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.
The Era of Signals and Changing Power Dynamics. By Dana Edwards. Posted on Steemit. October 8, 2018.
The world we live in is rapidly changing. For instance the #MeToo era has arrived. This new era shows us that any individual in any position in society can be brought down. It proves a point that many in the blockchain community may have known instinctively which is that any individual source of authority and or power can and may be removed from that position. Some people actively choose to seek to be in these positions of power for their own reasons and then some of these people abuse their positions of power. People who seek power for the wrong reasons and then abuse it are in my opinion a risk which positions of authority bring (which blockchain technology may help reduce).
What are signals and what is signalling theory?
Social desirability bias is a popular topic in academic circles. To explain:
In social science research, social desirability bias is a type of response bias that is the tendency of survey respondents to answer questions in a manner that will be viewed favorably by others. It can take the form of over-reporting "good behavior" or under-reporting "bad," or undesirable behavior. The tendency poses a serious problem with conducting research with self-reports, especially questionnaires. This bias interferes with the interpretation of average tendencies as well as individual differences.
People tend to want to be liked/loved. People when asked questions on a survey may feel pressured to answer the survey in a way which they think they will be viewed more favorably by others. In other words rather than answering in a manner which they truly think or feel they will assess how others might judge their response and then answer in a way which they think they will be judged more favorably.
A full video on this topic is below:
Social desirability bias is exactly why voting on platforms such as Steem will not work. When voting is public then most of the research seems to show that people will feel pressured to answer the question not in the way which they really believe or prefer but in the way which they think the whales want them to vote or prefer. In other words because on Steem the whales can reward (or punish) anyone who votes in ways which go against "political sensibilities" it is likely that social desirability bias applies particularly on DPOS style consensus platforms. If there are votes and the votes are not encrypted (secret) then we have no way to determine which votes are legitimate and which votes are the result of signalling (such as virtue signals).
For example when it was Trump vs Hillary the polls suggested Hillary would win. This is because there likely was social desirability bias which made it socially undesirable for anyone to admit they voted for Trump. As a result people who voted for Trump or who planned to vote for Trump may have said in public that they intended to vote for Hillary. Because the votes in the election are secret the people who may have seemed like loud Hillary supporters could have been secret Trump supporters in disguise.
In some of my previous posts I discuss signalling theory a bit more:
In these posts I have identified that behavior of individuals is shaped by how individuals think other individuals will think of their behaviors. This would apply to social desirability optimization which I'll label as adopting behaviors which provide the expected payoff of being rewarded with improved social desirability.
To provide clarity the definition of social desirability:
Social desirability is the tendency for research participants to attempt to act in ways that make them seem desirable to other people.
In other words people want to be liked. Likeability is a word I can use to simplify the concept of social desirability for readers. In the example with the 2016 election it is clear that supporters of Trump would risk a social stigma with severe social consequences if they came out in public support. This high cost of public support is why some believed that there were secret Trump supporters who were simply afraid of "losing face". In the most simple terms a person can talk red or talk blue depending on where the social stigma is.
One of the stunning conclusions I reached in my own research on this topic is that the increasing transparency leads to "preference falsification". That is a person who is talking blue while thinking red. If all speech is public (like it is on Steem) then there is the possibility that preference falsification is taking place.
Here is a video on the topic of preference falsification:
Why is this a major problem in the blockchain community? The evolutionary trajectory of a platform relies entirely on market preferences. If censorship exists and conformist pressures hinder true preference aggregation then the developers (and the community itself) will have no way of knowing which improvements to make or which changes would best satisfy the community.
What is leadership and what is the era of signals?
Before I attempt to discuss leadership I will first explain what I think leadership means and what it is. In my opinion the community must always come first. A person who is put into a leadership position is in my opinion in what I'll term "the seat of responsibility". This is in my opinion not an enviable position to be in but someone has to be in this position. For example a person who receives a security clearance is now in a position of heavy responsibility. The information which they protect is not their secrets but the nations secrets.
Leadership in my understanding is not about "being in power" but is about serving a community. To be in a "big seat" is to be in a position of responsibility to make decisions on behalf of a community which the chosen person must represent. In other words being in positions of responsibility is entirely about service and not about power. A representative in congress is not in a position of power but in a position to serve their constituents who put them in that position to represent their interests.
