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    Default The Dark Secret at the Heart of AI

    MIT
    Technology
    Review

    ________________
    Intelligent Machines


    The Dark Secret at the Heart of AI
    No one really knows how the most advanced algorithms
    do what they do. That could be a problem.
    Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it.

    Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result seems to match the responses you’d expect from a human driver. But what if one day it did something unexpected—crashed into a tree, or sat at a green light? As things stand now, it might be difficult to find out why. The system is so complicated that even the engineers who designed it may struggle to isolate the reason for any single action. And you can’t ask it: there is no obvious way to design such a system so that it could always explain why it did what it did.

    The mysterious mind of this vehicle points to a looming issue with artificial intelligence. The car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

    But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will. That’s one reason Nvidia’s car is still experimental.

    Already, mathematical models are being used to help determine who makes parole, who’s approved for a loan, and who gets hired for a job. If you could get access to these mathematical models, it would be possible to understand their reasoning. But banks, the military, employers, and others are now turning their attention to more complex machine-learning approaches that could make automated decision-making altogether inscrutable. Deep learning, the most common of these approaches, represents a fundamentally different way to program computers. “It is a problem that is already relevant, and it’s going to be much more relevant in the future,” says Tommi Jaakkola, a professor at MIT who works on applications of machine learning. “Whether it’s an investment decision, a medical decision, or maybe a military decision, you don’t want to just rely on a ‘black box’ method.”

    There’s already an argument that being able to interrogate an AI system about how it reached its conclusions is a fundamental legal right. Starting in the summer of 2018, the European Union may require that companies be able to give users an explanation for decisions that automated systems reach. This might be impossible, even for systems that seem relatively simple on the surface, such as the apps and websites that use deep learning to serve ads or recommend songs. The computers that run those services have programmed themselves, and they have done it in ways we cannot understand. Even the engineers who build these apps cannot fully explain their behavior.

    This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.

    The artist Adam Ferriss created this image, and the one below, using Google Deep Dream, a program
    that adjusts an image to stimulate the pattern recognition capabilities of a deep neural network. The
    pictures were produced using a mid-level layer of the neural network --Adam Ferriss
    In 2015, a research group at Mount Sinai Hospital in New York was inspired to apply deep learning to the hospital’s vast database of patient records. This data set features hundreds of variables on patients, drawn from their test results, doctor visits, and so on. The resulting program, which the researchers named Deep Patient, was trained using data from about 700,000 individuals, and when tested on new records, it proved incredibly good at predicting disease. Without any expert instruction, Deep Patient had discovered patterns hidden in the hospital data that seemed to indicate when people were on the way to a wide range of ailments, including cancer of the liver. There are a lot of methods that are “pretty good” at predicting disease from a patient’s records, says Joel Dudley, who leads the Mount Sinai team. But, he adds, “this was just way better.”
    “We can build these models,
    but we don’t know how they work.”

    At the same time, Deep Patient is a bit puzzling. It appears to anticipate the onset of psychiatric disorders like schizophrenia surprisingly well. But since schizophrenia is notoriously difficult for physicians to predict, Dudley wondered how this was possible. He still doesn’t know. The new tool offers no clue as to how it does this. If something like Deep Patient is actually going to help doctors, it will ideally give them the rationale for its prediction, to reassure them that it is accurate and to justify, say, a change in the drugs someone is being prescribed. “We can build these models,” Dudley says ruefully, “but we don’t know how they work.”

    Artificial intelligence hasn’t always been this way. From the outset, there were two schools of thought regarding how understandable, or explainable, AI ought to be. Many thought it made the most sense to build machines that reasoned according to rules and logic, making their inner workings transparent to anyone who cared to examine some code. Others felt that intelligence would more easily emerge if machines took inspiration from biology, and learned by observing and experiencing. This meant turning computer programming on its head. Instead of a programmer writing the commands to solve a problem, the program generates its own algorithm based on example data and a desired output. The machine-learning techniques that would later evolve into today’s most powerful AI systems followed the latter path: the machine essentially programs itself.

    At first this approach was of limited practical use, and in the 1960s and ’70s it remained largely confined to the fringes of the field. Then the computerization of many industries and the emergence of large data sets renewed interest. That inspired the development of more powerful machine-learning techniques, especially new versions of one known as the artificial neural network. By the 1990s, neural networks could automatically digitize handwritten characters.

