AI Concern: ‘Prometheus Doctrine’ Revisited – Nick Bostrom (Part 1 of 2)
I’m referring to the men and women who, as this video exemplifies, subscribe to a sort of ‘Prometheus Doctrine’; which for me is like a fetish of needing to destroy in order to create. They talk about their fear and project their fear onto and into our science and technology instead of quelling the sources of that fear from the very beginning. The source of their fear IS preventable!
If we were advancing technology for the right reasons and using the right means, we wouldn’t have anything to fear! The ‘snake’, through guilt and even ‘karma’, calls forth its own destruction and even begins to eat itself!
Also, the video literally reeks of the disdain and disregard (contempt) for humanity and the impetuousness of a science running amok (without morals and ethics) that has become the fashion in our mainstream trendy pabulum which premature globalist social engineering has created for our consumption. All branches of the human endeavour have been infected or affected by this social engineering in some way.
At university our youth is being incrementaly infected (radicalised) by this ‘bug’ of disdain and we should all be aware of it before it becomes our undoing! You see it when you ask them to consider the ramifications of the science and technology being created now, and they respond with “You’d better get used to it, because that’s the way it is.” It resembles the ‘bitch’ meme that is pervasive in the ‘prison culture’ social engineering I’ve been referring to above.
Their callous and impetuous response is paired with a complete wilful ignorance of the consequences of what science and technology (and their steady weaponisation) are doing or potentially can do to our home here on planet Earth as well as to ourselves. The social engineers will have us worrying about how our free speech may adversely affect others and therewith attempt to quell debate by means of political correctness (PC).
The youth of humanity has been abused by this kind of thing since at least the late 18th Century, because it is widely known (and not spoken of) that they, with rare exception, are not yet able to compete intellectually with adults. Adolescents sense this, which exacerbates their normal impetuousness, so they attempt to compensate for this perceived deficit by ‘attaching’ themselves to some any deeper perspectives they are introduced to. The mainstream ‘trendy’ has been ‘weaponised’ so these are usually various destructive lines of thinking (Communism, Satanism,…). They are provided with a narrow, but sometimes deep understanding by simply taking on these lines of thought with their peers. By doing this, they may well even surpass the understanding of the adults around them, but the knowledge imprint only stands out like a wart. This can be recognised, because the corresponding hallmark lines of development in wisdom and insight, that always accompany and provide a context for that knowledge, are absent.
The parasites perched upon humanity know this. That’s why they want our children so soon and so long. Students literally get ‘caught in the headlights’ of the teachers and professors, who are themselves victims of this incrementalism. The controllers can then direct this lack of experience and wisdom (naivety) against the rest of the population by indoctrinating our youth into zealots.
BTW: This post is not here to ridicule nor ostracise anyone! It is intended to wake everyone up! In the end we are ALL being manipulated (including Nick Bostrom) by the corporations who are controlling and transforming our science, education, media, governance,… I’ve had to delete comments below from disrespectful people who now want to criticize Nick Bostrom personally. I will not have that here!
This writing is not a criticism of Nick Bostrom, rather a criticism of the education system and science that subtly ‘fashions’ how we ourselves as well as our youth and those directly involved (including Mr. Bostrom) see themselves through science, philosophy, mathematics, and the arts; in fact, nearly all of the human endeavour has been infected or affected by it.
@00:31 “Okay, let’s look at the modern human condition…”
He shows a ‘doctored’ image of a man wearing glasses with his eye size increased to almost fill the lenses. I find myself asking myself if he is referring to the “I work with a bunch of mathematicians, philosophers, and computer scientists…” he talks about here?:@00:11
It sure isn’t clear of who he’s referring to with his ‘human condition’! Here is our first indication of the disrespect for humanity his action here reveals. He seems not to have considered or known that this very condition of humanity that he’s making light of for his audience Is, in fact, a result of the very science he represents!
When I see an image of someone who looks as in this image I think of Pavlov or B.F. Skinner with their ‘contributions’ to humanity (weaponized social engineering)! I ask myself why he chose this image particularly and not another that would have been as funny, but not so unforgiving of humans who have bought into the social engineering they’ve been subjected to?
@00:43 “We are recently arrived ‘guests’ on this planet.”
We are the living Earth! We are as much a part of this planet as anything else living on/in/above it. We are NOT guests on this planet, it’s our home!
@00:49 “Think about the world was created… the Earth was created one year ago.”
I find it interesting that he uses the word ‘created’ instead saying something like ‘formed itself’ or ‘accrued its main composition’. It’s almost the model that Carl Sagan offered in his Cosmos Series and elsewhere, but doesn’t quite ring as true.
@01:07–He uses a graph depicting GDP (Gross Domestic Product) to make statements about societal changes over thousands of years! This is not only wrong, the metrics don’t even correlate with each other! (Notice how the people laugh? I wonder how many of them really know what they’re laughing at?)
@00:37-[regarding technology] “That’s why we are so productive.”
We have always been productive. Technology is nothing new. [Which he acknowledges!] Even the militarization of technology isn’t new. He refers to some [ap]proximate cost idea he doesn’t explain nor provide a context for. Technology contains both potential and real costs and returns in many terms (social, cultural, personal,…), for the record. This has not changed over time.