In my opinion to be a good leader is to be a great listener. The leader must listen to the community to find out what the community wants and or needs. The leader must listen to the community to determine what the community thinks is right or wrong. The leader then must offer solutions or proposals or policies which satisfies the requirements of the community. What matters more than who is in the seat is the seat itself. This means the Presidency itself matters more than who is in office. The positions themselves matter more than who is in them. Long after whomever is in these positions are gone there will be these positions to be filled. Any leader in any position is replaceable by someone else if they show failure to lead (whether it be a CEO, or a President of a country, or a lead developer, or any other kind of community leader).
In my understanding it is like chess where all pieces on the board can be in various positions. We know in chess that the pawn can become any piece on the board. The point with this analogy is that individuals in my opinion are not likely to remain the source of power in society. The source of power in society is increasingly becoming the community for better or for worse. According to me, to lead is to serve and to lead effectively is to serve effectively.
To accept a responsibility to serve (to lead) it is required to seek feedback from all whom the community servant represents. This does not require voting specifically but it does require under any circumstance a mechanism by which the community can give brutally honest feedback to the system itself. When I say the system itself I do not mean the feedback must go direction to those who serve the system but that the system must have a means of collecting data, analyzing data, and then informing those who can improve the system on which changes best would satisfy the needs of the community.
In my opinion this is a very data driven process. I do not think leaders can for example process big data using their brain power. This will require that they harness the power of machines (machine intelligence). There is also risk if all the processing is done by one company (such as Google) just as there is risk if all people rely on Facebook for the news and opinions. We can see that Facebook has the ability right or wrong to shape elections by deforming the news feed or by allowing certain fake profiles to interact on the site. We see that Facebook can ban crypto ads at will for example to enforce certain policies without taking any kind of poll from the community or the users for instance. We simply do not see any poll data from the users which indicated that the users were tired of seeing crypto ads.
Summary of thoughts on leadership:
Augmenting the wisdom of the community as a means of better governance
In a world where the community must decide what to do we have a situation where responsibility is increasingly diffuse. This means while it is true that the signature may come from the face of the community (if it is a human face) it is still the community which has to be capable of wisdom. The problem is most communities in the world do not become wiser as more join the community. A bigger community doesn't produce better policies by merely voting together. The problem is while most people have opinions it does not mean opinions are well informed or scientific or wise. The lack of wisdom in a community results in horrible (harmful) policies, over reactions, systemic bias, and more.
The conclusion I have reached so far is that in order to have better governance in an era where the community is the government it is a requirement that the community be wise. It's not enough to simply give the community unlimited power to shape the future without providing any capacity for the community to be wise or to do research or to solve problems. Voting in the sense we see in elections does not involve informed voters. Information supplied to voters is almost always sub par and voters are expected to trust "opinion leaders" and "opinion shapers" who tell them how to vote and why. Often disinformation shapes elections more than scientific evidence, facts, math, or reason.
As we build blockchain technology I think it is critical that we put great emphasis on data analytics. Data analytics will allow our leaders to make better decisions on our behalf. Blockchain technology will have to rely on data analytics to figure out potential wants and needs of it's participants, users, e-citizens, etc. At the same time private communication will be a necessity even if just to conduct surveys. The reason is people will not necessarily provide their real opinion in a survey which is completely transparent. The only solution I could find to the problem of preference falsification is privacy.
Most important of all is those who are put into positions of leadership are in trusted positions. This includes people who are moderators at forums, people who are lead developers, people who run exchanges. People who are in these positions have the responsibility to serve the blockchain community to the best of their ability. The abuse of these positions for personal power or personal gain is a violation of this trust and in these instances the community can and should select someone else for that position.
Bulbulia, J., & Sosis, R. (2011). Signalling theory and the evolution of religious cooperation. Religion, 41(3), 363-388.
Davis, W. L. (2004). Preference falsification in the economics profession. Econ Journal Watch, 1(2), 359.
Frank, R. H. (1996). The Political Economy of Preference Falsification: Timur Kuran's Private Truths, Public Lies. Journal of Economic Literature, 34(1), 115-123.
Grimm, P. (2010). Social desirability bias. Wiley international encyclopedia of marketing.
