If Money = Memory, if Society = a Super Computer, if Computation is in Physical Systems, what is a Decentralized Operating System? By Dana Edwards. Posted on Steemit. October 24, 2018.
These concepts are not often discussed so let's have the discussion from the beginning. The first concept to think about is pancomputationalism or put another way the ubiquitous computers which exist everywhere in our environment. We for example can look at physical systems living and non living and see computations taking place all around us. If you look at rocks and trees you can see memory storage. If you look at DNA you can see code and if you look at viruses you can see microscopic programmers adding new codes to DNA. Even when we look at the weather such as a hurricane it is computing.
If you look at nature you see algorithms. You will see learners (yes the same as in AI), also in nature. The process is basically the same for all learning. Consider that everything which is physical is also digital. Consider that the universe is merely information patterns.
If we look at society we can also think of society as a computer. What does society compute though? One way people talk about a society is as a complex adaptive system, but this is also how people might talk about the human body. The human body computes with the purpose of maintaining homeostasis, to persist through time and reproduce copies of itself over time. The human brain computes to promote the survival of the human body. Just as viruses pass on codes to our DNA, the human brain is infected with mind viruses which are called memes. Memes are pieces of information which can alter physically how the brain is working.
The mind isn't limited to the brain. The mind is all the resources the brain can leverage to compute. In other words a person has a brain to compute with but when language was invented this allowed a person to compute not just using their own brain but using the environment itself. To draw on a cave is to use the cave to enhance the memory of the brain. To use mathematics is to use language to enhance the ability of the brain to compute by relying on external storage and symbol manipulation. To use a computer with a programming language is essentially to use mathematics only instead of writing on the cave wall we are writing in 1s and 0s. The mind exists to augment the brain in a constant feedback loop where the brain relies on the mind to improve itself and adapt. If there were no external reality the brain would have no way to evolve itself and improve.
A society in the strictly human sense of the word is the aggregation of minds. This can be at minimum all the human minds in that society. As technology improves the mind capacity increases because each human can remember more, can access more computation resources, can in essence use technology to continuously improve their mind and then leverage the improved mind to improve their brain. The Internet is the pinnacle of this kind of progress but it's obviously not good enough. While the Internet allows for the creation of a global mind by connecting people, things, and minds, it does nothing to actually improve the feedback loop between the mind and the brain, nor does it really offer what could be offered.
Bitcoin came into the picture and perhaps we can think of it as a better memory. A decentralized memory where essentially you can have money. The problem is that money is a very narrow application. It is the start, just as to learn to write on the cave wall was a start, but it's not ambitious enough in my opinion.
Humans in the current blockchain or crypto community do not have many ways where human computation can be exchanged. Human computation is just as valuable as non biological machine computation because there are some kinds of computations which humans can do quite easily which non biological machines still cannot do as well. Translation for example is something non biological machines have a difficult time with but human beings can do well. This means a market will be able to form where humans can sell their computation to translate stuff. If we look at Amazon Mechanical Turk we can see many tasks which humans can do which computer AI cannot yet do, such as labeling and classifying stuff. In order for things to go to the next level we will need markets which allow humans to contribute human computer and or human knowledge in exchange for crypto tokens.
The concept of a decentralized operating system is interesting. First if there are a such thing as social computations (such as collaborative filtering, subjective ranking, waze, etc) then what about the new paradigm of social dispersed computing?
The question becomes what do we want to do with this computing power? Will we use it to extend life? Will we use it to spread life into the cosmos? Will we use it to become wise? To become moral? To become rational? If we want to focus on these kinds of concerns then we definitely need something more than Bitcoin, Ethereum, or even EOS. While EOS does seem to be pursuing the strategy of a decentralized operating system which seems to be the correct course, it does not get everything right.
One problem is as I mentioned before the importance of the feedback loops between minds and brains. The reason I always communicate on the concept of external mind or extended mind is based on that fact that it is the mind which creates the immune system to protect the brain from harmful memes. The brain keeps the body alive. The brain is not really capable of rationality, or morality, or logic, and relies on the mind to achieve this. The mind is essentially all the computation resources that the brain can leverage.
EOS has the problem in the sense that it doesn't seem to improve the user. The user can connect, can join, can earn or sell, can participate, but unless the user can become wiser, more rational, more moral, then EOS has limits. EOS does have Everpedia which is quite interesting but again there are still problems. What can EOS do to improve people in society and thus improve society, if society is a computer and is in need of being upgraded?
Well if society is a computer first what does society compute? What should it compute? I don't even know how to answer those questions. I could suggest that if computation is a commodity along with data then whichever decentralized operating systems that do compete and exist will compete for these commodities. The total brain power of a society is just as important as the amount of connectivity. And the mind of the society is the most important part of a society because it is what can allow the society to become better over time, allow the people in the society to thrive, allow the life forms to continue to evolve avoid extinction.
A decentralized operating system on a technical level would have a kernel or something similar to it. This is the resource management part. For example Aragon promises to offer a decentralized OS and it too mentions having a kernel. A true decentralized operating system has to go further and requires autonomous agents. Autonomous agents which can act on behalf of their owners are philosophically speaking the extended mind. But the resources of a society is still finite, has to be managed, and so a kernel would provide for an ability to allow for resource management.