@01:43 “We have to move back farther… to the ultimate costs.”
He then introduces two “highly distinguished gentlemen”: Kanzi and Ed Witten. I dispute his choice of examples to go with, as Nassim Haramein http://resonance.is/ or Nikola Tesla would have been better choices from where I stand, but he didn’t ask me, did he? 😉
I wonder what we’ll be saying about Super-string and M-Theory in 100 years? I doubt seriously it will stand the test of time as the theories are almost certainly wrong.
@01:57 “If we look under the ‘hood’, this is what we find. Basically the same thing. [!]… one is a little larger. It maybe also have a few tricks in the way that it’s wired… These invisible differences cannot be too complicated; however, because there have only[!] been more than 250,000 generations since our last common ancestor and we know that complicated mechanisms take a long time to evolve.”
I guess that’s the reason the apes didn’t get very far?!?! Or what am I to make of this proposition? At some crucial juncture in the past the apes simply decided to turn left instead of right? Or did we? In any case he doesn’t reveal to us exactly what those ‘invisible differences’ may be.
@02:21 “So a bunch of relatively minor changes take us from Kanzi to Witten.”
Still no mention of what the changes are and I still don’t see why Kanzi isn’t writing Haiku!
@02:33 “So this then seems pretty obvious that everything we have achieved pretty much and everything we care about depends crucially on some relatively minor changes that made the human mind.”
He provides no basis for that statement and moves on to a corollary without even explaining this massive jump from somewhere around the time of a common ancestor to what the human mind has become!
@02:43 “And the corollary of course, is that any further changes that could significantly change the substrate of thinking could have potentially enormous consequences”
Wait just one minute! There has been no justification for the prior proposition, not to mention a justifiable connection it may have to some ‘substrate of thought’! Having a common phylogenic ancestor who has mastered over 200 lexical tokens is nothing compared to the subtlety and sophistication of the human mind!
@02:55 “Some of my colleges think that we are on the verge of something that could cause a profound change in that substrate… and that is machine super-intelligence. Artificial intelligence used to be…”
So what does this mean? Are we now entering an age of ‘post-artificial intelligence’? A sort of neo-AI? Could you also tell me more about that ‘substrate’?
@03:29 “Today the action is really around machine learning. Rather than hand-crafting knowledge representations and features we create algorithms that learn…”
Here he’s getting into an area he seems uncomfortable with. I suspect, for myself, one reason why. He is revealing that he’s never seen nor been a part of building a knowledge representation that was completely satisfying to those who made it!
It further reveals that he’s working without one or doesn’t trust any philosophy of knowledge or mind as a basis for the scientific methods he’s been involved with! A set of underlying philosophies of mind, language, and knowledge are absolutely required!
These facts are verified a bit later…@04:05 “Now of course AI is still nowhere near having the same powerful cross-domain ability to learn and plan as a human being has.”
He then reveals that he’s also locked into the brain-based-model of mind that is reminiscent of the adherence to phrenology in the early to middle 19th Century.
He then asks how far are we in being able to match those tricks. This leads him to mention a survey of some of the leading AI experts on just when we will likely reach a stage of human ability. Answers ranged from 2040 to 2050 (with estimates of 90% at around 2070/2075!!!).
@05:01 “The truth is, no one really knows.”
And they won’t know either, because they aren’t allowing all that is required for ‘intelligence’ to be included into the endeavour. I firmly believe that our current scientists will regret this phase of their history. Their names are on the line for the conceptual barren land they have created for themselves and are selling to us. They are not even doing themselves a favour; rather, are doing the corporations which pay them one!
The corporations and the banksters which run them who stand above the law are those who profit from this ‘science’, because it provides them with thin veils of plausibility to divert huge sums of money, minds, and other resources towards aims that few of us would ever allow if we knew them.
@05:05 “What we do know is that the ultimate limits to information processing in machine substrate lie far outside the limits in biological tissue.”
It seems we have now moved from ‘thinking substrate’ to ‘machine substrate’ without ever knowing what these terms mean. How can he know this? We haven’t even developed a successful philosophy of mind yet! There are many aspects of knowing, feeling, thinking, learning,… in organic intelligence that we have yet to understand.
@05:15 “This comes down to physics.”
He then compares the latest hardware (transistors) with neurons and means to show that these differences are meaningful in making the determination above and sticks with the size limitations of our brains being a size limitation for mind (again as if the mind were limited to the brain!)…
Note also that he is referring to information processing! If he had a decent set of knowledge representations to review, he would know that those tiny little neurons are not ‘transistors’ for the mind. There’s much going on in the mind for which the physical brain cannot give an answer! He is essentially attempting to compare apples and oranges with each other with an incomplete understanding what the apples are made of.
@05:47 “So the potential for super-intelligence kind of lies dormant in matter like much like the power of the atom lie dormant throughout history… patiently waiting there until 1945.”
Atoms did quite well, actually, before we learned how they work and began to make destructive use of the energy that comprises them. We certainly didn’t liberate them; rather, learned how to break them!
He then shows a picture of an hydrogen bomb blast and says @05:59*“In this century scientists may learn to awaken the power of artificial intelligence… and I think we might then see an intelligence explosion.”
