Wednesday 19 July 2017

Is structure fossilised sense?



In this essay I will compare the way experience is stored in structures with concepts from mathematical category theory. I will try to show that it is not unlikely that the involution of sensorial experience finds its expression in an observed evolution of biological species and behaves like a mapping process known in mathematical category theory as "Yoneda embedding". I will also argue that there is a primacy of sentience over matter, leading to an idealistic hypothesis of existence.
Warning/disclaimer: This essay is highly speculative and may rest on wrong interpretations. If you are not interested in metaphysics don't bother to read further or to reply.

Background


What is reality? Are the objects, entities and processes we observe with our senses really there? Or is what we observe a mind-fabricated hallucination? It is the ruling paradigm in science that our senses and brains filter the information we receive as an input and then fabricate a kind of simplified representation thereof, which we usually call "reality". But does the information we receive really correspond to anything out there? In the film "The Matrix" (1999), the main character Neo found out that everything he experienced before taking the red pill was not really there in a three dimensional tangible world, but rather a mental illusion fed to his brain by a vast computer system called the matrix to which he was connected in a kind of hibernation vessel. In other words, everything he experienced up till that moment was an illusion produced in the theatre of his brain by interplay of computer and brain information exchange.

This idea has also historical antecedents. Plato's cave with shadows that were taken for real and the notion of Maya in Hinduism and Buddhism. Modern developments in physics -in particular digital physics- invoking the so-called holographic principle have postulated the possibility that we are living in some sort of hologram, possibly projected from the two-dimensional surface of a black hole. Others even go as far as to speculate that we are living in a computer simulation. Perhaps not entirely like in the movie the Matrix, but the analogy is troubling.

Whatever is the higher truth as regards these ideas, at least we can make sense from what we observe. We can distinguish recurrent patterns and use them to our advantage. Technology is a proof, that however limited our understanding might be, at least we can employ this understanding in a predictable manner.

We may never know what reality really is like, but at least we can get an idea of what it is doing. The reproducibility of our knowledge suggests that what we observe is a meaningful and useful representation of the inner workings of reality. Perhaps even an isomorphous representation.

In mathematical category theory, if a category is like another category, there is a mapping between the two categories; a meaningful mapping that preserves the structure of the category when mapping it to another category. Such special structure-preserving mappings are called "functors".
The mappings from A to B can also be considered as the way A relates to B. The relation between A and B could then be considered as the sum of the maps from A to B and the maps from B to A. According to the philosopher Wittgenstein there are no things or objects in reality but only relations. It is the interplay between these relations which create the illusion of localised objects, where there are none. In fact quantum mechanics shows that everything is in fact a giant interference pattern of vibrations and vibrations are essentially non-local. Moreover everything is in a constant state of flux; there is no phenomenon that is exactly identical between two moments. Or as the Greek philosopher Heraclitus said: Panta rhei, ouden menei: Everything flows, nothing remains and "no man ever steps in the same river twice".

