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).
How Tauchain and the Exocortex can give anyone a conscience and make anyone more law abiding. By Dana Edwards. Posted on Steemit. September 2, 2018.
First "anyone" is not literal. By anyone I mean anyone with a reasonable level of intelligence who is willing to take the advice generated by the network. The network would include human beings and machines. The network would learn and be more properly defined as a complex adaptive system. Tauchain would enable the emergence of this network. This post is about how the network which can emerge from Tauchain. It is also about how people who intend to be as moral as possible whilst also complying with the law as much as possible might leverage the network. This post assumes that the human brain has a finite memory and comprehension capacity. This post assumes that every human being can benefit from enhancing these naturally limited capacities in areas of legal comprehension and risk literacy (under the assumption that most or perhaps none of us know every law on the books but need to comply with the laws most likely to be aggressively enforced).
The Personal Moral Assistant
PMA is a concept I've been thinking about for years now. The idea that we can augment our ability to be moral persons. A PMA is a personal moral assistant and in an ideal world every person born would have one. This would be an interface similar to what we see with Cortana or Siri where you can ask any question pertaining to whether a particular action is right or wrong. This PMA would solve the problem using the same priorities that you would and so you would get a definite right or wrong result.
A Personal Moral Assistant is just one primary use case. But these personal assistants over Tauchain could also include for instance a Personal Compliance Assistant. This is essentially another bot but instead of dealing with moral problems this bot would handle compliance. If you're trying to accomplish a goal this bot would make sure that you do so following all the known laws as your exocortex currently understands it. This would enable people to avoid legal pitfalls whilst chasing opportunities.
In order to go from poor to rich in this world requires taking risks. There is no way around risk taking if you want to get ahead. Risk literacy is essential and very few people who are poor have risk literacy. The PMA might be able to tell a person whether a certain choice aligns with their current values. The PCA might tell a person whether a certain choice complies with the laws. What about opportunities? An opportunity web crawler agent could theoretically search across the entire Internet to find opportunities which match your chosen risk profile.
What are we doing today?
Today we have to make choices often in trial and error. If we aren't lucky enough to have mentors or people who can guide us then the only way to learn is to make the common mistakes. When we deal with moral problems today we often rely on holy scripture interpreted by other human beings who are just as flawed as we are. We simply don't have a bot which could interpret the scripture in a completely logical way. In other words we don't have the digital representation of the mind of our spiritual guides.
We also have a situation where some of us can afford to comply with every law and take the lowest risk approach while others simply don't have the resources available to pay the expensive legal fees. Some people get better legal advice than other people as well. What if we could get at least some level of legal assistance from our intelligent assistant? What if this intelligent assistant can even ask human beings who have legal knowledge to help?
And finally what if we could figure out which risks are worth taking and which are not worth taking? It's one thing to find opportunities but another to be able to assess them. People get scammed because at the end of the day our emotions influence our ability to do proper assessment of opportunities. I'm human and it even happens to me from time to time. What if we could avoid this by using the capabilities of Tauchain to analyze massive amounts of information for us which our brains could never handle?
Opportunity Crawler Bot
I ask a simple hypothetical question: what if you could have set a bot to search the Internet for opportunities that resemble Bitcoin in 2008? What if this bot would be activated and search for an indefinite period of time on an undetermined yet expanding number of networks? If you define "Bitcoin in 2008" in a way which the bot can make sense of then it could search for anything which meets that criteria. We have this technology now but it's extremely primitive. On Google you can set up alerts for certain things but what if you could go beyond mere alerts and look for code on Github, and certain individuals involved with it, and certain growth patterns?
A way to think about these bots / intelligent assistants
One way to think about these intelligent assistants is as part of your extended mind. These bots essentially help you to think better and communicate better. It's still you and what they do on your behalf is essentially as if you did it. So the total collection of all of these agents which are under your control represent your complete exocortex. It will take great responsibility and wisdom to use these abilities in a way which is perceived by the world as ethical, moral, legal, etc. It is for these reasons that I initiate a discussion on how each of you would like to use such technology if it did exist or such bots or how you would think about them?
The power of ambiguity and of ambiguity minimization in communication. By Dana Edwards on Steemit. June 1, 2018.
Formal communication benefits from ambiguity minimization.