This begs the question of what intelligence is! Also, it is unclear what aspects is he referring to: logic, abstract thought, understanding, self-awareness, communication, learning, knowledge, memory, creativity, problem solving,…? Later he tries to clarify this, but in so doing confuses the issue more.
Also there seems to be confusion here about the kind of intelligence (if we now pretend to have defined that term) would be that will have arisen. I’ll return to this later.
@06:10 “Now most people when they think about what is smart and what is dumb I think have in mind a picture roughly like this:”
and shows @06:15 a line (which is actually a distribution, but no one notices) with a “Village idiot” (using his terms) on the low end and Ed Witten on the the high end and a line stretching across between them.
It appears to be about knowledge of physics, because of Ed Witten being on it and how he then refers to what could have been Albert Einstein or any other favourite “Guru” we may want to choose. I wonder how this distribution would have ended up if he were to have measured empathy, situational awareness, or the knowledge of how the work your doing is being used for purposes other than good?
Where would Ed Witten, Albert Einstein, anyone of our choosing, or the village idiot then be found in the distribution. There are many kinds of ‘intelligence’ that are not even being considered here.
Notice how this distribution then magically transforms itself into an evolutionary path (which even appears to contain logarithmic/exponential value, as well). At least he has the village idiot higher on the scale than a chimp! I was almost expecting Kanzi to be somewhere in the middle of the distribution that the line represented before.
And then he says at @07:07 “The train doesn’t stop at ‘Humanville station’…”
This is more of that disdain I referred to above and will return to later in this post.
@07:11 “It’s likely rather to ‘swoosh’ right by.”
He doesn’t tell us why this will happen, but I suppose we will simply be surpassed by ‘somebody’ who’s got a bigger place to put his ‘brains’ in? That seems to be where this is heading…
@07:14 “Now this has profound implications particularly when it comes to questions of power.”
He compares the purely physical strength between a chimpanzee and a human (as if that were the only metric!) and uses that to transition us to accept his further propositions when he compares us to some kind of AI.
@07:27 “… and yet the fate of Kanzi and his pals depends a lot more on what we humans do than what the chimpanzees do themselves.”
So by analogy, this will also be true of ‘super-intelligence’ with respect to humans. We are expected to simply accept this analogy by ignoring (or here in this audience, not caring perhaps) the multitude of domains that influence and even determine the validity of the comparison!
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And now we come to the middle of time in the presentation and the most provocative and humanly egocentric propositions made in the whole talk..
@07:43 “Think about it. Machine intelligence is the last invention that humanity will ever need to make.”
He has no standing to make this claim. He nor anyone else can know what new way of looking at our world may come. NONE of us can truthfully say we have/know all of the ‘variables’ and ‘dimensions’ to our universe. We have barely begun to scratch the surface in all of our endeavours and therefore, have no right to make claims like these.
Yet it gets even more insane, because he then yields humanity to the proverbial ‘chopping block’ of evolution:
@07:49 “The machines will be better at inventing than we are and they will be doing so on digital time scales.”
What kind of education would create these kinds of propositions?
Why do we stand for this? He’s obviously a highly intelligent human being. How can he have fallen for this kind of artificial relation of our place in the universe. We are likely not the only planet with intelligent life either!
We don’t even know enough about the creative process to explain away God, not to mention explaining punctuated evolution! And I’ve not even referred to the discovery process yet as an additional criterion for intelligence.
This is where the inherent disdain for humanity contained within our hijacked science and technology best reveals itself. It has poisoned some of the most brilliant minds of our children like we see here. He makes these naive claims and doesn’t even realize the measure of his presumption whilst doing so.
Even the remark about digital time scales is naive. We don’t know enough about the depth and subtlety of the concepts such as time (temporality) nor scaling (proportion) to make any of these claims.
There are other ways of looking at these rich concepts that could transform our view of what we think or presume to know and even how we see ourselves in light of those expanded perspectives and context.
This naivety is shown here, as well:
@07:55 “What this means basically is a telescoping of the future.”
and here:
@08:01 “Think of all the crazy technologies that you could have imagined maybe humans could have developed in the fullness of time.”
I simply don’t know what to say about such a remark, except non sequitur. It simply doesn’t make any sense! Am I the only one who recognizes this fact? I sure hope not.
Our attention is then drawn to the blue hue surrounding the audience and I’m shocked to see how many people are being duped and even enthralled by this show. It’s as if they have taken their ‘phone off the hook’ and sit there like they’re watching a television. Some of them are even taking notes! We must stop being so trusting as to allow ourselves to be put in that position in the first place!
@08:24 “Now a super-intelligence with such ‘technological maturity’ would be extremely powerful. And at least in some scenarios, it would be able to get what it wants.”
There is no such thing as technological maturity and this underscores the disjunct the funders of science have created between who we are and our artefacts (what we make). He is talking about tools, isn’t he? He’s been trained to anthropomorphise technology (despite his reservations later below) as if it were ‘alive’ as we. Even if we were to create technology that is capable of mind, it would not represent an achievement of technology, rather an achievement of humanity. It would belong to our achievements.
@08:35 “We would then have a future that would be shaped by the preferences of this AI.”
How can we be sure? I ask this because, his next question is:
@08:41*“Now a good question is, ‘What are those preferences?’ Here it gets trickier.”