    But it was not until the start of this decade, after several clever tweaks and refinements, that very large—or “deep”—neural networks demonstrated dramatic improvements in automated perception. Deep learning is responsible for today’s explosion of AI. It has given computers extraordinary powers, like the ability to recognize spoken words almost as well as a person could, a skill too complex to code into the machine by hand. Deep learning has transformed computer vision and dramatically improved machine translation. It is now being used to guide all sorts of key decisions in medicine, finance, manufacturing—and beyond.

    Adam Ferriss
    Cornell's artificial neural network
    through Deep Dream by Ferriss

    (Nov 23, 2017)
    The workings of any machine-learning technology are inherently more opaque, even to computer scientists, than a hand-coded system. This is not to say that all future AI techniques will be equally unknowable. But by its nature, deep learning is a particularly dark black box.

    You can’t just look inside a deep neural network to see how it works. A network’s reasoning is embedded in the behavior of thousands of simulated neurons, arranged into dozens or even hundreds of intricately interconnected layers. The neurons in the first layer each receive an input, like the intensity of a pixel in an image, and then perform a calculation before outputting a new signal. These outputs are fed, in a complex web, to the neurons in the next layer, and so on, until an overall output is produced. Plus, there is a process known as back-propagation that tweaks the calculations of individual neurons in a way that lets the network learn to produce a desired output.

    The many layers in a deep network enable it to recognize things at different levels of abstraction. In a system designed to recognize dogs, for instance, the lower layers recognize simple things like outlines or color; higher layers recognize more complex stuff like fur or eyes; and the topmost layer identifies it all as a dog. The same approach can be applied, roughly speaking, to other inputs that lead a machine to teach itself: the sounds that make up words in speech, the letters and words that create sentences in text, or the steering-wheel movements required for driving.
    “It might be part of the nature of intelligence that only part of it is exposed to rational explanation. Some of it is just instinctual.”
    Ingenious strategies have been used to try to capture and thus explain in more detail what’s happening in such systems. In 2015, researchers at Google modified a deep-learning-based image recognition algorithm so that instead of spotting objects in photos, it would generate or modify them. By effectively running the algorithm in reverse, they could discover the features the program uses to recognize, say, a bird or building. The resulting images, produced by a project known as Deep Dream, showed grotesque, alien-like animals emerging from clouds and plants, and hallucinatory pagodas blooming across forests and mountain ranges.
    The images proved that deep learning need not be entirely inscrutable; they revealed that the algorithms home in on familiar visual features like a bird’s beak or feathers. But the images also hinted at how different deep learning is from human perception, in that it might make something out of an artifact that we would know to ignore. Google researchers noted that when its algorithm generated images of a dumbbell, it also generated a human arm holding it. The machine had concluded that an arm was part of the thing.

    Further progress has been made using ideas borrowed from neuroscience and cognitive science. A team led by Jeff Clune, an assistant professor at the University of Wyoming, has employed the AI equivalent of optical illusions to test deep neural networks. In 2015, Clune’s group showed how certain images could fool such a network into perceiving things that aren’t there, because the images exploit the low-level patterns the system searches for. One of Clune’s collaborators, Jason Yosinski, also built a tool that acts like a probe stuck into a brain. His tool targets any neuron in the middle of the network and searches for the image that activates it the most. The images that turn up are abstract (imagine an impressionistic take on a flamingo or a school bus), highlighting the mysterious nature of the machine’s perceptual abilities.

    This early artificial neural network, at the Cornell Aeronautical Laboratory in Buffalo, New York,
    circa 1960, processed inputs from light sensors.
    We need more than a glimpse of AI’s thinking, however, and there is no easy solution. It is the interplay of calculations inside a deep neural network that is crucial to higher-level pattern recognition and complex decision-making, but those calculations are a quagmire of mathematical functions and variables. “If you had a very small neural network, you might be able to understand it,” Jaakkola says. “But once it becomes very large, and it has thousands of units per layer and maybe hundreds of layers, then it becomes quite un-understandable.”