Sîrbu, A., Loreto, V., Servedio, V. D., & Tria, F. (2017). Opinion dynamics: models, extensions and external effects. In Participatory Sensing, Opinions and Collective Awareness (pp. 363-401). Springer, Cham.
Let's use Tauchain to save our own lives and the lives of others: The life saving potential of Tauchain. By Dana Edwards. Posted on Steemit. September 10, 2018.
In this post I'm going to discuss what I think is one of the main reasons why I want Tauchain to exist. This is a reason I think many or perhaps most people can relate to. It starts with the question of how can we save our own lives using our own effort? It evolves into the question of how can we save lives in general by augmenting our efforts as much as technologically feasible?
1 out of 2 (around 50%) will be diagnosed with invasive cancer
The current statistics reveal that the highest scale we have a 50% chance of developing cancer in our life time. This can be lower according to some recent statistics (closer to 30% or in some cases 40% but still this is very high). The fact is if we are each in a room then about 1 out of every 3 of us in the best case will get cancer someday. And 100% of us will know someone who has cancer someday. So there is a very high chance that someone we care about a lot will develop cancer and do we want to be in a position where we didn't do all we could to have a capability of saving their life? It could even be you who developers cancer and would you want to be in the position where you can say you dedicated some of your resources toward finding a cure?
Cancer is one of those global problems that most human beings want to eradicate. It is not politically controversial to want to cure cancer. It is also something that Tauchain can help with because using Tauchain we can scale discussions, define problems in a precise manner, and most importantly leverage the market. The ability to create markets which are smart (meaning which can adapt to regulatory obstacles) is a potentially unique feature of Tauchain.
Some might say that there are already pharmaceutical companies trying to cure cancer or develop anti-aging treatments. Indeed this is true there are these companies. The problem right now is these companies do not have the new business models which Tauchain might make possible. First is the fact that using an ICO you can let future patients/customers own shares in the company. This allows companies which want to create cures to have the potential to raise billions of dollars necessary to do expensive trials. In addition the ability to do research may improve due to the features of Tauchain as well so that it is cheaper to search for new potential drugs or supplements.
The human genome is very complicated and is an area we know very little about. Cancer is also something we have to study. One example of an approach to defeating cancer is immunotherapy but this again is going to require a lot of research into how to reprogram the immune system to identify and destroy cancer. If everyone can help or contribute in some way to the process then it makes the process much cheaper than it is right now which means the drug or treatment can potentially be cheaper due to lower R&D cost.
Most people want to live long and healthy lives but we still know very little
We know very little about aging. We do have some theories as to what causes aging. We even have some theories on how to slow it down. But we don't understand the mechanism well enough yet to develop a treatment. By aging I'm referring to the process by which cellular function deteriorates over time. We know for example the risk of getting cancer increases with age. But we still are working on the means of developing biomarkers to even determine the age of a person.
What if we could leverage the potential of Tauchain to discover more about the aging process? What if we could develop an anti aging pill or treatment which we could collaboratively develop and own? What if we could make a profit from every pill sold via tokenization? If this sounds good to you then it might sound good to millions of others who could be encouraged to participate in an ICO to develop a pill to slow or supplement the aging process.
The ethical and rational argument
Some people could say that to put an emphasis on saving lives is to seek to do the greatest good for the greatest number. This emphasis could put Tauchain on a fast track to mainstream adoption because utility would be measured in not just how profitable it is to hold a token but in the potential lives that could be saved. To profit from saving lives is an ethical and rational argument. To align the profit motive with saving as many lives as possible is an easy ethical (and rational) argument to make. People who value life will value any technology which saves lives.
Some projects exist which I will list below that already are trying to save lives or end aging. These projects did ICOs over Ethereum and so they currently are Ethereum focused. That being said there is the possibility that some projects could still leverage Tauchain regardless of whether they originally launched on Ethereum. It is also possible that new projects can launch on Tauchain to attempt the same or similar objectives.
What can Tauchain do?
Grunau, G. L., Gueron, S., Pornov, B., & Linn, S. (2018). The Risk of Cancer Might be Lower Than We Think. Alternatives to Lifetime Risk Estimates. Rambam Maimonides medical journal, 9(1).
“A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.”
