocking, diverting, and subverting of humanity’s evolution through the centuries.
We MUST NOT let this happen any more. ‘The sleeper must awaken!’
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…
‘Trust’ For Sale
More of Google’s attempt to become the ‘clearing house’ of truthful, ‘trustful’, and important facts and therewith create a ‘truthful tribe’. I thought we wanted to rid ourselves of tribalism?
So many talented people will never be known, because they work ‘under the radar’ or for being ignored (exiled) as ‘heretics’.
Here is a question: how can even truth, not to mention trust, be systematized when we cannot know all of it as well as its many sources of origination?
Google is creating its own demise with this. It will go down or cause a vast migration of awakened (and non-evangelists) to move to, create, or participate in other search engines.
True research must make it’s own decisions upon what is truthful, trustworthy, and valuable. If we allow a corporation to manage these values, we will enter an age of ‘privatized credibility’.
They will be able to keep people out of the debate (social discourse) by making them non-authoritative. If they can establish metrics then everyone must conform to them.
It’s like believing Marx, Engels, and Lenin were philosophers when they were really children playing with snake-oil in order to sell the idea that a tyranny of Communism was the solution to humanity’s problems.
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.
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.
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.
“This map was constructed by sorting roughly 800,000 published papers into 776 different scientific paradigms (shown as pale circular nodes) based on how often the papers were cited together by authors of other papers.”
“Links (curved black lines) were made between the paradigms that shared papers, then treated as rubber bands, holding similar paradigms nearer one another when a physical simulation forced every paradigm to repel every other; thus the layout derives directly from the data.”
“Larger paradigms have more papers; node proximity and darker links indicate how many papers are shared between two paradigms. Flowing labels list common words unique to each paradigm, large labels general areas of scientific inquiry.”
Manuel DeLanda. 2015. Philosophical Chemistry: Genealogy of a Scientific Field. Bloomsbury “There is no such thing as Science. The word ‘Science’ refers to a reified generality that together with others, like Nature and Culture, has been a constant source of false problems: are controversies in Science decided by Nature or Culture?”
“Avoiding badly posed problems requires that we replace Science with a population of individual scientific fields, each with it own concepts, statements, significant problems, taxonomic ad explanatory schemas. There are, of course, interactions between fields, and exchanges of cognitive content between them, but that does not mean that they can be fused into a totality in which everything is inextricably related. There is not even a discernible convergence towards a grand synthesis to give us hope that even if the population of fields is highly heterogeneous today, it will one day converge into a unified field. On the contrary, the historical record shows a population progressively differentiating into many subfields, by specialization or hybridization, yielding an overall divergent movement.”