    In the office next to Jaakkola is Regina Barzilay, an MIT professor who is determined to apply machine learning to medicine. She was diagnosed with breast cancer a couple of years ago, at age 43. The diagnosis was shocking in itself, but Barzilay was also dismayed that cutting-edge statistical and machine-learning methods were not being used to help with oncological research or to guide patient treatment. She says AI has huge potential to revolutionize medicine, but realizing that potential will mean going beyond just medical records. She envisions using more of the raw data that she says is currently underutilized: “imaging data, pathology data, all this information.”
    How well can we get along with
    machines that are unpredictable
    and inscrutable?
    After she finished cancer treatment last year, Barzilay and her students began working with doctors at Massachusetts General Hospital to develop a system capable of mining pathology reports to identify patients with specific clinical characteristics that researchers might want to study. However, Barzilay understood that the system would need to explain its reasoning. So, together with Jaakkola and a student, she added a step: the system extracts and highlights snippets of text that are representative of a pattern it has discovered. Barzilay and her students are also developing a deep-learning algorithm capable of finding early signs of breast cancer in mammogram images, and they aim to give this system some ability to explain its reasoning, too. “You really need to have a loop where the machine and the human collaborate,” -Barzilay says.

    The U.S. military is pouring billions into projects that will use machine learning to pilot vehicles and aircraft, identify targets, and help analysts sift through huge piles of intelligence data. Here more than anywhere else, even more than in medicine, there is little room for algorithmic mystery, and the Department of Defense has identified explainability as a key stumbling block.

    David Gunning, a program manager at the Defense Advanced Research Projects Agency, is overseeing the aptly named Explainable Artificial Intelligence program. A silver-haired veteran of the agency who previously oversaw the DARPA project that eventually led to the creation of Siri, Gunning says automation is creeping into countless areas of the military. Intelligence analysts are testing machine learning as a way of identifying patterns in vast amounts of surveillance data. Many autonomous ground vehicles and aircraft are being developed and tested. But soldiers probably won’t feel comfortable in a robotic tank that doesn’t explain itself to them, and analysts will be reluctant to act on information without some reasoning. “It’s often the nature of these machine-learning systems that they produce a lot of false alarms, so an intel analyst really needs extra help to understand why a recommendation was made,” Gunning says.

    This March, DARPA chose 13 projects from academia and industry for funding under Gunning’s program. Some of them could build on work led by Carlos Guestrin, a professor at the University of Washington. He and his colleagues have developed a way for machine-learning systems to provide a rationale for their outputs. Essentially, under this method a computer automatically finds a few examples from a data set and serves them up in a short explanation. A system designed to classify an e-mail message as coming from a terrorist, for example, might use many millions of messages in its training and decision-making. But using the Washington team’s approach, it could highlight certain keywords found in a message. Guestrin’s group has also devised ways for image recognition systems to hint at their reasoning by highlighting the parts of an image that were most significant.

    One drawback to this approach and others like it, such as Barzilay’s, is that the explanations provided will always be simplified, meaning some vital information may be lost along the way. “We haven’t achieved the whole dream, which is where AI has a conversation with you, and it is able to explain,” says Guestrin. “We’re a long way from having truly interpretable AI.”

    It doesn’t have to be a high-stakes situation like cancer diagnosis or military maneuvers for this to become an issue. Knowing AI’s reasoning is also going to be crucial if the technology is to become a common and useful part of our daily lives. Tom Gruber, who leads the Siri team at Apple, says explainability is a key consideration for his team as it tries to make Siri a smarter and more capable virtual assistant. Gruber wouldn’t discuss specific plans for Siri’s future, but it’s easy to imagine that if you receive a restaurant recommendation from Siri, you’ll want to know what the reasoning was. Ruslan Salakhutdinov, director of AI research at Apple and an associate professor at Carnegie Mellon University, sees explainability as the core of the evolving relationship between humans and intelligent machines. “It’s going to introduce trust,” he says.

    Just as many aspects of human behavior are impossible to explain in detail, perhaps it won’t be possible for AI to explain everything it does. “Even if somebody can give you a reasonable-sounding explanation [for his or her actions], it probably is incomplete, and the same could very well be true for AI,” says Clune, of the University of Wyoming. “It might just be part of the nature of intelligence that only part of it is exposed to rational explanation. Some of it is just instinctual, or subconscious, or inscrutable.”

    If that’s so, then at some stage we may have to simply trust AI’s judgment or do without using it. Likewise, that judgment will have to incorporate social intelligence. Just as society is built upon a contract of expected behavior, we will need to design AI systems to respect and fit with our social norms. If we are to create robot tanks and other killing machines, it is important that their decision-making be consistent with our ethical judgments.

    To probe these metaphysical concepts, I went to Tufts University to meet with Daniel Dennett, a renowned philosopher and cognitive scientist who studies consciousness and the mind. A chapter of Dennett’s latest book, From Bacteria to Bach and Back, an encyclopedic treatise on consciousness, suggests that a natural part of the evolution of intelligence itself is the creation of systems capable of performing tasks their creators do not know how to do. “The question is, what accommodations do we have to make to do this wisely—what standards do we demand of them, and of ourselves?” he tells me in his cluttered office on the university’s idyllic campus.