He gives his warning about anthropomorphising and shows a picture of a terminator. Before explaining what these preferences may be, he suggests to conceive of the issue “more abstractly”.
@09:09 “We need to think of intelligence as an optimization process. A process that steers the future into a particular set of configurations.”
How does he know that intelligence is the only factor doing the steering of the future or even if it’s possible to ‘steer’ the future? At best we can ‘steer’ ourselves and thereby influence how that future unfolds!
Also, optimization is not the only process necessary and is not alone sufficient to influence future outcomes. He’s now not only comparing apples with oranges, he’s using thin slices of them!
@09:17 “A super-intelligence is a really strong optimization process. It’s extremely good at using available means to achieve a state in which its goal is realized.”
This is another fundamental deficit with AI (which would be more aptly named: synthetic intelligence): they continually miss other aspects of reality that have nothing to do with state and aren’t states at all!
The universe doesn’t restrict itself to states no matter how needful we are to make it be so Hidden Markov models, Bayesian statistics, for example are all dead-ends which are in the process of playing themselves out.
Goal-oriented ‘intelligence’ is also not all there is to mind and the achievement of goals is not automatically a measure of usefulness nor necessarily a sign of intelligence.
It gets naively ‘Turing-esque’ with this statement:
@09:27 “This means there’s no necessary connection between being highly intelligent in this sense and having an objective that we humans would find worth while or meaningful.”
He’s using the word ‘connection’ here when he can only mean ‘difference’ for it to make any sense going from the way he’s framed the sentence.
I’ve written elsewhere on Turing, so I won’t go into detail, but this statement offers the same kind of fraud that the Turing Test offers us, namely: If a machine can fool you so well that you cannot tell it’s a machine or a real person, then the machine has passed the test.
Here he’s saying that a ‘super-intelligent machine’ being capable of pursuing a meaningful goal is another proof of its real intelligence. That’s incorrect even if it were possible get a machine participate in the richness of mind. We don’t yet even understand the processes in which we organically set and arrive at goals with, but we are going to have a machine do this?
@09:39 “Suppose we give an AI the goal to make humans smile. When the AI is weak, it performs useful or amusing actions that cause its user to smile. When the AI becomes super-intelligent it realizes there is a more effective way to achieve this goal.”
Ah… excuse me, but if we’re speaking of intelligence then we don’t have users, do we? We don’t if their intelligence is anything like our own.
He differentiates between strong and weak AI to underscore that ‘super-intelligence’ implies sentience. We don’t yet know how a dominant monad (‘I’-ness) works inside of us organically, not to mention how to impart this quality to a machine. I suppose, like all good materialists, we’ll just create enough initial conditions which then will become complex enough that sophonce spontaneously generates itself? (sophonce: self-awareness, including self-reflection and the ability to think about one’s thinking)
@09:43 “Take control of the world and like stick electrodes into the facial muscles of humans…”
Isn’t that sweet? That’s not intelligence, it’s stupidity, and a callous lack of regard for human dignity.
We knew that at least some mechanism of fear and control is going to be involved here (just having banksters fund the work presumes that ‘cocktail’ in the mix). But here is another example of the disparity made evident when such a thing could be made possible. We have received inverted and perverted priorities from those who fund our science and finance the development of our technology, and control the education of our young.
Do you see how easy it is for him to imagine such a scenario. See how the audience is not appalled at such an outcome? Neither the speaker nor the audience seems aware of how wrong this picture is.
The need to dominate and subjugate, which funds our science, pays for our technology and directs our education is even weaving itself into them: thereby infecting the young minds being exposed to it.
We must wake up and stop this perversion of our science and technology. If we do science or create technology with no concern for our values and ethics, then we are going to arrive at fundamental choices too early in our evolution and make the wrong choices on how they are put to use.
@10:02 “Take another example. Let’s suppose we give AI the goal to solve a difficult mathematical problem. When the AI becomes super-intelligent, it realizes that the most effective way is to get the solution to this problem by transforming the planet into a giant computer so as to increase its thinking capacity.”
Does that sound intelligent to you? I’m well aware of where this is heading, because of what has come before. We shall see what he proposes to solve his scenario’s ‘conundrum’. He’s simply giving us examples of what could be from his own imagination, but this reveals his own inner thoughts, feelings, priorities, and… training.
@10:17 “And notice that this gives the AI an instrumental reason to do things to us that we might not approve of. Human beings in this model are a threat. We could prevent the mathematical problem from being solved.”
If we could, why would we create an AI that would do such a thing? Mistakes happen? No! If an AI is really intelligent, it would also know of the consequences of its actions at the latest, during its execution of them.
Now we get to the main reason for the talk.
[To be continued in my next post with the same title.]
Men And Their Semantics – Turning Meaning into Legos
Semantically speaking: Does meaning structure unite languages?
This work is a dead end waiting to happen. Of course it will attract much interest, money, and perhaps even yield new insights into the commonality of language, but there’s better ways to get there.
What’s even more sad is that they, who should know better, will see my intentions in making this clear as destructive criticism instead of a siren warning regarding research governed/originating through a false paradigm. These people cannot see or overlook the costs humanity pays for the misunderstandings research like this causes and is based upon.
It’s even worse in the field of genetic engineering with their chimera research. The people wasting public money funding this research need to be gotten under control again.