So what exactly do I mean by formal communication? Well when we think of how human beings communicate with machines it is in a formal language. This formal language requires minimized ambiguity for security analysis (how can we analyze code if we cannot effectively interpret it?). The other problem is that the machines require for example that if... then... else and similar conditional statements are well defined and unambiguous.
Is it possible to show that a grammar is unambiguous?
To show a grammar is unambiguous you have to argue that for each string in the language there is only one derivation tree. This is how it would be done theoretically speaking.
In computer science, an ambiguous grammar is a context-free grammar for which there exists a string that can have more than one leftmost derivation or parse tree, while an unambiguous grammar is a context-free grammar for which every valid string has a unique leftmost derivation or parse tree. Many languages admit both ambiguous and unambiguous grammars, while some languages admit only ambiguous grammars.
Specifically we know that deterministic context free grammars must be unambiguous. So we know unambiguous grammars exist. It appears the strategy is ambiguity minimization with regard to formal languages (such as computer programming languages).
For computer programming languages, the reference grammar is often ambiguous, due to issues such as the dangling else problem. If present, these ambiguities are generally resolved by adding precedence rules or other context-sensitive parsing rules, so the overall phrase grammar is unambiguous. The set of all parse trees for an ambiguous sentence is called a parse forest.
The parse forest is an important concept to note. All possible parse trees for an ambiguous sentence is called a "parse forest". This concept is key to understanding the strategy of ambiguity minimization. So we can in practice minimize ambiguity and we know for certain that deterministic context free grammars admit an unambiguous grammar but what does that mean? What are the benefits of unambiguous language in general?
A benefit of ambiguity minimization
Simple English is a form of controlled English designed to minimize ambiguity in English. This is important because by using simple English to codify the rules or write the laws it puts it in a language where there is less of a computational expense (in brain power) to process and interpret the statements.
In one of my older blogposts @omitaylor commented and in one of her future posts she asked about the topic of love. In specific her post was titled: "What Does LOVE Mean To YOU"
Her post highlights the fact that there are different love languages and that we don't all speak the same love language. Ambiguity here is actually not a good thing but the simple fact is when someone speaks about love how do we know they are talking about the same thing? As a result we often seek an agreed upon or formally defined "love concept" where we all agree it's love. This is not trivial to find and as a result a topic like love is not easy to discuss in any serious manner. Unambiguous communication or to be more precise (minimized ambiguity) would allow Alice to discuss with Bob the topic of love in a way where they both know exactly what the other is referring to in terms of behavioral expectations, emotions/feelings, etc.
If Alice agrees to love Bob then Bob has no way to determine what Alice means unless he and she agree on a mutually defined concept of love. This highlights how agreement requires very good communication and how minimizing ambiguity can be beneficial at least in this example.
Ambiguity minimization makes sense when you are following a principle of computational kindness. That is if Alice would like to reduce the computational burden on Bob then she can reduce or minimize the ambiguity of her sentence. This is because in order for Bob to interpret an ambiguous sentence Bob must in essence sort all possible interpretations of that sentence from most likely interpretation to least likely interpretation, and before he can even sort he must first search in order to find all possible or at least plausible interpretations.
This is very computationally expensive for Bob but very cheap for Alice. Alice knows exactly what she means but Bob has no clue what Alice REALLY means.
A benefit of ambiguity
There are other examples where increasing ambiguity could be beneficial, such as perhaps when the communication is less than formal, or to share a stream of consciousness without turning it into a formal communication. Humor for example rides on ambiguity and a good joke may have multiple layers. Art also leverages ambiguity because it's perhaps meant to be interpreted 20 different ways all to produce a certain desired affect.
Ambiguity allows more meaning to be packed into fewer words. This in a sense is a sort of compression scheme. So if a sentence has multiple possible meanings the levels or meanings are still finite. It's a fixed amount of meanings and so theoretically speaking a search can be conducted. In fact this is what a human being does when interpreting natural language where a sentence can have multiple meanings (they do a search for all possible interpretations of that sentence). The problem with this is that it is computationally expensive as a process at least for the human being to try to figure out all possible interpretations of a sentence.