    He also has a word of warning about the quest for explainability. “I think by all means if we’re going to use these things and rely on them, then let’s get as firm a grip on how and why they’re giving us the answers as possible,” he says. But since there may be no perfect answer, we should be as cautious of AI explanations as we are of each other’s—no matter how clever a machine seems. “If it can’t do better than us at explaining what it’s doing,” he says, “then don’t trust it.”

    Article Source
    Last edited by turiya; 23rd November 2017 at 18:07.

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    Default Re: The Dark Secret at the Heart of AI

    The Kev Baker Show with Anthony Patch...

    Interrogating A.I. with Anthony Patch
    (Nov 21, 2017)

    @~4:40
    Anthony Patch: "But the Lord laughs at the wicked for He knows their day is coming."

    Kev Baker: We spoke about Jeff Bezos and the fact that he is the man behind Amazon. Well, its now public, and its in Business Insider right now that Amazon is launching a secret cloud service (article) for the CIA.

    So that's right folks, Amazon - the people that do all your online shopping - but they've moved into so many other areas now - including Amazon Alexa that home system that records absolutely everything. And here we are now, Tony, sitting & looking at articles where they are joining forces with the CIA to come up with something that they've called Secret Region - an Amazon web-based service for the CIA.

    Anthony Patch: DARPA, representing the Defense Department - the government-at-large - puts out what are known as RFPs - A request for proposal (RFP) - DARPA comes up with an idea, a concept. And then they put it out to the public sector to bring their idea to life, so-to-speak, an RFP put out for data acquisition, but in a very secure environment within the super-computing cloud-based systems. And this is what the public sector bid on. Amazon won the bid. It was a $600 million deal.

    That was back in 2014. That is something that we've brought up to our up-to-speed audience, but there may be some new folks in the audience, so I kind of retrace our steps a little bit.

    But this just demonstrates what we've said before - about companies like Amazon, Google, Facebook & others... including D-Wave, who have all received multiple millions of dollars from DARPA.

    Now, its not all that sinister, in terms of how this takes - its not behind closed doors. As I said, its a public request for proposals - to make a bid, its an open bid system. But you can be guaranteed that Amazon had an edge in the bidding process. Because Amazon itself was founded through an RFP process with DARPA. Just like Facebook, just like Google, they received their seed money - their start-up capital - from DARPA, the American taxpayer.

    -----------------

    @9:08
    Anthony Patch: Folks, you got to understand... This isn't conspiracy theories being bantered around. On the one hand, you can say its a benevolent process - that our intelligence communities are using the high-tech sector for the benefit of protecting us from threats. Okay, I get it. We're speaking the intelligence communities everytime we do our show, Kev, everytime we're on the computer - everything is being monitored - not just us, but everybody. So we know that, there is no such thing as privacy anymore.

    So what I am saying to the intelligence community - directly, as we often do on this show - is that we are not your enemy. We're simply saying is that "when you involved the private sector, it should be transparent, it shouln't be hidden. The fact that your seed money for these corporations come from the American taxpayer, it should be transparent for the American taxpayer. I understand about keeping secrets from your enemies, etcetera, etc. But when the process, when the technology, when the intelligence-gathering process is used against people, individually, who are not breaking the law, when surveillance becomes the methodology by which you control people, beyond simply securing them & protecting them, then we step into the arena of fascism. And that when I have a problem with these kinds of surveillance programs. Because our liberties are few that are remaining, and even those are pretty much an illusion at this point."

    So, we're just sharing the facts. This comes out in the public media. This is just Business Insider public information. We're just repeating it. So, I would just ask the intelligence community, "Back off. We're not your enemy. We're just repeating the news. We're reporters. And we're certainly not a threat to anyone."

    Kev Baker: And, there's something else I find interesting... You've got DARPA, who obviously helped Jeff Bezos get off the ground in the first place, they helped another company as well called D-Wave, and Jeff Bezos just happens to own D-Wave.

    So now, we have a definite connection between the intelligence agencies over in the U.S. and a D-Wave. So again, in my mind, any potential 'white hat' hackers out there who are intending to hit any intelligence services networks - well, I think you're up against it now, because we're looking at quantum encryption on this part of the cloud, I would imagine.