― Robert A. Heinlein 
No, it is not a vow everybody to be everything. It is a reflection of the fundamental human fungibility . The average human can be taught to take any human role. The exceptions of true organic geniuses (those who are hard to be replaced) and morons (those who are incapable to replace), only confirm this general rule of shear numbers . This is what makes the mankind so scalable .
''Know'' is synonymous with ''can''. Literally. Knowledge = technology. Even etymologically . Knowledge is praxis . Only. There ain't such thing as impractical knowledge. If it is not a skill, it is not knowledge. I mentioned once  that we're all AIs. Ref.: feral children .
We are not what we eat , but we are what we've learnt. You are what you know/can. And you can what you have learnt. Learning is from the taking side. Teaching is on the giving side. Of one and a same process. We do not have a word to denote the modulus  of learning/teaching, it seems. But it will come.
We are taught by the others, the society. We are the cherry ontop of a layer cake of culture onto nature . We are learning by ... living. We acquire skills in plethora of contexts from family, street, school, job, media ... Learning  is not a monopoly of man, countless systems are also learners. Maybe one of the basic definitions of life and intelligence is the ability to learn . Giant topic, yeah. We won't graze into it here now on what is learning, but on how we learn.
Due to our neurological bottlenecks we spontaneously form hierarchies . This hinders our scalabilty  by forcing humanity to be more or less a fractal of 5. We are close to a number of breakthroughs which to mitigate these innate limitations of ours into a number of ways    . But the general case is not subject of this article - herein we focus on HOW we are taught. How we acquire knowledge, and how this knowledge of ours gets recognized and utilized by society. And the hierarchic emergent structuring is of course in full force upon us in teaching as well as into everything social else.
So comes education , such comes exam , knowledge certification , certified skills application , knowledge creation verification , job fitness testing , CVs and employer recommendations ... etc., etc. With all the bugs and the so little features of this 'map is not the territory' , situation.
It is all centralized and hierarchic - exactly as the global fractal of double-entry accountancy ledgers which we call fiat financial system is. In fact it is so interwoven with fiat finance than it is almost inextricable from it . And as much inefficient and imprecise.
In all these years of talking and thinking on Tauchain  - I noticed - and this suspicion of mine incrementally turns into shear conviction - that Tau, the upscaler of humanity, inevitably also is the ultimate teaching machine. If education is facilitating of learning, Tau is the maximizer of learning. By its very construction, it comes out so.
People talk and listen whenever and whatever they want. Tau has unlimited capacity to listen and attend and remember, and answer. Only limited by the hardware capacity allocated. Tau extracts meaning. Purifies the stream, distills it down to the essence. Detects repetitions, contradictions and all other, ubiquitous nowadays conversation bugs. Remembers changes of opinions of the individual user. And points them out. Sounds like the best tool to know oneself. And the others to know you if you let them.
Your Tau account or profile is what you know. You say what you say and also ask. Say statements and questions. Tau pools you together with the others who state the same and, more importantly, who ask the same type of questions. Knowing what you know, and asking about what you don't know but want to know, maps not only your knowledge state but also maps your knowledge dynamics. Records and drives how your knowledge changes. You even have access to what you forget, and can recollect it. True real time knowledge state reporting. For first time in human history.
If consciousness  is - aside from the clinical state of being merely awake - the post-factum integration of senso-motoric experience , the Accountant of mind, the speaker of the narrative which is you, then Tau is your consciousness booster. That is - stronger than thought.
The ultimate teaching, the ultimate fair testing or exam, the ultimate real-time comprehensive diploma, or certificate, super-peer reviewed paper(s) of you as academic carrer.., the ultimate job interview AND the ultimate ... job of being working as yourself and anything useful you create to be instantly scarcifiable and monetizable - your Tau account is! And all the rest of accessible socoety - being your own workforce. And you to them. In the billions. In a move. In real time.
Including control over the pathways of increase of your skills towards the most productive personally for you learning directions, because it aids you to analyze the you-Tau history and to apply knowledge maximizer techniques and to participate profitably into creation of newer better ones. Maximizer of self. And maximizer of society making it to consist of max-selfs. Ever improving. Merger of education with work occupation. Work-as-you-live.