The total computation ability of a society is likely a massive amount of resources. A lot more than just to connect a bunch of CPUs together. Every member of the society which can compute could participate in a computation market. Of course as we are beginning to see now, the regulators seem concerned about certain kinds of social computations such as prediction markets. So it is unknown how truly decentralized operating systems would be handled but my guess is that if designed right then they could be pro-social, be capable of producing augmented morality by leveraging mass computation, and also by leveraging human computation be able to be compliant. To be compliant is simply to understand the local laws but these can be programmed into the autonomous agents if people think it is necessary.
What is more important is that if a law is clearly bad, and people have enhanced minds, then it will be very clear why the law is bad. This clarity will help people to dispute and seek to change bad laws through the appropriate channels. If there is more wisdom, due to insights from big data, from data scientists, etc, then there can be proposals for law changes which are much wiser and more intelligent. This is something specifically that people in the Tauchain community have realized (that technology can be used to improve policy making).
A lot is still unknown so these writings do not provide clear answers. Consider this just a stream of consciousness about concepts I am deeply contemplating. This is also a way to interpret different technologies.
“We are moving into an era where cities will matter more than states and supply chains will be a more important source of power than militaries — whose main purpose will be to protect supply chains rather than borders. Competitive connectivity is the arms race of the 21st century.”
-- Parag Khanna , 
A network is made of lines and switches, right?
Lots have been told about the network scaling effects , including attempts by myself [4-12] ... which compels me to introduce the not so frivolous notion of network forces.
These forces are expressed in several laws. I though initially to say 'forces' and 'laws' here, but I realize they are quite objective and physical emergenta , indeed.
In my ''Geodesic by Tauchain''  article of about couple of months ago I emphasized over the Huber-Hettinga Law , of how cost of switching literally defines the 'orographic'  topology of a network .
The cheaper the routing - the flatter the network.
Expensive switches = hierarchy, verticality, power, control, obey, centalization, 'world is fiat' ,, sollen , hence borders instead of bridges, limitations not stumulae, exclusivity ...
Cheap switching = geodesic society , 'world is flat', horizontality, p2p, decentralization, inclusivity ...
The more vertical by centralization a network is - the more it must deplete information - to omit, to ignore calls from the deeps or to even actively suppress or silence nodes. To cope with the stream by strangling it. Simply due to lesser capacity, less degrees of freedom . Geodesic networks possess higher entropy  and therefore are richer. They bolster higher both Scrooge  and Spawn  factors. With other words:
The flatter the network - the richer  it is.
Maybe the explanation on why the wealthiest-healthiest societies tend to be those who are with biggest economic-political freedom. 
Naturally the Huber-Hettinga Law led me to the elementary-watson  conclusion of the power and value of Tau as the ultimate über -switch. So far so good.
Now lets stare in the Lines. Here comes Nick Szabo .
Nick Szabo - a lawyer AND computer scientist - is a legendary figure from the great 'Archaic era of crypto'  - the 1990es when he, together with the other cypherpunk  titans like Tim May , Wei Dai , Bob Hettinga  etc. etc., poured the very baserock foundations in a staggering detail of what we enjoy now as Crypto  in the post-Satoshi  era.
It is THEIR vision came true we all now live in.
Bitcoin was a detonation of namely that critical mass of fused thoughts, of namely these very smart people, piled up and compressed by the connective network forces of the early internet .
No, I do not mean at all Szabo's most famous thing - the 1994 coining of the term of 'smart contracts' . In fact I deeply and strongly reject the very notion of 'smart contracts' - as utter non-sense, even as an oxymoron - which is an yuge separate problem, which I suspect that I nailed it, and I'll address in series of dedicated articles starting in the upcoming weeks...
I mean something much more valuable, what I call the Szabo Law.
When we hear the phrase 'networking effects' the first what comes to mind is the famous Metcalfe law .
''Metcalfe's Law is related to the fact that the number of unique connections in a network of a number of nodes (n) can be expressed mathematically as the triangular number n(n − 1)/2, which is proportional to n2 asymptotically (that is, an element of BigO(n2)).''
In the above order of appearance these network forces laws respect quantitatively the basic properties of a network as:
- Huber-Hettinga Law - the cost of switches and routing.
- Metcalfe Law - the number of nodes, i.e. switches defining the number of unique connections or lines.
- Szabo Law - the cost of the lines and connecting.
All these Laws are scaling ,  laws. Before we to come back to and continue on Szabo Law, we have to briefly mention another one .:
''So what is “scaling”? In its most elemental form, it simply refers to how systems respond when their sizes change. What happens to cities or companies if their sizes are doubled? What happens to buildings, airplanes, economies, or animals if they are halved? Do cities that are twice as large have approximately twice as many roads and produce double the number of patents? Should the profits of a company twice the size of another company double? Does an animal that is half the mass of another animal require half as much food?'' ... With Dirk Helbing (a physicist, now at ETH Zurich) and his student Christian Kuhnert, and later with Luis Bettencourt (a Los Alamos physicist now an SFI Professor), Jose Lobo (an economist, now at ASU), and Debbie Strumsky (UNC-Charlotte), we discovered that cities, like organisms, do indeed exhibit “universal” power law scaling, but with some crucial differences from biological systems.Infrastructural measures, such as numbers of gas stations and lengths of roads and electrical cables, all scale sublinearly with city population size, manifesting economies of scale with a common exponent around 0.85 (rather than the 0.75 observed in biology). More significantly, however, was the emergence of a new phenomenon not observed in biology, namely, superlinear scaling: socioeconomic quantities involving human interaction, such as wages, patents, AIDS cases, and violent crime all scale with a common exponent around 1.15. Thus, on a per capita basis, human interaction metrics (which encompass innovation and wealth creation) systematically increase with city size while, to the same degree, infrastructural metrics manifest increasing savings. Put slightly differently: with every doubling of city size, whether from 20,000 to 40,000 people or 2M to 4M people, socioeconomic quantities – the good, the bad, and the ugly – increase by approximately 15% per person with a concomitant 15% savings on all city infrastructure-related costs.