How relations build structure

Relations at their most fundamental level can then only be a functional process of mutual information exchange, which is continuously updated. The relations are expressed as vibrations, which result in resonance patterns of standing waves: There is a continuous waving and vibrating taking place, but what we observe is a form with a kind of stability.
In other words if we were to consider the forth- and back going vibrations between two points A and B as a mapping activity in progress, this mapping activity results in a physical (re)presentation of another dimension, which we call the standing wave and which we experience as an almost static thing.
In category theory we call mappings morphisms. Mappings show the maps between "objects" (characters, strings, mathematical objects, sets etc.).
A special functor (a mapping between categories) in category theory is the Yoneda functor. Whereas functors normally map objects, the Yoneda functor takes morphisms (mappings) themselves as objects and maps these into a set, which is a new object. (A map of maps so to say).
The analogy struck me. I wondered whether if relations are sets of mappings and such a set can be considered an object, there is at least an artistic similarity with my standing wave idea. I'd perhaps even go so far as to formulate the hypothesis that the structure of an object is a faithful (not in mathematical sense) representation of the functional relations from which it is built.
Perhaps this example is a bit far-fetched, as it is disputable whether vibrations can be considered as relations. But what happens in the brain, may be a better analogy.
Memories in brains are not stored locally as in computers but in distributed ways. Brains store memories in a highly "Wittgensteinian" manner: The patterns that build a concept or an image in the mind are stored functionally in flux patterns of neurotransmitters between neurons and structurally in terms of links between synaptic links between dendrites and axons (the input and output channels) of different neurons. It is the resulting pattern of relations which maps an event or object we have memorised. Whenever we experience something new, the molecular fluxes stimulate synaptic growth to connect neurons. In this way, sensing, which is a functional process forces the formation of structures. It is like a Yoneda mapping taking place in situ in concrete form: the sensorial patterns we observe and categorise according to a certain pattern similarity in our brains are then stored as a new pattern: The morphisms crystallise or fossilise in a set of synaptic links.
But this type of physical direct mapping does not only occur in the brain; at the level of DNA experiences often result in parts of the DNA being post-translationally modified, most often in the form of methylation. The methylation pattern of the DNA can influence whether a gene is switched on or off. It can also be inherited. This is the field of epi-genetics. Environmental influences can strongly influence the way genes can or cannot be expressed as a consequence of environment-induced methylation. This can also render a gene more prone or vulnerable to mutation or influence the way genes are copied or even multiplied upon cell division. In other words certain types of experiences are also stored on the level of the genes or can result in mutations at the DNA level. Again this is an example how sensing the environment and building a relation with the environment is mapped physically in a set of information. Environmental morphisms fossilising in the form of material and informational structure.
In other words, I have drawn an analogy between the abstract way a Yoneda functor maps and embeds morphisms into a set and the concrete way the brain and the epigenome store information resulting from sensorial input. The way the sensorial input is processed corresponds to the morphisms and the concrete stored information in synaptic links or methylation patterns correspond to the embedded set.
Also in this way structure can be considered as a form of fossilised sense.

Yoneda mapping as an analogy for meditation

One of the techniques in Indian meditation is the "Panchadasi" technique. You mentally try to throw your light on a topic of consideration from 15 different perspectives. By doing so, you probe the object functionally and structurally. It is like having an object defined by a few dots and then trying to connect the dots to see what it represents. In fact you are mapping relations between the dots, and the more you progress from these relations you suddenly start to see what the intended object was. From partial links at a certain moment the whole which is more than the sum of parts reveals itself. By performing this technique and considering a topic from as many perspectives as possible, you build as many ontological relations in your mind as possible. At a certain moment, the framework of ontological relations is sufficient to understand the whole. No longer do you experience a broom, a hose and a drum, but suddenly the elephant -of which you had considered the tail, trump and ears separately, without knowing what they were- snaps into your experience. This holistic experience of the phenomenon of contemplation can even result in that you start to feel what it must be "like" to be this phenomenon. Not only do functional relationships reveal a structure, structural relationships can also reveal function.
To speak in category language, not only do the morphisms lead to a representation in a set, but the relations of the objects in the set can by an inverse functor also be back-translated into the morphisms they originated from.
The meditative process thus might be a way to experience "what it is like to be" concerning the object of contemplation.  In Latin this is called "quale" from which the word quality derives. Neurosciences often speak of "qualia" as the qualitative aspects of observation, such as the "redness" of a tomato. Meditation is often intended to achieve oneness with the object of contemplation. This is achieved by experiencing the "what it is like-ness" of the object. Perhaps a process which resembles Yoneda embedding or the reverse thereof is involved in this experience.
Funny enough, one of the basic tenets of category theory is that if a category is "like" another category there is a meaningful mapping which preserves the structure of the category (functors).