I don’t want to criticize the researcher’s intentions. It’s their framing and methodology that I see as primitive, naive, and incomplete.
I’m not judging who they are nor their ends; rather, their means of getting there.
“Quantification” is exactly the wrong way to ‘measure/compare semantics; not to mention “partitioning” them!
1) The value in this investigation that they propose is to extrapolate and interpolate ontology. Semantics are more than ontology. They possess a complete metaphysics which includes their epistemology.
2) You cannot quantify qualities, because you reduce the investigation to measurement; which itself imposes meaning upon the meaning you wish to measure. Semantics, in their true form, are relations and are non-physical and non-reducible.
3) Notice also, partitioning is imposed upon the semantics (to make them ‘measurable/comparable’). If you compare semantics in such a way then you only get answers in terms of your investigation/ontology.
4) The better way is to leave the semantics as they are! Don’t classify them! Learn how they are related. Then you will know how they are compared.
There’s more to say, but I think you get the idea… ask me if you want clarification…
We Be To Not To Be
Shtick and pitch for fraud
This is another example of current trendy mainstream being given overly exaggerated results. We are simply getting better at expressing our own problem solving to computers.
Has anyone asked themselves or better, an expert of their choice, how a computer stores, understands and expresses its own purpose for being? or
Where a computer finds its own intention to know anything?
WE are providing these elements… not the computers themselves!
Please try to recognize that you are being given a shtick or pitch to make you believe that we are creating intelligent machines. What we are doing is learning to make better use of them! Bankster funded corporatism running our universities and economies are pulling the wool over our eyes. Wake up! Now!
Complexity At the Cost of Being Simple
Complexity At the Cost of Being Simple
There are grievous problems with complexity ‘science’. Some of those problems are apparent here. I will note a few of them.
Reductionism at @13:00 is completely annoying. Epiphenomenological aspects of the problem are completely missing when you reduce into pure binary! It’s like taking you and your emotional life (with its incipient impact on your immune system) and reducing it down to DNA!
“There are way more problems than there are solutions.” @17:00!Sure! When you peel away the contextual embedding of any problem (via reductionism), then you’ve just committed a sort of lobotomy!
The definition of NP at @23:00 while correct, reveals how misguided this theory is. Not all choices are guesses, and correct answers aren’t always ‘lucky’.
Check out the response one receives from the system (algorithm) at @25:11.Did you notice something’s wrong or what?
@26:51 Does anyone notice who is supplying the criterion for the value of ‘correct’? The algorithm is being falsely attributed with properties it can only be endowed with and not arrive at on its own!
@30:00 The rules to Tetris are known by both (algorithm and human) however, the proof of a truth value cannot be computationally arrived at in NP, yet the proof – via a human being AND the skills necessary to ‘prove’ anything can do it in P! It should be obvious that we are going about the whole thing in the wrong way by now!
@31:00 the P<>NP Problem is described. The problem is meaningless and yet you’ll get a Millenium Prize for solving it! (Even sane and not sane find themselves in the balance! Whoa!) If you continue listening to the justification, you might want to be near a bathroom.
@32:27 Check out how NP is being determined to be ‘more’ than P! “Nobody in their right mind…”, “Obviously insane…”,… so naturally NP must be more than P!
Sounds reasonable? I don’t think so…
@32:37 Watch the disappointment: “…very annoying…” and I wonder why? The question is meaningless! Other phrasings of the P<>NP Problem are nothing special and are completely obvious: “You can’t engineer luck.” (Excuse me, but isn’t that the definition of luck in the first place?) and “Solving problems is harder than checking them.”
@34:17 “What could we possibly say… this is all kind of weired…” I don’t know anymore either and I sure hope you don’t tell me! Are we at the end of the lecture already?
@35:53 Now we are getting to the ‘meat of the potato’. If we just “believe in… have faith in…” P<>NP, then Tetris is within NP-P! Wait a minute? That doesn’t sound like any proof to me… perhaps it’s an axiom? We’ll see. It sure looks like begging the question, but I want to be convinced so I’ll just have to wait.
@36:43 He then moves on to a ‘proof’ that looks more like a set of definitions! NP-hard and NP-complete are correctly defined, but they do not prove anything! Tetris and chess act like a definitions, as well!
@40:33 Now he wants to talk about reductions. Wait, weren’t we talking about them already? Let’s take a look…
Yes, we stand upon giants [Authoritarianism]@46:15(Karp’s 3-Partition) and don’t need to think about it anymore and just reconfirm that all NP-complete is reducible to each other! You find some problem that was defined by a “giant” to be a member of your classification and then show that yours is at least as hard @48:47.
If we happen to find a better solution to a member of NP-complete, then either the whole house of cards falls down or we simply reclassify (by reduction) it to P! Now believe it or believe what you want, okay?
There will be a time when we have to revisit mathematics and do a house cleaning of this ‘cuddle muddle’.
Good News! It’s Not Just Particles! It’s Properties and Patterns of Particles! – Max Tegmark
“Consciousness is a mathematical pattern.”
Is it possible to explain the phenomenon of purpose away with another phenomenon of emergence?
I wonder how he defines purpose itself?
Isn’t consciousness more than our senses?
Why are we only looking at states of matter and leave out stages, lines, levels, types,…?