Which probably comes to denote the shear size of the network in STEM (space, time, energy, mass) , I'm not sure, but I have some strong suspicions about the unity of matter, structure and action which I will expose and share some other time.
What I call Szabo's Law reveals in his ''Transportation, divergence, and the industrial revolution''(Thu, Oct 16, 2014)  that similarly to Metcalfe's (''double the population, quadruple the economy'') there is power-law  correlation between the cost of connections or links or lines ... and the value of the network, too.:
''Metcalfe's Law states that a value of a network is proportional to the square of the number of its nodes. In an area where good soils, mines, and forests are randomly distributed, the number of nodes valuable to an industrial economy is proportional to the area encompassed. The number of such nodes that can be economically accessed is an inverse square of the cost per mile of transportation. Combine this with Metcalfe's Law and we reach a dramatic but solid mathematical conclusion: the potential value of a land transportation network is the inverse fourth power of the cost of that transportation. A reduction in transportation costs in a trade network by a factor of two increases the potential value of that network by a factor of sixteen. While a power of exactly 4.0 will usually be too high, due to redundancies, this does show how the cost of transportation can have a radical nonlinear impact on the value of the trade networks it enables. This formalizes Adam Smith's observations: the division of labor (and thus value of an economy) increases with the extent of the market, and the extent of the market is heavily influenced by transportation costs (as he extensively discussed in his Wealth of Nations).''
My encounter with this article of Nick Szabo's was a goosebumps experience for me, cause it coincided with series of lay rants of mine on the old Zennet irc chat room of Tau that ''computation =communication =transportation''. Somewhere in 2016 as far as I remember. :)
Maybe it was the last drop to shape my conviction that by my dedicated involvement in both Tau and ET3 , , , I'm actually working for ... one and a same project.
For communication, computation and transportation being modes of state change. Cause information is a verb, not a noun. And software being states of hardware.
''Decentralizing the internet is possible only with decentralized physical infrastructure.'' 
Just like the brain is a network computer of neuron nanocomputers , the emergent composite we colloquially call humanity or mankind or economy or society or world ... is a network computer made of all us billions of humans.
Brains do thought, economies do wealth.
Integrated circuitry  upon the face of planet Earth as a motherboard . Literally. The Humanity's planet-hardware. Parag Khanna's Connectography explained.
The Earth is definitely not our ultimate chip carrier . Probably there ain't limit at all of our culture-upon-nature hardware upgrades, see: , . The universe is our computronium  and we've been here for too short and haven't seen far enough. Networking is connectomics . And thus it always also is metabolomics .
Remember my last month's  ''Tauchain the Hanson Engine''?
The series of exponentially shortened growth doubling times looks like driven by transportation technological singularities : domestication of the horse, oceanic navigation, combustion engine ...
In the light of all the net forces summoned above: The planet Earth viewed as a giant computer chip ...
- itself is a subject of the relentless network entropic  force of the Moore's law 
The network forces accelerate what that wealth computer does.
Two quick examples:
A.: The $1500 sandwich  as a proof that trade+production is at least thousands of times stronger in sandwich-making than production alone.
B.: The example of Eric Beinhocker in his 2006 ''The Origin of Wealth''  about the two contemporary tribes of the Amazonian Yanomami  - a stone age population nowadays and the Eastcoastian Manhattanites . That the former are only about 100 times poorer, but the later enjoy billions of times bigger choice of things to have.
Tauchain 'threatens' to affect the parameters of ALL the network forces formulae mentioned herewith in a mind-bogglingly big scale.
Simultaneously, orders of magnitude :
- lower switch cost
- higher nodes count 
- lower connection cost
A wealth hypercane  recipe. Perfect value storm. Future ain't what it used to be .
Size matters. Some people object that it does not matter, but has meaning. But meaning always matters, so it is the same.
The bigger problems one solves, the bigger the gains. Big problems require big solutions. We live in a big universe and our very survival is to deal with bigger and bigger problems, which require bigger and bigger solutions to cope.
But nevertheless to build big is hard so we naturally prefer to create small things which can grow. Small from point of view both of understandable and affordable to build. So best fit are small solutions, cheap and easy to make which scale out or unfold or unleash into big means to address big problems. Scaling is everything.
Scaling. Scalable! Scalability !!
The root-word 'scale' possesses marvelous riches of meaning in English language  with lots of poetics inside.:
 snake skin epidermals - wisdom, memory, protection, rejuvenation, regeneration, eternity...
hen to pan (ἓν τὸ πᾶν), "the all is one"
 warrior armour - security, defense, power, strength.
 weighting scales - device to measure mass, unit, measure, account.
all very Blockchainy wording without any shadow of doubt.