Pancomputational Panpsychic Akasha

In my book "Transcendental metaphysics" I argue that the ground of existence is "primordial consciousness" (i.e. sentience per se if you prefer). From this formless all-pervading filed, informational units arise, which form a kind of neural computational network in the so-called the quantum vacuum, which has been equated with the Indian concept of the "Akasha". The Akasha even allows for a kind of digital processing in addition thereto. If reality is indeed a computational substrate involving information processing as digital physics suggests, there must be a consciousness to make sense of the information (otherwise it is gibberish). This leads to my hypothesis of pancomputational panpsychism. As this network of reality as a whole is considered sentient in this model, perhaps I can also speculate that the very way in which structures arise in this model is via Yoneda embedding. It is interesting to note that Yoneda embedding requires that the functor which operates the mapping does so from a "locally small category". This is important because I have suggested in earlier posts that sentience is present at the smallest level of reality which can be considered to have a certain individuality and relative locality. If reality indeed creates structure by fossilising sensed experiences, then this is not in contradiction with my panpsychic hypothesis. Moreover the fractal of panpsychic entities, which I have proposed, perfectly fits the idea that functions and structures are each other's transform.
In my model your localised awareness inhabits a vessel which is made out of smaller entities (your cells), which can be considered as a bunch of smaller localised entities. The awareness of a cell inhabits a vessel made by atoms, which in turn can be considered as a bunch of smaller localised entities with a minute form of individual awareness. Thus you get a fractal of entities that on the one hand are sensing entities themselves and on the other hand form structured vessels in cooperation. Each entity is then at one level a functional sensorial living entity and at the same time the structural fossilised building block of a higher aggregation level.

I don't say this is my belief or an absolute truth to me. It's a speculative artistic process of associations, which I explore in the hope that one day I will be able to integrate them into a verifiable hypothesis. Consider these my metaphysical musings and please do not take any speculation for a fact in this essay. Perhaps my analogies are not even valid since I am not a mathematician. But if they are I hope my musings will be read by one of them and inspire them, to help me prove my ideas.

Consciousness

In a previous article I have also suggested that primordial consciousness might operate to generate information by self-representation. Again this fits the notion of Yoneda embedding. Self-representation or self-reproduction is a concrete analogy of mapping the functional consciousness process into a fossilised structure that can be experienced , so that the knower generates information as known and by observing its self-generated information comes to know itself as the Ouroboros from alchemy biting its own tail.

Conclusion

I hope to have shown that the abstract mapping of morphisms into sets in mathematical category theory may have an equivalent in the way structures arise in physics and biology. The process of Yoneda embedding may not only be involved in such concrete examples but also in meditative processes as well as in the ontogenesis of existence from primordial consciousness.

By Antonin Tuynman a.k.a Technovedanta; inspired by ideas from Eric D.Ryser.
You can find my book here.
Image from http://eresaw.deviantart.com/art/Soap-Bubble-Ballet-293874327

Thursday 13 July 2017

Tsang's Brain Fractal Theory: The ultimate algorithm for AGI



In this chapter I will discuss how Tsang's Fractal Brain Theory describes a way to implement the evolutionary algorithm of intelligence in a computer environment to generate Artificial General Intelligence.