Who is doing the “feeling” he’s describing?
Who gives the particles their work to do?
How are the particles different between dead and living beings?
So we are to replace our questions with a certainty of the phenomenon of consciousness and then explain that in terms of an interpretation of same?
I’m not a religious person, but the video is starting to sound like I should be one!
Is this what we get when a physicist tries to do philosophy? Oh my!
Knowledge Is What Awareness Does – Knowledge Representation as a Means to Define Meaning Precisely
Knowledge Representation as a Means to Define Knowledge Precisely
Video is finally here!
A Precise Definition of Knowledge – Knowledge Representation as a Means to Define the Meaning of Meaning Precisely
A Precise Definition of Knowledge
Knowledge Representation as a Means to Define the Meaning of Meaning Precisely
Copyright © Carey G. Butler
August 24, 2014
What is this video about?
In this introductory video I would like to explain what knowledge representation is, how to build and apply them. There are basically three phases involved in the process of building a knowledge representation. Acquisition of data (which includes staging), collation and the representation itself. The collation and the representation phases of the process are mentioned here, but I will explain them further in future videos.
You are now watching a simulation of the acquisition phase as it collects and stores preliminary structure from the data it encounters in terms of the vocabulary contained within that data. Acquisition is a necessary prerequisite for the collation phase following it, because the information it creates from the data are used by the collation algorithms which then transform that information into knowledge.
The statistics you are seeing tabulated are only a small subset of those collected in a typical acquisition phase. Each of these counters are being updated in correspondence to the recognition coming from underlying parsers running in the background. Depending upon the computer resources involved in the
acquisition, these parsers may even even run concurrently as is shown in this simulation.
The objects you see moving around in the video are of two different kinds: knowledge fields or knowledge molecules. Those nearest to you are the field representations of the actual data being collected called knowledge fields. They could represent an individual symbol, punctuation, morpheme, lexeme, word, emotion, perspective, or some other unit of information in the data. Each of them contain their own signature – even if their value, state or other intrinsic properties are unknown or indeterminate during the acquisition.
Those farther away from the view are clusters of fields which have already coalesced into groups according to shared dynamically adaptive factors such as similarity, relation, ordinality, cardinality,…
These ‘molecules’ also contain their own set of signatures and may be composed of a mixture of fields, meta-fields and hyper-fields that are unique to all others.The collation phase has the job of assigning these molecules to their preliminary holarchical domains which are then made visible in the resulting knowledge representation. Uniqueness is preserved even if they contain common elements with others in the domain they occupy. Clusters of knowledge molecules and/or fields grouped together are known as ‘knowledge domains’, ‘structural domains’,’dynamical domains’ or ‘resonance domains’, depending upon which of their aspects is being emphasized.
We now need a short introduction to what knowledge representation is in order to explain why you’re seeing these objects here.
What is Knowledge Representation?
Knowledge representation provides all of the ways and means necessary to reliably and consistently conceptualize our world. It helps us navigate landscapes of meaning without losing our way; however, navigational bearing isn’t the only advantage. Knowledge representation aids our recognition of what changes when we change our world or something about ourselves. It does so, because even our own perspective is included in the representation. It can even reveal to us when elements are missing or hidden from our view!
It’s important to remember that knowledge representation is not an end, rather a means or process that makes explicit to us everything we already do with what we come to be aware of. A knowledge representation must be capable of representing knowledge such that it, like a book or other artifact, brings awareness of that knowledge to us. When we do it right, it actually perpetuates our understanding by providing a means for us to recognize, interpret (understand) and utilize the how and what we know as it relates to itself and to us. In fact – knowledge representation even makes it possible to define knowledge precisely!
What Knowledge is not!
Knowledge is not very well understood so I’ll briefly point out some of the reasons why we’ve been unable to precisely define what knowledge is thus far. Humanity has made numerous attempts at defining knowledge. Plato taught that justified truth and belief are required for something to be considered knowledge. Throughout the history of the theory of knowledge (epistemology), others have done their best to add to Plato’s work or create new or more comprehensive definitions in their attempts to ‘contain’ the meaning of meaning (knowledge). All of these efforts have failed for one reason or another. Using truth value and justification as a basis for knowledge or introducing broader definitions or finer classifications can only fail. I will now provide a small set of examples of why this is so.
Truth value is only a value that knowledge may attend. Knowledge can be true or false, justified or unjustified, because knowledge is the meaning of meaning. What about false or fictitious knowledge? Their perfectly valid structure and dynamics are ignored by classifying them as something else than what they are. Differences in culture or language make even make no difference, because the objects being referred to have meaning that transcends language barriers.
Another problem is that knowledge is often thought to be primarily semantics or even ontology based! Both of these cannot be true for many reasons. In the first case (semantics): There already exists knowledge structure and dynamics for objects we cannot or will not yet know. The same is true for objects to which meaning has not yet been assigned,such as ideas, connections and perspectives that we’re not yet aware of or have forgotten. Their meaning is never clear until we’ve become aware of or remember them.
In the second case (ontology): collations that are fed ontological framing are necessarily bound to memory, initial conditions of some kind and/or association in terms of space, time, order, context, relation,… We build whole catalogs, dictionaries and theories about them! Triads, diads, quints, ontology charts, neural networks, semiotics and even the current research in linguistics are examples. Even if an ontology or set of them attempts to represent intrinsic meaning, it can only do so in a descriptive (extrinsic) way.