The scalability issues could be grokked  with the following anecdote:
Bunch of workers on a construction site and a huge log. The onsite manager commands a few of them to lift and move it. They try and object ''Too heavy!''. The manager adds more and more workers, until they shout back again: ''Too short!''.
A few real examples, the first two - bad and the last three excellent:
[a] I won't name this 'crypto' just will say it is named after a mythical element of the universe, according to the prescientific gnostic  imaginations. It's core 'value proposition is to shovel meaningful computation into a thread of computation which very value proposition is to be as random, meaningless and unidirectional (hard to do, easy to prove) as possibly possible - the blockchain. The theoretically most expensive form of computation. Visualize: cars and airplanes made of gold and diamonds burning most expensive perfumes. Or mass production of electricity by raising trillions of cats and hiring trillions of people to pet them with grid of pure gold wires to discharge and collect the electrostatics. If they have chosen the original Satoshi blockchain  for their 'experiments' - where the futility of such attempt would become instantly clear and would die out outright due to impending unbearable cost - will of course be more fair way to do, and would've spared dozens of billions of dollars to the Mankind, but logically they preferred a 'controlled' blockchain of their own. In a sense that the guys with vested interest into it have the power to hand-drive, stop, restart and vivisect it. The only use of this 'blockchain supercomputer' is ... tokenomics by Layering. Why it was at all necessary for a blockchain advertised as so good as to do all the general computation, to be made so hairy and bushy with layered tokens??
[b] Another trio of chaps, won't mention names again, were really at awe with Satoshi's creation, so much that they not just liked, but wanted it and decided to have it. For themselves. All of it. And rebelled and forked out and provided 'scaling' errrmm ... uhhh... solution. By increasing the blocksize. Something which Satoshi meditated on, extensively discussed with his disciples and not occasionally decided to put breaks on.  Very recently the crypto news headlines said that the blocksize increase solution providers are eyeing ... Layering. Which they furiously were advocating that blocksize increase makes unnecessary. Cause it is the solution, isn't it? Or maybe it just was. And is not anymore? Well, I'd say that all the aka 'alts'  - to provide a rejuvenated clone of Bitcoin tweeked here and there to provide momentary ease of difficulty and transaction fees - suffer from one and a same problem - traveling back in time does not tell you the future.
[c] Lets jump half a century back in time. It is 1960es. The very making of internet. Computers are already here and scaled up in numbers so their networking to become a problem/juice worth the solution/squeeze. The birth of TCP/IP  and the report of the very makers of it. Of the solution for the network scaling. Enjoy the ancient wisdom:
Initially, the TCP managed both datagram transmissions and routing, but as the protocol grew, other researchers recommended a division of functionality into protocol layers. Advocates included Johnatan Postel of the University of Southern California's Information Sciences Institute, who edited the Request for Comments (RFCs), the technical and strategic document series that has both documented and catalyzed Internet development. Postel stated, "We are screwing up in our design of Internet protocols by violating the principle of layering." Encapsulation of different mechanisms was intended to create an environment where the upper layers could access only what was needed from the lower layers. A monolithic design would be inflexible and lead to scalability issues. The Transmission Control Program was split into two distinct protocols, the Transmission Control Protocol and the Internet Protocol.
The layering made the Internet as we know it. By the simple trick of just one node needed to permit another. Unstoppable inclusivity!
[d] The Mastercoin / Omni Layer :
«A common analogy that is used to describe the relation of the Omni Layer to bitcoin is that of HTTP to TCP/IP: HTTP, like the Omni Layer, is the application layer to the more fundamental transport and internet layer of TCP/IP, like bitcoin».
[e] The Lightning network (LN) :
The Lightning Network is a "second layer" payment protocol that operates on top of a blockchain (most commonly Bitcoin).
Satoshi spoke on 'payment' channels in his masterpiece. Foreseeing the way to scale.
An estimate of the power of LN layering .:
''The bitcoin devs accept that eventually larger block sizes will be needed. The current transaction rate isn't going to cut it if people all over the world actually start using bitcoin daily. They estimate that eventually, if everyone in the world uses bitcoin and makes 2 transactions a day, but uses the lightning network, a 133mb blocksize will be needed. Without the lightning network, something like a 200gb (GIGABYTE) size PER BLOCK would be needed to accommodate that much usage.''
Layering upscales it with orders of magnitude of higher efficiency.
If Bitcoin is the 'first layer' and Omni and Lightning are 'second layer', I see which one is the 'Zeroth Layer' and also foresee  the inevitability of the merger or 'Amalgamation' of all second layers over all blockchains, so the user will be able to transact everything into anything to anybody, without to know or care which chain is in use ... I have special nicknames for these and will go back to these topics in series of future posts.
Enough of examples I reckon.
The Postel's sacred Principle of Layering comes from the implementation levels paradigm.
or Abstraction layering :
''separations of concerns to facilitate interoperability and platform independence''
With other words - delegate the task to that layer of the system which does the particular job best. We can generalize this into The Scaling Commandment. Only one enough:
''Thou shalt not jam it all into a single layer!''
The Layer Cake architecture is literally ubiquitous across the Universe.: biology, semantics, informatics ...