Background


In my previous book "Is Intelligence an Algorithm?" I described an algorithm that evolution follows to generate complexity. To my great surprise I found the same ingredients back in the book "Fractal Brain Theory", although differently presented. This chapter is the first of a series of a sequel to my previous book.
I described how when a (living) system encounters a problem such as a lack of resources, this gives the system a stimulus to start to probe for a variety of alternatives or other solutions.
Quote from my previous book:
Nature will now generate a plethora of alternatives by combining elements from the environment with the system. 
This includes changes such as mutations.
In Tsang's book an equivalent is found in that the system differentiates or diverges.
From the probing or testing of these alternatives by the system, the system abstracts patterns. (Screening of relational “Syntheses”.) From these the most successful alternative strategies can be selected. (Elimination, Pruning of Syntheses and Emergence of new “Theses”.)
This plays a role in what Tsang calls "intersection", which I will discuss later in this chapter.
Quote from my previous book:
This can be repeated on a heterarchical level between groups of entities or (living or non-living) systems (such as bacterial colonies or animal societies). When contending groups encounter each other, this gives a stimulus to start a so-called “Intergroup tournament”. The tournament can lead to a mutual probing of the distinctions between the groups. Nature will screen which elements from the contender can be copied and integrated and which ones should be discarded. This can result in the formation of 1) a “niche” (each group specialises in a niche such that it does not poach on the contender’s preserves); 2) a “symbiosis”: the groups learn to cohabitate peacefully together and provide each other with a service, resulting in a transactional scenario of a win-win situation); or 3) an exchange of those features which are different between the groups (“mimicking”). Thus the system adapts itself to its environment.
The most promising strategies ideally result in symbiosis, a unification of features toward which the system will strive. 
In Tsang's book I found an equivalent which he calls convergence.
Quote from my previous book:
The system will try to resonate “morphogenetically” (i.e. in form, as dictated by its genetic make-up) with its new environment and thereby adapt to it. This is Nature’s way of continuously striving for more complexity and incorporation of mutual features, as this assures more adaptability to and integration with the environment and hence increased chances for survival. In other words Nature’s intelligence algorithm is essentially integrative: It tries to unite, to combine apparent opposites.
Now one of the most interesting points I found in Tsang's book was the way he described the selection process (which I called the screening and pruning), which he calls the intersection of the convergence and divergence. This is one of the points that I will discuss in more detail in this chapter.
The other point is that Nature is a system performing mapping. I discussed this in my essay: "Is structure fossilised sense". Likewise I find that Tsang describes mapping as the unifying process underlying all natural processes.
Finally, Tsang speaks about a recursive self-modifying process, in which the process takes itself as an object and maps this. This is Yoneda embedding, which I also discussed in my article on structure being fossilised sense. Moreover, in my article on sentience I suggested that this form of self-representation is the very ontogenetic process of reality generation.

Mapping

Tsang convincingly shows that nature both on the genetic as well as the brain level cunningly exploits the process of making binary trees to arrive at an ontogenetic process which observes rules of symmetry and symmetry breaking, recursive self-modification and warranting self-similarity over different scales. The brain maps its experiences, its sensory data observing a hierarchical process involving binary trees, and these are reflected in the generation of corresponding structures at the neuronal level in the form of axonal and dendritic branching  (but also at the genetic level: e.g. epigenetic markers). Moreover, this forward chaining process is mimicked by a backward chaining process in the motor neurons. Both the structural modifications and the motor neuron actions can be considered as mappings of the sensory process: (s)ensing translates into (r)econstruction in terms of Tsang. From (s)timulus to (r)esponse.

Amplification, Reproduction and seed.

Nature has found both at the neuronal and genetic level a system to reproduce itself, which is a special kind of recursive mapping which takes itself as object to generate isomorphic structures, we could call this amplification. At the same time, there is a kind of randomisation process going on allowing for mutations and changes, a differentiation can occur in the copies. At the level of DNA this is obvious in the form of point mutations, deletions and insertions, but at the brain level as well plasticity is rewarded allowing for morphological differentiation and asymmetric linking up of the neurons. Moreover, a Yoneda type mapping process occurs in that the mapping process itself becomes the object of the mapping process. We can reflect on how we reflect and this is reflected in new links being created at the neuronal level. Now that we understand that this type of reflecting is a Yoneda-type of mapping we are actually doing this very thing in situ. The process which maps and creates our neuronal links is mapped to itself. You have now created a mapping of the recursive process by the recursive process. You have done so by creating a hierarchical binary tree. You have crystallised (or fossilised) sensing and function into structure. This is what nature does, it evolves evolvability by a process which Tsang calls recursive self-modification. A hierarchical binary tree generation process which is the unifying process in our ontogenesis.
Tsang moreover shows that the brain is like a fractal structure as every idiosyncratic aspect of the brain can be mapped to a structure or function at the genetic level. After all our genome encodes precisely how our brain's architecture should be formed. Our genome in a certain sense is a brain in seed form.
Interestingly, Stephen King a computer scientist (not the horror writer), called this process of self-generation the generation of a null-representation, a self-representation or a seed, which can grow out into a full blown new entity.