The literal Knowledge Economy, as described by @trafalgar in his article  from few months ago. Where search, creation, reflection, certification, recognition, commercialization, accumulation, modification, improvement ... everything of knowledge - is all in one.
And it is not only Humans and Tau lonely job. I foresee the other Machines to join the party . Yes, I mean machines capable to have interests and to ask and seek answers of palatable questions.
This - the education amplification - to come down the technology way - has been, of course, anticipated by many. Few arbitrary examples:
- A distant rough-sketch hint for the inevitable tuition power of Tau is Neil Stephenson's  ''The Diamond age''  , with the depicted: '' Or, A Young Lady's Illustrated Primer '' , as an interactive networked teaching device.
- or if I'm right about the inevitable conquest of the natural languages territory  - UX  like in the 'Her' (2013) film .
- Thomas Frey  of the futurist DaVinci Institute  in his book ''Epiphany Z''  paid special attention of this.: down the way of micro- and nano-education, an effective merger of the processes of education, diplomas issuing, job application, exam and actual execution of job obligations. Tom does not know about Tau. But I'll tell him.
With a big smile of irony and self-irony of course... these examples. Just to pick from here and there proofs of the giant anticipation of what's to come. And taken with a few big grains of salt. Cause the reality will be immensely more powerful.
Tutor , tuition , my emphasis via using exactly this wording, comes to denote the economic side of learning/teaching. It is about the cost of learning - the association of tuition with fees, about the placement of the acquired skills, about the business organization of those, about the protection of ownership and security of transaction of knowledge ... Let me introduce here a neologism  which to reflect the business side of it:
Scrooge Factor 
- Simply denoting the money-making power of a technology use by a business. The 'money suction power' of a business entity or organization of any kind coming from the application of a technology, if you want. Technology as socialized knowledge. Scaled up over multiple humans. Over a society. Of course the Scrooge Factor can pump in different directions. The Scrooge Factor of the traditional hierarchic education, governance and everything ... is apparently very often negative - hierarchies decapitalize, dissipate, waste. Orders of magnitude more wasteful than any PoW , but on this - some other time.
So aside from all the niceties of the abstractions of the full supply and value chains of a Knowledge economy, lets round up some numbers:
- We know that a true functional semantic search engine alone is worth $10t. Yeah. Tens of Trills. Trillions. As per the assessments of Davos WEF attendees of as far as I remember 2015 or 2016...
- Also, Bill Gates stated back in 2004  that ''If you invent a breakthrough in artificial intelligence, so machines can learn,'' Mr. Gates responded, ''that is worth 10 Microsofts.''
- Tom Frey  also argued  that by 2030 the biggest corporation in the world will be an online school. Given the present day size and growth rate  of, say, Amazon  this 'online school' should be in the range of good deal of trillions of marcap if it is to be bigger than the biggest corporations. But we do not need such indirect analogies over analogies to access the scale. The shear size of the global education industry is the most eloquent indicator . Note that Tom talks about 'corporation' i.e. for clumsy and inefficient hierarchic human collective. Not for a system which does this orders of magnitude more efficiently and powerfully due to being intrinsically P2P, i.e. geodesic . Even the best futurologists can be forgiven for missing to predict Tau. :)
And this mind-boggling hail of trillions, does not even account for the Hanson Engine  factor.
Tau the Tutor ex Machina is just another unintended useful consequence outta the overall design.
It is nearly impossible to track and contemplate exactly what all these 'side-effects' would be and how they will synergetically boost each other.
With my articles I intend to only touch some lines of the immense phase space  of the possibilia, with neither any ambition to think it is possible to cover it all, nor this to represent any form of advice.
Future is incompressible. Compression is comprehension. Comprehensible only by living.
Failure to go to the geodesic way of learning, will turn these beautiful but trilling words into prophecy:
"The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents. We live on a placid island of ignorance in the midst of black seas of infinity, and it was not meant that we should voyage far. The sciences, each straining in its own direction, have hitherto harmed us little; but some day the piecing together of dissociated knowledge will open up such terrifying vistas of reality, and of our frightful position therein, that we shall either go mad from the revelation or flee from the deadly light into the peace and safety of a new dark age." H.P.Lovecraft  (1926 ).''