It seems that it is if not the only, at least THE way to scale.
Maybe, someday, we the Humanity, upscaled by Tauchain will discover more powerful than Layering ways to Scale, but it is all we have for now.
Scaling is a problem. Scaling must be scalable, too.
Metascale from here to Eternity.
''Thinking by Machine: A Study of Cybernetics''
by Pierre de Latil 
Published by Houghton Mifflin Company in 1957 (c.1956), Boston.
Foreword of Isaac Asimov (then only 36 years old) ! Recommendation by the legendary mathematician and cyberneticist Norbert Wiener (then 62 years old) ! ... A true jewel! The book is described as:
A review of "the last ten years' progress in the development of self-governing machines," describing "the principles that make the most complex automatic machines possible, as well as the fundamentals of their construction."
Nineteen fifties !! The midway between the first digital computer made by my half-compatriot John Atanasoff  and internet . Almost a human generation span between the former, the book and the later event. Epoch so deep in the past that even television, air travel, rockets and nukes ... were young then.
Same Kondratieff  wave phase btw, which hints towards the historical rhyming of socially important intellectual interests. (On how K-waves imprint on the humanity growth curve - in series of other posts to come).
I must admit here that I've never put my hands and eyes onto this book. But, it is stamped into my mind and memory by Stanislaw Lem  - one of the greatest philosophers of the XXth century, working under the disguise of a Sci-Fi writer, for being caught on the wrong side of the Iron curtain.
''Summa Technologiae'' (1964)  is a monumental work of Lem's, where most issues discussed sound more contemporary nowadays than they were the more than half a century ago when it was built, and for many things also we are yet in the deep past ...
... Lem reports and discussed the following from the aforementioned Pierre de Latil's book.:
''As a starting point will serve a graphic chart classifying effectors, i.e., systems capable of acting, which Pierre de Latil included in his book Artificial Thinking [P. de Latil: Sztuczne mys´lenie. Warsaw 1958]. He distinguishes three main classes of effectors. To the first, the deterministic effectors, belong simple (like a hammer) and complex devices (adding machine, classical machines) as well as devices coupled to the environment (but without feedback) - e.g. automatic fire alarm. The second class, organized effectors, includes systems with feedback: machines with built-in determinism of action (automatic regulators, e.g., steam engine), machines with variable goals of action (externally conditioned, e.g., electronic brains) and self-programming machines (system capable of self-organization). To the latter group belong the animals and humans. One more degree of freedom can be found in systems which are capable, in order to achieve their goals, to change themselves (de Latil calls this the freedom of the "who", meaning that, while the organization and material of his body "is given" to man, systems of that higher type can - being restricted only with respect to the choice of the building material - radically reconstruct the organization of their own system: as an example may serve a living species during biological evolution). A hypothetical effector of an even higher degree also possesses the freedom of choice of the building material from which "it creates itself". De Latil suggests for such an effector with highest freedom - the mechanism of self-creation of cosmic matter according to Hoyle's theory. It is easy to see that a far less hypothetical and easily verifiable system of that kind is the technological evolution. It displays all the features of a system with feedback, programmed "from within", i.e., self-organizing, additionally equipped with freedom with respect to total self-reconstruction (like a living, evolving species) as well as with respect to the choice of the building material (since a technology has at its disposal everything the universe contains).
Longish quote, but every word in it is a worth. When I've read this as a kid back in 1980es ... immediately came to my mind the next, the seventh logical higher effector class.: the worldmaker !!
The degrees of freedom of all the previous six according to the classical taxonomy of de Latil are confined by the rule-set, the local laws of physics.
They are prisoners of an universe. Like birds incapable to reconfig their cage into roomier and cozier ones.
If we regard the laws of nature as code or algorithm, my 7th level effector will be capable to draft and implement itself onto newer and stronger algorithmic foundations. ( Note the seamlessness between computation and robotics in Latil/Lem categorization construct - quite logical indeed, having in mind that software is state of hardware, that matter-form-action are inextricable from each other, but on this in series of other times and posts ... ). Without bond?
So, I wonder:
Where, you reckon, is Tauchain  placed onto the Latil's effectors map?
Retrodictive archaeology is so tempting. It is about what it was, what it is, what we knew and what we know.
Here I present another time travel glimpse of mine:
February 1998. Global Information Summit*. Japan. Robert Hettinga** - the patriarch of financial cryptography wrote:
My realization was, if Moore's Law creates geodesic communications networks, and our social structures -- our institutions, our businesses, our governments -- all map to the way we communicate in large groups, then we are in the process of creating a geodesic society. A society in which communication between any two residents of that society, people, economic entities, pieces of software, whatever, is geodesic: literally, the straightest line across a sphere, rather than hierarchical, through a chain of command, for instance.
A network scales according to the capacity of its switches.
Mankind is a network of interlinked humans routed by ... humans.
The network topology*** of society is dictated by our incapacity to switch - similarly to the way the penguins society is shaped by their inability to fly.
Running the Sorites paradox**** in reverse - humanity does not form a sand-heap by adding grains, but fractalizes into groupings of up to just a few individuals.*****
Big body of research on discussions persistently brings back the result that over a certain threshold of as little as 5 persons the number of possible social interactions explosively exceeds the participants capacity to handle the group traffic of information.