Lawyers when they do their work are working with a specific knowledge base of common legal sentences and common interpretations known in their profession but the rest of us might see a sentence in lawyer-speak and not really know what it means because we will not know the common interpretations. This is a big problem of course because to form agreements between two parties both parties need to have a common understanding (a kind of knowledge symmetric understandability) allowing them both to interpret roughly the same sentence to mean the same thing.
“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 ).''
Masa. Masayoshi Son . The master of SoftBank . The Japanese national of Korean background  - really great achievement in this context! The individual with, I suspect, the biggest buying power in all the human spacetime combined. In the world and in the history.
Masa's business record is formidable. He's not just serial and parallel multi-billionaire but a multi-billionaires-breeder  - for example he's THE Jack Ma-backer, i.e. THE Alibaba-maker. And many others more ...
He's buying pieces of Google  ! $32b cash for ARM , undisclosed $b cash for Boston Dynamics . Et cetera. And Masa definitely knows what he's doing with these bits and pieces. What mosaic he's building with those chunks.
Masa has a vision. An yuuuge vision. Masa has a Vision Fund . So, visions fully backed. Backing is what distinguishes a vision from fantasy. SoftBank Vision Fund current minimum check size is $100m by the organization's own rules.
With >$100b shopping spree cash in pocket (and we talking cash, not lower liquidity assets), and an yuge vision the already yuge Vision Fund to get even yuuuger.  Cause - you know - trillions are the new billions (and it is not 'just inflation' but in absolute, shear power - productivity beats inflation ).
His vision on the philosophic level in a nutshell is Vernon Vinge's  , Hans Moravec's  , Raymond Kurzweil's  (and countless other's  ) ... SINGULARITY .
On pragmatic level it is as simple as it is ingenious  - the machinery productivity and production grows so immense that inevitably and soon its output/supply exceeds the cumulative human demand. The machines run out of market!
Solution? As obvious as the Frederick Pohl's Midas Plague (1954)  - machines doing business with machines  (- from about minute 09:00 of the vid onwards). Many orders of magnitude more machine-machine collaboration than all the possible machine-human, human-machine or human-human ones. Trillions and trillions of transhuman chips and bots doing business between each other.
And Masa not just advocates or evangelizes this vision behind his Vision - he does it. Now.
In the narrow-minded aspect it is just matter of (a little) time before Masa notices my precious Tau  and ET3  (which I told you I see as 1, not 2 - explanations to be delivered in future posts).
From wide-minded perspective ... Well...
Do you see what I see?
Chatbots porting into Tau.
Masa's chips or bots are into Moore's law  state of inevitability, e.g. doomed to cross the human scale barrier and to rush even further ahead. To even crack the human natural language code barrier and to do all what a human can do and more. (On human-machine-Tau-machine-human sandwiching architecture for direct use of the few megayears thin natural language wealth and even the few gigayears deep non-verbal communication capital - some other time in some other posts).
Machine-Tau-Machine is completely legitimate and unavoidable use and dev mode. Nothing can stop it. (Better Turing Test, anyone?)
In my previous post  I explained my understanding of the ingenuity of Ohad's approach towards the Moravec-hardness problem of the human condition  - the realization that it is a waste and side-tracking to follow dehumanizing pathways of creation of biomimetic cybernetic homunculi to mitigate the organic limited human specifications, BUT we use them - Tau is the way the problem to become the solution. We utilitify all the processing and algorithmic capital accumulated over billennia into what we call human.
Is the Tau way into a divergence course with the Masa way? No! Absolutely not.
To make chips or bots of > and >> x100 Einstein intellect is a huge collaborative effort. Machines alone - it'd take few billions of man-years to get there. Humans needed - to serve as the effort amplifier lever fulcrum 
Tau with its human-machine-human network topology makes collaboration - for first time ever - really a P2P  thing, with social diameter  of 1 or even <1 for each and every participant  no matter human or machine.
- Tau is Masa vision accelerator.
- Tau is the geodesic Agora  of all intellects imaginable, no matter 'natural' or 'artificial'.
NOTE: Ohad most probably will disagree with this vision of visions on visions of mine, but I dared to dare already anyways. Sorry, bro. It is of course, not an official Tau Team position.
 - https://en.wikipedia.org/wiki/Masayoshi_Son
 - https://en.wikipedia.org/wiki/SoftBank_Group
 - https://en.wikipedia.org/wiki/Koreans_in_Japan#Integration_into_Japanese_society
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.