Divergence and Differentiation

And Tsang adds the modifying and divergence or symmetry breaking aspect to it. Some branches will get more attention than others. Neurons have a kind of background random spiking activity, which can be rewarded if an interaction is generated and a connection is built. This creates a divergence. If a cell would simply undergo a doubling process by division without any differentiation, all you would get is a homogeneous essentially spherical blob of cells. Fortunately, nature has invented a way to differentiate by employing so-called morphogens (special chemicals that cells produce), the presence of which tells the cell to differentiate, by silencing certain parts of the DNA and switching on other parts. These morphogens form a gradient, so that not every cell is differentiated, but only the ones where the morphogen concentration is high. Even on the neuronal level there is a differentiation in type, there are activating and inhibitory neurons; there are also spindle cells for long distance information transfer.

Screening, Pruning, Intersection and Selection

I described how nature has to screen and prune the variety of alternatives it has generated to select the most promising ones. Darwin's survival of the fittest. But how does it pull off this trick if a mapping process underlies the ontogenesis? It is here that I found Tsang's description most elegant and inspiring. It employs a combination of forward chaining and backward chaining, just like certain type of heuristics in artificial intelligence. In a literal sense the sensory  motor neurons expand and branch until they meet each other and only those who meet are selected, because they form a link! Just like  a forward chaining heuristic starting from the problem meets a backward chaining heuristic starting from the solution. Tsang describes this as Bayes inverse probability Rule in action. Bayesian probability can be expressed as the chance that B occurs when A is present  P(B ¦ A) being equal to the chance that A occurs multiplied by the chance that A occurs when B is presented and divided by the chance that B occurs: P (B ¦ A) = P(A)*P(A ¦ B)/P(B).
The chance that B occurs when A is present is like the forward chaining heuristic and the chance that A occurs when B is present as the backward chaining heuristic. Where the branches meet a connection is formed and metaphorically an intersection is formed. This is how neurons select. Neurons that wire together fire together. Enhanced flow through a neuron attracts the attention of other neurons, which will then also benefit from enhanced flow. This is like publicity. This is what Howard Bloom calls the "Matthew" principle: To those who have it shall be given, from those who have not it shall be taken away. There is a mutual rewarding going on, which is rather exclusive. Only really new ontologies to be created may be able pull off the trick of including the previously excluded neurons.
But only those who can create a proper linkage create a connection, and Tsang here uses the lock and key metaphor. The conjugation or linking up at every level can only occur if the key of the backward chaining heuristic fits the lock of the forward chaining heuristic. In order to select which ones can link up, a scoring system is needed. Tsang proposes that the lock comes before the keys otherwise we wouldn't have anything to score the keys with. The female precedes the male, in this chicken-and-egg problem.

Convergence and Integration

This shows that ontogenesis is more than differentiation and selection only. The parts must also start to work together, they must be integrated into a whole. A meta-system transition must occur for the cells to group into an organ. And again this trick is pulled off by mapping. Yes, mathematical category theory is a very powerful concept, for describing reality as we know it. Here we employ linking up of the various  mapped elements. This is the cooperative symbiotic part of the evolutionary search engine, allowing the mapped conjugated entities to map into a convergent hierarchical tree. And this new entity can then be submitted to a new round of recursive self-modification, giving rise to the steps I described as intergroup tournament, distinction probing and (further) symbiosis.

Artificial Intelligence

Tsang believes that the ingredients of symmetry, self-similarity and recursion resulting in a simple self-modifying recursive algorithm, which creates binary trees, may be the key to unlocking the secret of Artificial general Intelligence: Creating AI which is context independent and which can achieve or surpass the human level of intelligence. Provided that Tsang in his endeavours in AI includes the elements of selection and integration he has described, this may indeed be a promising novel avenue in this field. But we must not forget that it took nature billions of years to arrive at the complexity we presently have. The different layers and structures in the brain (cerebellum, hypothalamus, pituary gland, hypophysis, hippocampus, amygdala, cerebral cortex etc.) have a very special fine-tuned architecture, which employs a great variety of neurotransmitters. If Tsang's future algorithm is successful it will take quite some cycles and extensive pruning and selection, before a human  level AGI evolves from it. On the other hand the ever increasing speed at which this can occur and the ever increasing resources in terms of memory and miniaturisation according to Moore's law, may pull-off this trick faster than we think. Because it has the very notion of representation and recursive self-modification at its heart.
Noteworthy, Dr Joe Tsien has recently shown that intelligence indeed follows a “neural network” type algorithm (not a traditional von Neumann style algorithm). The more thought, the more cliques join in, Tsien says. The basis of Tsien’s Theory of Connectivity is the algorithm, n=2ⁱ-1, which defines how many cliques are needed for a “Functional Connectivity Motif” to arise. This enabled the scientists to predict the number of cliques needed to recognise options in their testing of the theory. The  2ⁱ in this formula represents the number of neurons that join in, which follows exactly the binary tree indicated by Tsang!