Increase the group size and the 'c factor' - the collective intelligence - abruptly implodes. Bellow the individual human level. So long 'wisdom of the crowd'.
Hierarchy is the only way we know (up to now) for a society to scale. Centralization as emergenta of organic switching limitations.
It is fair to say that we have and have had upscaling exosomatic prosthetics all the time.: language, writing, institutions, specialization... but at the end of the day even within these boosters the social switching is bottlenecked down to just a few humans-strong.
Since recently, cause, you know ... computers. Humans are not only lousy switches, but also tremendously expensive ones to make. Computers - the vice versa: their performance/cost relentlessly bigbangs.
Moore's law****** is not only about silicon wafers. It is a megatrend from the very dawn of the universe as Kurzweil noticed******* long time ago, which goes up and up across all computronium substrata imaginable or possible.
Non-human computation and automated communication promises to break the social scaling barrier.
Here comes the Ohad Asor's Tau.********
The only project I know which asks the correct questions and looks into doable solutions of humanity scaling. And the only meaningful identification and treatment of these problems which seems to lead towards fulfilling of Bob Hettinga's Geodesic visions from few decades ago.
Of course I do not know it all, but lets say that I intensively search the relevant space.
Tau transcends the human switching limitations in humane way. Without to amalgamate individuals out of existence, which some other discussed ways - like direct neural interfacing - seem to inevitably infer. For society is ... human beings.
What's the pragmatics of geodesic vs hierarchic?
What game really the 'flat' p2p networks beat the vertical social configurations into?
It is an easy answer. It is pure physics:
A Tauful geodesic society comprises IMMENSELY richer economy.
Metcalfe's (and Szabo's) law on max!
The combinatorial size of it vastly exceeds the possible arrangements of any traditional social 'pyramid'.
The maximum social diameter becomes ~1.
In fact, it seems quite an ancient archetypal vision, the whole thing:
“Imagine a multidimensional spider’s web in the early morning covered with dew drops. And every dew drop contains the reflection of all the other dew drops. And, in each reflected dew drop, the reflections of all the other dew drops in that reflection. And so ad infinitum.” Allan Ginsberg*********
1. *- http://www.nikkei.co.jp/summit/98summit/english/online/emlasia3.html (the second entry)
2. **- http://nakamotoinstitute.org/the-geodesic-market/
3. ***- https://en.wikipedia.org/wiki/Network_topology
4. ****- https://en.wikipedia.org/wiki/Sorites_paradox
5. *****- https://sheilamargolis.com/2011/01/24/what-is-the-optimal-group-size-for-decision-making/
9.*********- https://en.wikipedia.org/wiki/Indra%27s_net (image from: https://mindfulnessforhealing.com/2012/12/29/weaving-a-tapestry-of-wellness/ )
NOTE: I'm in the Tau Team, but this post expresses only my own associations and interpretations.
More on partial evaluation - How does partial evaluation work and why is it important? By Dana Edwards. Posted on Steemit. December 23, 2017.
I have been asked the question about what partial evaluation is. Partial evaluation is one of the core components behind the Tau Meta Language. In order to understand Tauchain and TML we have to do a little digging to understand not just partial evaluation but in specific the partial fixed point logic.
Self interpretation and self definition are the core of what makes Tauchain unique, and no other crypto or really any technology outside of academia will have that. Partial fixed point logic will be discussed in this blog post along with Futamura's paper on partial evalulation.
Partial Evaluation of Computation Process--An Approach to a Compiler-Compiler
Futamura's paper discusses partial evaluation as an approach to a compiler compiler. A compiler as many programmers know, is a lot like a translator. A compiler translates "source code" written in a high level formal language into "machine code" which is a lower level language. This translation process is what allows human "programmers" to communicate in a language which the machine can understand without having to speak directly in the machine code at the lowest level. With this in mind we can now understand that a compiler-compiler allows humans to describe, define, and compile a compiler, in essence allowing humans to create new programming languages.
Partial evaluation is a means of building a compiler compiler allowing this. A partial evaluation of a computation is based upon taking the formal description of the semantics of a programming language which is known as an "interpreter", allowing for description of the "evaluation procedure" which is the interpreter, to be used for defining the semantics of a programming language. So to simplify it down, the interpreter allows the advanced users of TML to define the semantics also known as the "meaning" of a programming language. This gives the user of TML a lot of flexibility, to in essence define their own programming language and then compile it (compiler-compiler). A meta compiler is what the paper describes as the ability to compile a particular language, where the partial evaluation process is where the meaning behind the semantics is defined.
A programming language is both syntax and semantics. So for future reference, after parsing is complete (syntax analysis) the meaning comes from the semantics through "semantic analysis". Partial evaluation is a process pertaining to the semantic analysis portion which takes place after syntax analysis otherwise called parsing. So we start with source code, which is input into a parser, which outputs into the generator, which at this point receives input from the partial evaluator just prior to the final stage of compilation into "machine code".
The significance of partial evaluation in Tauchain and the interesting features of partial fixed point logic
Partial evaluation is a bit of a tweak on what is usually called a compiler-compiler or parser generator. Partial fixed point logic is where the magic of TML is supposed to happen and by magic I mean the main selling points such as self defining, decidable, etc. A quick Google search of fixed point logic shows that fixed point logic has a role in model checking which is a critical design feature for Tauchain. We also learn that partial fixed point logic is more expressive on infinite structures than inflationary fixed point logic.