To zoom out is useful. It puts the events networks of our spacetime in perspective. Including on what the great Jorje Luis Borges was calling the Orbis Tertius :
''ORBIS TERTIUS. "Tertius" (Latin = third) is an allusion to: World 3: the world of the products of the human mind, defined by Karl Popper.''
Poetically stated, ''retrodiction studies'' , ,  enables us to get a glimpse on the "clear, cold lines of eternity".
Back in 20th century Prof Robin Hanson put together this extremely insightful and strong document .
Long-Term Growth As A Sequence of Exponential Modes,
Economy grows. [see: Footnote]. Unstoppable.
Hanson's unprecedented contribution was to provide us with systematic orientation tool on how and why economy grows.
It accelerates. See:
Mode Doubling Date Began Doubles Doubles Transition
Grows Time (DT) To Dominate of DT of WP CES Power
---------- --------- ----------- ------ ------- ----------
Brain size 34M yrs 550M B.C. ? "16" ?
Hunters 224K yrs 2000K B.C. 7.3 8.9 ?
Farmers 909 yrs 4856 B.C. 7.9 7.6 2.4
Industry 6.3 yrs 2020 A.D. 7.2 >9.2 0.094
The model identifies the past economy accelerators as.:
- neural networks, evolving into doubling brain size each 30-ish megayears (hinting that human level of intelligence is an inevitability: +/-30 millions of year around the Now, by the virtue of the good old 'coin-toss' Darwinian algorithm alone.)
- human as the top-of-the-foodchains predator since around 2 000 000 BC. (maybe the human mastering of the Fire and the Blade to blame), compressing the doubling time with over two orders of magnitude down to a quarter of a million of years.
- Food production, ecosystem manipulation (or rather the collimation of farming, horse domestication and writing as accelerator components), leading to less than 40 human generations per economy doubling.
- All we know as division of labor, specialization, systematized Sci-Tech... industry - the centralized ways for production and control of knowledge leading to another hundreds-fold compression down to mere ~decade of economy doubling time.
Recommended: digest each Hanson (economy accelerator drive or) Engine with the Bob Hettinga's 'ensime' :
My observation about networks in general is a rather obvious one when you think about it: our social structures map to our communication structures. As intuitive as it is to understand, this observation provides great insight into where the technology of computer assisted communication will take us in the years ahead.
Connectivity specs as indicator and drive.
Now, when we leave the past and use these models to gaze into the future, the really interesting stuff comes out.
Aside from giving explanation to the, detected by Brad DeLong in his also monumental paper , overall trajectory of the economy, the nucleus of meaning in the Rob Hanson's paper is:
Typically, the economy is dominated by one particular mode of economic growth, which produces a constant growth rate. While there are often economic processes which grow exponentially at a rate much faster than that of the economy as a whole, such processes almost always slow down as they become limited by the size of the total economy. Very rarely, however, a faster process reforms the economy so fundamentally that overall economic growth rates accelerate to track this new process. The economy might then be thought of as composed of an old sector and a new sector, a new sector which continues to grow at its same speed even when it comes to dominate the economy.
Visualize: a Petri dish and sugar being expanded in size and quantity by the accelerating growth of the bacterial culture in it.
Hanson actually predicted nearly quarter of century ago, ... something that is relentlessly coming.
In the CES model (which this author prefers) if the next number of doubles of DT were the same as one of the last three DT doubles, the next doubling time would be ... 1.3, 2.1, or 2.3 weeks. This suggests a remarkably precise estimate of an amazingly fast growth rate. ... it seems hard to escape the conclusion that the world economy will likely see a very dramatic change within the next century, to a new economic growth mode with a doubling time perhaps as short as two weeks.
An economy accelerator avalanche is roaring down the slope of time towards us.
A brand new Hanson Engine is about to leave the assembly line.
Tau, is that you?
FOOTNOTE: To wrap up the above statements in the flesh of the deep thesaurus of content onto which they lie, would conservatively consume hundreds of pages. Even if only briefed. I promise to come back to these subtopic meaning expansions (by referring back to here) with series of posts in the months to come to tie up with the notions of.: economy as a network, network as computer, what exactly it processes and outputs, economy (like the universe or life) being endogenously driven positive feedback loop self-amplifying non-equilibrium entropic combinatorial explosion system, the wealth as economy complexity growth in relation with GDP size and the intimate connection of dollars-joules in energy intensity, physical and economic limits of growth, self-reinforcing predator-pray models, knowledge as synonymous with skill and so forth, economic cycles upon the DeLong curve ... to name a few. Readers questions and comments will of course help a lot with the subtopics prioritization, and will boost (incl. mine) understanding. Thank you in advance!