An ontology, no matter how sophisticated, is incapable of generating the purpose of even its own inception, not to mention the purpose of objects to which it corresponds! The knowledge is not coming from the data itself, it’s always coming from the observer of the data – even if that observer is an algorithm!
Therefore ontology-based semantic analysis can only produce the artifacts of knowledge, such as search results, association to other objects, ‘knowledge graphs’ like Cayley,.. Real knowledge precedes, transcends and includes our conceptions, cognitive processes, perception, communication, reasoning and is more than simply related to our capacity of acknowledgment. In fact knowledge cannot even be completely systematized, it can only be interacted with using ever increasing precision!
- What is knowledge then?
• Knowledge is what awareness does.
• Awareness of some kind and at some level is the only prerequisite for knowledge and is the substrate upon which knowledge is generated.
• Awareness coalesces, interacts with and perpetuates itself in all of its form and function.
• Awareness which resonates (shares dynamics) at, near, or in some kind of harmony (even disharmony) with another tends to associate (disassociate) with that other in some way.
• These requisites of awareness hold true even for objects that are infinite or indeterminate.
• This is why knowledge, the meaning of meaning, can be precisely defined and even provides its own means for doing so.
• Knowledge is, pure and simply: the resonance, structure and dynamics of awareness as it creates and discovers for and of itself.
• Awareness precedes meaning and provides the only fundamentally necessary and sufficient basis for meaning of meaning expressing itself as knowledge.
• Knowledge is the dialog between participants in awareness – even if that dialog appears to be only one-way, incoherent or incomplete.
• Even language, mathematics, philosophy, symbolism, analogy, metaphor and sign systems can all be resolved to this common denominator found at the foundation of each and every one of them.
More information about the objects seen:
The objects on the surface of the pyramid correspond to basic structures denoting some of the basic paradigms that are being used to mine data into information and then collate that information into knowledge. You may notice that their basic structures do not change, only their content does. These paradigms are comprised of contra-positional fields that harmonize with each other so closely that they build complete harmonic structures. Their function is similar to what proteins and enzymes do in our cells.
#Knowledge #Wisdom #Understanding #Learning #Insight #Semantics #Ontology #Epistemology #Philosophy #PhilosophyOfLanguage #PhilosophyOfMind #Cognition #OrganicIntelligence #ArtificialIntelligence #OI #AI
#Awareness
Spreading It Thick! Hopelessness Propaganda Placement That Doesn’t Even Smell Good! (BS)
Helplessness Propaganda Placement Video
This propaganda piece is easy to decode. Let’s play like we’re redundant.
We will never make humans redundant. Even if those who run and control our society want it that way! Creativity cannot be replaced and, although this video mentions it, it’s only ‘intelligence’ masking it.
I’m thinking of the film WALL-E. The humans were redundant and left the Earth on some pointless trip and left intelligent robots on the Earth to clean up their garbage.
The analogy of the horse fails (among other analogies in the film) when one realizes that horses were only assigned the purposes that we imagined for them. (Not to mention for ourselves!)
The film is social engineering propaganda designed to drive hopelessness into the viewer. It’s more of this arrogant in your face ‘Get used to it, like it or not’ weaponized culture (‘bitch culture’) they sell to us.
Just because our corporations are leading us to a place where automation takes our jobs away they have not and cannot take our usefulness in creativity away. They are describing more about their failure than their victory. They describe a culture and social fabric that they created, not WE!
The whole of humanity, and all of its potential (which they have failed to find access to) is not even being considered in this artificial world they are creating!
There are many other subtle mind manipulations going on in this piece, but I’d like to leave that open for future discussion.
Knowledge Representation – Self and Other
Knowledge Representation of Self and Other
This knowledge representation, which I made for a presentation in Nürnberg on April 29th, 2013, depicts a partial resonance domain with respect to sentient relation and orientation. The representation is not designed to be comprehensive in any respect, rather it is intended to help those who are not accustomed to viewing knowledge in this way.
It shows how, to quote Carl Sagan: “One voice in the Cosmic fugue.” can be represented more generally. There are certainly other possibilities with respect to relation and orientation between self and other.
You may need to stop this video occasionally as some of the transitions occur very quickly.I’ve indicated what is happening in the representation to aid in the interpretation of what is being shown.
I would appreciate any feedback you may want to give. I’d be pleased to answer any questions that may arise.
Thank you for watching!
UPDATE:
A question has come in from an anonymous source asking for clarification on the use of “Resonance Domain”.
A resonance domain is comprised of resonance fields. When one or more fields are being examined, the group is called a domain.
For further clarity I’d like to add that we are looking at two separate fields (sentient beings) in terms of the relation they participate in and the orientation they share with each other.
Fields are always composed of other sub-fields and contain even partial fields from other sources!
UPDATE: “Why do you use the word ‘sentient’ in your description?”
There are basically three types of entities in our universe:
1) Having some measure of interiority (concept of self).
2) Artifacts
3) Heaps
‘Self and other’ can come in any number of combinations:
The knowledge representation above requires that at least two of the participants are of type 1 (sentience) for this knowledge representation to hold.