The critical paper comes from Imhof titled "logics that define their own semantics". It is almost magical in that in this paper we are presented with the logic which is self definable by it's nature as well as decidable. So the literature is clearly showing that theory backs TML. TML likey will be used to produce a partial fixed point logic solver which through the unique properties of this logic we will gain the magical properties promised for Tauchain. To understand partial fixed point logic fully requires a lot more in depth study, but this blog post will point potential developers in the right direction so that the most basic questions are answered.
What is the significance of this breakthrough? This is the part which is hardest for me because it opens the door to so many opportunities and so much potential. For example what can developers do with the ability to inject any logic they wish, whether partial fixed point logic or some other? What does this mean for Tauchain which can now support multiple logics? What does this mean for Agoras which can be built using a decidable logic yet be expressive? PSPACE complexity, what will this allow for developers?
I'm unable to answer those questions sufficiently, but I think this is a much bigger deal than mere "Turing complete" status which we see common with the current state of the art blockchain tech. In a way this represents the next level, which is a state of the art meta language and compiler-compiler where flexibility is in the ability to communicate from human to machine.
Futamura, Y. (1999). Partial evaluation of computation process—an approach to a compiler-compiler. Higher-Order and Symbolic Computation, 12(4), 381-391.
Kreutzer, S. (2002, September). Partial fixed-point logic on infinite structures. In CSL (pp. 337-351).
Imhof, H. (1999). Logics that define their own semantics. Archive for Mathematical Logic, 38(8), 491-513.
Fuente / Source: Original post written by Dana Edwards. Published on Steemit. December 23, 2017.
The value of Knowledge Representation and the Decentralized Knowledge Base for Artificial Intelligence (expert systems). By Dana Edwards. Posted on Steemit. March 27, 2017.
This article contains an explanation of two core concepts for creating decentralized artificial intelligence and also discusses some projects which are attempting to bring these concepts into practical reality. The first of these concepts is called knowledge representation. The second of these concepts is called a knowledge base. Human beings contribute to a knowledge base using a knowledge representation language. Reasoning over this knowledge base is possible and artificial intelligence utilizing this knowledge base is also possible.
Knowledge representation defined by it's roles.
To define knowledge representation we must list the five roles of knowledge representation which can reveal what it does.
1. Knowledge representation is a surrogate
2. Knowledge representation is a set of ontological commitments
3. Knowledge representation is a fragmentary theory of intelligent reasoning
4. Knowledge representation is a medium for efficient computation
Part 1: Knowledge Representation is a Surrogate
By surrogate we means it is substituting or acting in place of something. So if knowledge representation is a surrogate then it must be representing some original. There is of course an issue that the surrogate must be a completely accurate representation but if we want a completely accurate representation of an object then it can only come from the object itself. In this case all other representations are inaccurate as they inevitably contain simplifying assumptions and possibly artifacts. To put this into a context, if you make a copy of an audio recording, for every copy you make it going to contain slightly more artifacts. This similarly also happens when dealing with information sent through a wire, where if not properly amplified there eventually will be artifects that come from copying a transmission.
"Two important consequences follow from the inevitability of imperfect surrogates. One consequence is that in describing the natural world, we must inevitably lie, by omission at least. At a minimum we must omit some of the effectively limitless complexity of the natural world; our descriptions may in addition introduce artifacts not present in the world.
Part 2: Knowledge Representation is a Set of Ontological Commitments.
"If, as we have argued, all representations are imperfect approximations to reality, each approximation attending to some things and ignoring others, then in selecting any representation we are in the very same act unavoidably making a set of decisions about how and what to see in the world. That is, selecting a representation means making a set of ontological commitments. (2) The commitments are in effect a strong pair of glasses that determine what we can see, bringing some part of the world into sharp focus, at the expense of blurring other parts."
In this case because our commitments are made then our representation is selected by making a set of ontological commitments. An ontological commitment is a framework for how we will view the world, such as viewing the world through logic. If we choose to view the world through logic, through rule-based systems then all of our knowledge about the world is also within that framework. We choose our representation technology and commit to a particular view of the world.
Part 3: Knowledge Representation is a Fragmentary Theory of Intelligent Reasoning.
Mathmaetical logic seems to provide a basis for some of intelligent reasoning but it is also recognized to be derived from the five fields which include of course mathematical logic, but also psychology, biology, statistics, and economics. If we go with mathematical logic then we have deductive and inductive reasoning approaches. Deductive reasoning according to some is the basis behind. If we want to explore an example of reasoning we can take the Socrates example,
Statement A: True? Y/N?
"All men are mortal"
Statement B: True? Y/N?
"Socrates is a man"
Satement C: True? Y/N?
"Socrates is a mortal"
If A is true, and B is also true, then C must be true. This is an example of basic logical reasoning which can easily be resolved using symbol manipulation and knowledge representation. The symbol at play in this example would be implication.
Part 4: Knowledge Representation is a Medium for Efficient Computation.
If we think of computational efficiency, and think of all forms of computation whether mechanical or natural in the sense of the sort of computation done by a biological entity, then we may think of knowledge representation as a medium for that computation efficiency. Currently we think of money as a medium of exchange, and if we think of the human brain as a type of computer which does human computation, then we may think of knowledge representation.