Conclusion

We have seen that Tsang's brain fractal theory can be mapped quite accurately to my "intelligence algorithm" and "structure is fossilised sense" ideas. We have seen that Tsang provides serious improvements thereof in terms of binary trees, an intersection selection and connection process and a recursive self-modifying process. We have also seen that this may be a serious candidate to create human level AGI which may perhaps one day herald the advent of the technological singularity. Thus Tsang lifts the veil of the underlying algorithm of existence as a whole, a process, which the Greek called Apokalypsis. The Fractal Brain Theory by Wai H.Tsang, wholeheartedly recommended.

Thursday 6 July 2017

The Moral Compass of Higher Intelligence: Preface


A wave of divisiveness engulfs this world. Extreme right wing populism is gaining momentum, because many people believe the lies of the demagogues. People believe that their kind should come first and that others should be excluded. They build walls, like between Israel and Palestine and are planning to build one between the USA and Mexico.

Excluding others not only happens on the political plane. Economic exclusion is becoming a more and more frequent phenomenon. People losing their jobs, being evicted from their houses whilst a small group of extreme rich billionaires, the top 0,1% owns as much as the bottom 90%. This is not a scenario of a third world country where such a partitioning is common, this is the reality of the USA!

Strangely enough, the poor and dispossessed hardly organise in cooperatives, guilds and unions. No, there is a general trend that they admire the usurpers. “Exclusivity” is something people crave for. And the poor and dispossessed do not adopt a different more inclusive lifestyle, no they too try to pick every little grain that is still left joining the general tendency to egoism: I first, my kind first.

This tendency towards exclusion and divisiveness are expressions of different types of discrimination. We discriminate with regard to gender (sexism), race (racism), economic status (classism) and religious beliefs (this has no official name, but I’d like to call it “cretism” from the Latin word “credo”).

Moreover as a consequence of the hoarding and overconsumption linked to the reign of egoism, we deplete all mother Earth’s natural resources and we pollute this planet with our vehicles, factories and overconsumption so that many of the huge agglomerations have turned into literal shitholes. The emissions resulting from our massive burning of fossil fuels have resulted in a climate change beyond compare as regards the speed with which the climate is changing. This brings the risk of a runaway scenario in which the air becomes so saturated with carbon dioxide that the resulting greenhouse effect will warm up temperatures which may even make life impossible on earth. Earth could become a second Venus, where temperatures are as high as 462°C!

We are like bacterial colony in a petri dish. We thrived, we boomed with an explosion of population and now we start to really deplete the last resources. What biology tells us is that such a colony will soon herald its own demise. The crisis of survival in the last stages is called a Malthusian crisis after the 19th century biologist Thomas Malthus.

Is this what history has taught us as a viable and sustainable way to survive? Is this an intelligent strategy of the evolutionary search engine?

In my previous series, “Is intelligence an Algorithm?” I have already argued that natural intelligence seeks to cooperate, that the so-called Nash equilibrium results in a win-win situation wherein the overall output is higher than when the contenders would have continued to compete.
Today I read an article by Krnel about morality. Whereas I agree with his intent, I have a slightly different philosophical stance on this topic which I will try to explain in this series (in the last paragraphs of this article you’ll find a hint as to why my stance is different).
In this series I will argue that if we seek the best solutions to our global problems by applying the natural algorithm of intelligence we actually acquire what is a kind of natural morality intrinsic to complex systems that manage to survive.