NOTE: I currently have the pleasure and honor to be part of the Tau Team, but this post contains ONLY my personal views.
Ohad Asor the lead developer and founder of Tauchain releases first new blog post in over a year. By Dana Edwards. Posted on Steemit. December 30, 2017.
The new blog post titled "The New Tau" is available for everyone to read. The blog post speaks on the critical topic of collaborative decision making. This is a topic which I myself have been interested in and Ohad's solution is different from the usual solution. In my own thinking I was considering a solution based on collaborative filtering but I realized this would never scale. I then considered a solution based upon using IA (intelligence amplification) by way of personal preference agents and this does scale but requires that the agents have a lot of data to truly know each user and their preferences. The solution Ohad Asor comes up with attempts to solve many of the same problems but his solution scales without seeming to require collaborative filtering or any kind of voting as we traditionally think about it.
Let me list some of the obvious problems with voting which many will recognize from Steem which also relies on collaborative filtering:
Now let's see what Ohad Asor has to say:
In small groups and everyday life we usually don't vote but express our opinions, sometimes discuss them, and the agreement or disagreement or opinions map arises from the situation. But on large communities, like a country, we can only think of everyone having a right to vote to some limited number of proposals. We reach those few proposals using hierarchical (rather decentralized) processes, in the good case, in which everyone has some right to propose but the opinions flow through certain pipes and reach the voting stage almost empty from the vast information gathered in the process. Yet, we don't even dare to imagine an equal right to propose just like an equal right to vote, for everyone, in a way that can actually work. Indeed how can that work, how can a voter go over equally-weighted one million proposals every day?
This in my opinion is very true. In reality we have discussions and at best we seek to broadcast or share our intentions. Intent casting was actually the basis behind how I thought to solve this problem of social choice but I would say intent casting even with my best ideas would not have been good enough because again the typical voter would be uninformed. Without an ability of the typical voter to be either educated continuously which in a complex world may be unrealistic, or for the network itself to somehow keep the voter up to date, this intent casting barely works. It works well for shopping where a shopper knows what they want but does not work so well when a person doesn't actually know what they want and merely knows what they value. Values are the basis for morality, for ethical systems, and this is the area where Ohad's solution really shines.
Tauchain has the potential not only to scale discussions but also morality, because it will have the built in logic to make sure people can be moral without constant contradiction. The truth is, without this aid, the human being cannot actually be moral in decision making in my opinion due to the inability to avoid all sorts of contradictions.
All known methods of discussions so far suffer from very poor scaling. Twice more participants is rarely twice the information gain, and when the group is too big (even few dozens), twice more participants may even reduce the overall gain into half and below, not just to not improve it times two.
This is the conclusion that Ohad and myself reached separately but it still holds true. We require the aid of machines in order to scale collaborative decision making. This in my opinion is one of the major difference makers philosophically speaking between the intended design and function of Tauchain vs every other crypto platform in development. This also in my opinion is going to be the difference maker for the community which Tauchain as a technology will serve because it will enable the machines and humans to aid each other for mutual benefit or symbiosis.
The blog post by Ohad Asor brings forward a very important discussion which has many different angles to it. The angle I focused on with regard to the social choice dilemma is the problem of how do we scale morality. In my opinion if we can scale morality in a decentralized, open source, truly significant manner, then nothing stands in the way of absolute legitimacy, mainstream adoption, and with it a very high yet fairly priced token. The utility value of scaling morality in my opinion is higher than just about anything else we can accomplish with crypto tech and AI. If the morality is better, then the design of future platforms will be greatly improved in terms of how the users are treated, and this in itself could at least in my opinion help solve the debate about whether AI can remain beneficial over a long period of time. I think if we can scale morality in a decentralized way, it will make it easier to design and spread beneficial AI. Crypto-effective alturism could become a new thing if we can solve the deeper more philosophical problems.
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.