While the issue of efficient use of representations has been addressed by representation designers, in the larger sense the field appears to have been historically ambivalent in its reaction. Early recognition of the notion of heuristic adequacy  demonstrates that early on researchers appreciated the significance of the computational properties of a representation, but the tone of much subsequent work in logic (e.g., ) suggested that epistemology (knowledge content) alone mattered, and defined computational efficiency out of the agenda. Epistemology does of course matter, and it may be useful to study it without the potentially distracting concerns about speed. But eventually we must compute with our representations, hence efficiency must be part of the agenda. The pendulum later swung sharply over, to what we might call the computational imperative view. Some work in this vein (e.g., ) offered representation languages whose design was strongly driven by the desire to provide not only efficiency, but guaranteed efficiency. The result appears to be a language of significant speed but restricted expressive power .
While I will admit the above paragraph may be a bit cryptic, shows that there is a view that better representation of knowledge leads to computational efficiency.
Part 5: Knowledge Representation is a Medium of Human Expression.
Of course knowledge representation is part of how we communicate with each other or with machines. Human beings use natural language to convey knowledge and this natural language can include the use of vocabularies of words with agreed upon meanings. This vocabulary of words may be found in various dictionaries including the urban dictionary and we rely on these dictionaries as a sort of knowledge base.
What is a decentralized Knowledge Base?
To understand what a decentralized knowledge base is we must first describe what a knowledge base is. A knowledge base stores knowledge representations which are described in the above examples. This knowledge base in more simple terms could be thought of as representing the facts about the world in the form of structured and or unstructured information which can be utilized by a computer system. An artificial intelligence can utilize a knowledge base to solve problems and typically this particular kind of artificial intelligence is called an expert system. The artificial intelligence in the most simple form will just reason on this knowledge base through an inference engine and through this it can do the sort of computations which are of great utility to problem solvers.
When we think of Wikipedia we are thinking about an encyclopedia which the whole world can contribute to. When we think about the problems with Wikipedia we can quickly see that one of the problems is the fact that it's centralized. We also have the problem that the knowledge that is stored on Wikipedia is not stored in a way which machines can make use of it and this means even if Wikipedia can be useful for humans to look up facts it is not in the current form able to act effectively as a decentralized knowledge base. DBPedia is an attempt to bring Wikipedia into a form which machines can make use of but it still is centralized which means a DDOS or similar attack can censor it.
Decentralized knowledge is important for the world and a decentralized knowledge base is critical for the development of a decentralized AI. If we are speaking about an expert system then the knowledge base would have to be as large as possible which means we may need to give the incentive for human beings to contribute and share their knowledge with this decentralized knowledge base. We also would have to provide a knowledge representation language so that human beings can share their knowledge in the appropriate way for it to enter into the knowledge base to be used by potential AI.
Knowledge representation is a necessary component for the vast majority of attempts at a truly decentralized AI. If we are going to deal with any AI then we must have a way for human beings to convey knowledge to the machines in a way which both the human beings and machines can understand it. The use of a knowledge representation language makes it possible for a human being to contribute to a knowledge base and this ultimately allows for machines to make use of it's inference engine capabilities to reason from this knowledge base. In the case of a decentralized knowledge base then the barrier of entry is low or non-existent and any human being or perhaps any living being or even robots can contribute to this shared resource yet at the same time both humans and machines can gain utility from this shared resource. An artificial intelligence which functions similar to an expert system can make use of an extremely large knowledge base to solve complex problems and a decentralized knowledge base combined with open and decentralized access to this artificial intelligence can benefit humanity and life on earth in general if used appropriately.
Discussion of example projects.
One of the well known attempts to do something like this is Tauchain which will have both a knowledge representation system and a decentralized knowledge base. In the case of Tau there will be a special simple knowledge representation language under development which resembles simplified controlled English. This knowledge representation language will allow anyone to contribute to the collective knowledge base. Tauchain eventually will have a decentralized knowledge base over the course of it's evolution from the first alpha.
Unfortunately upon reading the Lunyr whitepaper and following their public materials I fail to see how they will pull off what they are promising. I do not think the current Ethereum can handle concurrency which probably would be necessary for doing AI. I also don't see how Ethereum would be able to do it securely with the current design although I remain optimistic about Casper. The lack of code on Github, the lack of references to their research, does not allow me to completely analyze their approach. I can see based on the fact that they are talking about a decentralized knowledge base that their approach will require more than the magic of the market combined with pretty marketing. They will require a knowledge representation language, they will require a true decentralized knowledge base built into IPFS. This true decentralized knowledge base will have to scale with IPFS and through this maybe they can achieve something but without a clear plan of action I would have to say that today I'm not confident in their approach or in Ethereum's ability to handle doing it efficiently.
Fuente / Source: Original post written by Dana Edwards. Published on Steemit: The value of Knowledge Representation and the Decentralized Knowledge Base for Artificial Intelligence (expert systems).
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Suggested readings to better understand the Tau ecosystem, Tau Meta Language, Tau-Chain and Agoras, and collaborate in the development of the project.
Lecturas sugeridas para entender mejor el ecosistema Tau, Tau Meta Lenguaje, Tau-Chain y Agoras, y colaborar en el desarrollo del proyecto.