I will not make many friends with the series, because I am going to challenge your very belief systems. I am going to turn upside down your comfort zone. I am going to tell you an inconvenient truth. I will question what truth is, whether objective truth exists at all. I will question what morality actually is. I will question your religions and only distil therefrom what is universal and in line with Nature’s natural intelligence algorithm. But I will denounce all the nonsense in religions that make man suffer. I will denounce capitalism, communism and anarchism. And I will denounce our corrupted ways of living, which are rapidly sending us towards a point of no return: The extinction of our species.

Is then everything lost?
No, Nature has its intelligent ways to survive even the advent of a destructive variant of a species. When bacteria or eukaryotic unicellular organisms reach the Malthusian crisis, they do something very interesting: They sporulate. The entirety of their intelligent knowledge is so to speak stored in a spore in which their genome is safely packaged in a way that can withstand extreme environmental changes. Once the metaphorical environmental “storm” is over and conditions are favourable again, the spores break open and the organism can come to life again.

We are already sporulating. The whole creation of the internet in which all our knowledge is packed, and the not-so-far-in-the-future awakening of the internet as a quasiconscious entity, lays the foundation for the creation of life, of our successors in a distant future. They might even bring back to life human beings as in the film “Artificial Intelligence” by Steven Spielberg.

This series will explore two avenues:
The first one will describe what we can still attempt to do to save our Earth and learn how to live in a responsible manner. How we can transform the manure of our corrupted ways into a blooming awakening into a sustainable respectful all-inclusive society. The remedy? Turning inwards to our innate intelligence and spirituality.
The second avenue will explore the ways how we can effectively sporulate our knowledge into an artificial substrate, which may allow one day to raise us from death again, but now with the knowledge what we should learn to avoid.

My plea will be moralising. Not because I believe in good and evil, not because I believe in right or wrong, or any other “absolutes”, but because I am pragmatically convinced that intelligence is more successful than ignorance. That usefulness yields better results than futility. Yes, that morality is an innate aspect of intelligence. What I understand under “morality” will be the topic of a next essay.

This is my new project and my new topic for my next book.

Tuesday 2 May 2017

Is Intelligence an Algorithm?


My book "Is Intelligence an Algorithm?" will be published on 26-1-2018 by iff-books. This book is a must for anyone who would like to improve his/her intelligence. The book starts with an overview how in Nature evolutionary complexity is arrived at via an inherent sequence of steps, which you could call an algorithm. Then the book analyses different aspects involved in human intelligence such as (re)cognition, reasoning and problem-solving. The role of emotions and how to control them is also discussed. Three chapters are dedicated to artificial intelligence. The book concludes with the more elusive aspects of intuition.

The book is available on amazon for pre-orders:

https://www.amazon.co.uk/Intelligence-Algorithm-Antonin-Tuynman/dp/1785356704
Here is the "Marketing Blurb":



Do you wish to improve your intelligence? Then we’ll first have to figure out what “intelligence” actually is.
Join me on a journey that starts with Nature’s ways to generate complexity. I will show you that from bacterial wisdom to the quagmire of human social interactions the same steps are followed to generate so-called “meta-system transitions”, where singleton entities organise into societies and finally into new emergent entities built there from.
In this book I will not only dissect intelligence into elements of cognition, pattern recognition, reasoning, problem-solving and diversity generation, I will also venture into the more elusive realms of emotions and intuition.
From these concepts I will provide strategies, heuristics and architectural plans to create a new generation of Artificial Intelligence. A conceptualisation of Artificial Consciousness and a blueprint for an Artificial Webmind.
And as a bonus I will provide you with tools. Tools to organise your thoughts, tools to solve any kind of problem, tools to navigate through the wild waves of our emotions.
This is the abstraction of the dissecting knife of the intellect and the great integrator of cliques allowing to spawn a plethora of novel and inventive solutions which are screened and pruned to generate an apotheosis of ever increasing complexity.
This is the book that reveals nature’s inherent simple algorithm to achieve complex goals in complex environments.

Please visit my new website dedicated to this new book: https://www.intelligencealgorithm.com/ 

I will be needing reviews from people who have read the book. If you are interested in getting a "review copy" for a reduced price before the book is officially published please contact me at iconomen@gmail.com.