Examples:
Type 1) human and type 1) dog will work.
Type 1) human and type 2) book will not work.
Type 1) human and type 3) rock will not work.
This way of looking at our Kosmos (multiverse) is called Mathesis Universalis.
For those interested in more on the subject, go to http://mathesis-universalis.com.
[PS: There are also the conditions that both participants are conscious of each other and that their shared consciousness is such that differences in semantics between them are ‘reconcilable’ (coherence). (for the scientists/mathematicians among us!)] 😉
Google’s Ray Kurzweil On Artificial Intelligence, Human Immortality
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The ongoing perception deception masking malevolence with benevolence.
True intelligence can never be artificial and the mind is much more than the brain can be used to explain it.
He is wrong in many ways. Even if he has really foreseen other inventions, this is one where he is wrong. They will, however, made a good show of it, by convincing us of their success so that we buy into the fraud with investment or participation.
WE (all biology) ARE the Most Advanced Technology In the Universe…
Using the 4th most powerful computer in the world: “The computer has 705,024 processor cores and 1.4 million GB of RAM, but still took 40 minutes to crunch the data for just one second of brain activity.”
read more: http://tinyurl.com/pexmtk6
Intel Announces Edison, A Computer the Size Of An SD Card
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Why aren’t we discovering and creating ourselves rather than pay corporations to create things that are going to replace us? Something is really wrong here.
We are creating a nightmare when we could have a wonderful dream made reality.
The name Edison is fitting (if you know how Edison treated Tesla.)
Google Semantic Search – David Amerland
What is Semantic Search?
The first thing I notice is the fluid, direct and economical style of writing that makes reading the book a pleasant experience.
1 Definition found: Search, above all else, is marketing.
The Shift to Semantic Search
I disagree with the addage “Knowledge is power!” For me, the use of knowledge is what can be or manifests power. David’s proviso that “knowledge is power if it leads to comprehension” pleases me, because it comes closer to what knowledge is, as it relates to power.
2 Definitions found: Semantics, Tim Berners-Lee’s ‘Semantic Search’
At one point David refers to how an answer engine’s success, as well as Google’s brand, depends upon the answers it provides; I would include other critical factors having nothing to do with the answers the engine returns. Google’s reputation is already in question in meaningful circles, despite the usefulness of its algorithms. I suspect that David will address at least some of them as the book continues.
How Search Works
Definitions: Spiders, Index, SERPs, organic results, ranking elements (algorithm/signals).
Clarifications:
How Google’s page is synthesized from an interplay of elements composed of front and back ends.
The incredible speed and volume of indexing data is touched on.
Where the system no longer works as it was intended (SEO gaming) and how semantic search has changed that.
I like the use of the term ‘signals’ (a characteristic of knowledge) with respect to ranking. I’m looking forward to a clearer understanding of what that entails as it relates to semantic search.
How Semantic Search Works
Definitions: URI, RDF, (semantic) ontologies, serendipity discovery (and the dynamics that govern it)
Clarifications:
Requirements that semantic search must be supplied to understand words (URI, RDF, ontology library)
Learning more about serendipity discovery interests me, however at this point in the text, only its usefulness in marketing and finding customers in the future is discussed. There is mention, however, that the book formalizes a set of practices to use it.
I am looking forward to an explanation of why serendipity discovery is treated in this ‘condensed’ way. David offers a bibliography for those who need a deeper understanding.
I am concerned on one other point: the restriction of semantics solely to an ontological foundation. I am aware at this point that an interplay of 2 additional components (and their surrounding dynamics) are in use (URI and RDF), but I need to know more about them, before I am willing to trust them completely.
It is important to remember that up to this point no promise is made for _real_ understanding in the model presented, rather only its _simulation._ That seems to be, nevertheless, very useful and completely new.
Kara : A PS3 New Technology
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For those barren of humanity, the next place is barren humanity.
Has anyone taken the time to ask themselves why we are being driven to create machines like we are instead of use our creative power in developing ourselves?
Cognitive Computing
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“Looking for consciousness in the brain is like looking inside a radio for the announcer” – Nassim Haramein
Sorry to burst your bubble, but the mind cannot be reduced to a brain.
Meet Atlas – DRC-Robot
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They’re being built to help you. They just wana help mankind..
Now give them your money to build them,… ‘kay?
(You know it’s trendy…)
The long-term future of AI(and what we can do about it): Daniel Dewey
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This is more about harvesting funding for computer hardware and software than about anything we can take seriously.
@01:20“[AI] It’s a bit like a particle. There are arguments as to why it should exist, but we haven’t been able to confirm it yet.”
And you won’t either. Particles are not fundamental, rather they are only a manifestation of an underlying (and completely fundamental) field.
The current AI is lost in, just like physics, a compulsion to explain the world in only physical terms. Meaning of World, Thought and Language will continue to elude them as long as they keep on chasing a failed and bereft paradigm. It sure is trendy, but it’s false.
DARPA Envisions the Future of Machine Learning
This is an example of what I referred to earlier in some of my posts. This one is about probabilistic programming. Our government is spending our money on research that isn’t even capable of achieving the goals it sets for itself.
They may be able to create semi-intelligent drones with this kind of research, but they will never achieve their aim of intelligent machines.
Heurist.me (Carey G. Butler) 