    Anthony Patch: Oh most definitely, because one of the premise for building the quantum computers is to break all forms of encryption, particularly RSA coding, based on Shor's algorithm communications.

    So, 2048 & 4096 - both alogrithms - its important to understand that cryptology - secrets / secret communications / quantum encrypted communications - is all of where its at. So I would venture to say that in this article they're talking about secret & top-secret... Look, anything that is beyond top-secret is going to be encrypted in a quantum communication - specifically, a quantum entangled form of communication. And Kev, we've covered China & all of their processes of quantum communications between ground-based systems & satellite-based systems & point-to-point on-the-ground systems of entangled communications.

    What it means, just as a quick review, is that quantum entangled communications cannot be hacked. It requires an identical quantum computer, but even when you do that you collapse the entanglement. And therefore, when you collapse the entanglement, it is detected - it is registered by the parent quantum system. So virtually, the system shuts down, is the way to put it - if there is any attempt to hack it.

    So we're really talking about, what I venture to say, the ultimate secure communication & data collection system when it is based on a quantum computer. We're going to relate a little bit later on, some more about quantum computers as they relate to graphics cards, and, how AI has developed. We'll talk about - kind of a low-level AI with graphics cards, then we're going to go to the quantum scale & the more sophisticated, as the show progresses.

    Kev Baker: With China taking control of the infrastructure of this actual network that they're building. And if that's the case then, Anthony, I think the listeners should be made aware of just where the heart of the AI is going to come from. Because I think we're now starting to see the location which where all this is going to be based. Interestingly enough, it doesn't come a million miles away from our favorite place - CERN. Because, Switzerland is definately on the map when it comes to AI, isn't it?

    Anthony Patch: It definitely is. Early last week, or the week prior to that, we brought out the Blue Brain Initiative - the Blue Brain Laboratories in Switzerland. And there actually are about six(6) primary neurological research centers in Switzerland right outside of CERN - and that is not by random selection that they've placed themselves there. Because we revealed a couple weeks ago that the large Hadron Collider - the Synchotron Collider - operates in a quantum mechanical fashion that is identical to D-Wave's quantum computers, only the scale is different.

    I put out, what I believe, is proof that the LAC - the particle collider - actually operates as a quantum computer. And therefore, they have the ty(?), and the ability, to feed that information to these brain-mapping neural-morphic laboratories where they're trying to counterfit the human brain. They're actually trying to create artifical neurons, artificial cubits, artificial brains to counterfit the human brain.

    Virtually all of the work that is going on in the United States related to neuralmorphic counterfitting, if you will - the mapping of the brain, and then the reproduction of the structures of the brain - all of that research is being fed to Switzerland - specifically, to Blue Brain [Project]. And that has a direct tie to what is known as the Singularity in the Bitcoin Blockchain environment. And, singularityNET.IO is the website. And we presented that a few days ago. And there is a direct correlation between AI, Blockchain or cryptocurrency, the Singularity, as it relates to this company known as SingularityIO who is really running what is the single clearinghouse software program for all cryptocurrencies.

    So that is quick review of what we've already covered. But there is a definate connection between CERN, the Project with a Brain, AI, cryptocurrency and, just to wrap this up, Kev - cryptocurrency is a blockchain, and as we have presented, is for the purpose of gathering data & raising the I.Q. of AI.

    Kev Baker: Absolutely. And now to build onto that information for the weekend, I came across an article. And I want people to really take note - write down this term, because this is something we're going to hear about this more & more, imo. And that is: Artificial Organisms. This comes from, myself & Anthony's favorite website, futurism.com. But the headline reads:
    A Global Collaboration to Create “Artificial Organisms” Just Went Live
    And it goes on to say that:
    The Brain Code
    Mindfire, a new foundation with the goal of “decoding the mind” to help develop true artificial intelligence (AI) is launching November 17th in Zurich, Switzerland.
    Now,
    Mindfire, they've got their website. And just to give you a taste as to what they're about, I will give a quote:
    Mindfire Mission
    "It is the aspiration of Mindfire to unite the smartest minds on earth to work together on one of the greatest unsolved challenges of our time – to free the mind code.

    The Foundation

    The Mindfire foundation is a non-profit organization established with the principle of progressing AI openly, responsibly and ethically. In short, to use the power of human level AI to solve our most pressing global challenges.

    How to achieve our goal
    We sincerely believe that what is needed to decode the human mind is already out there. It is a matter of bringing together the brightest minds – which we call talents - and to inspire them to realize their full potential, in a completely new environment, with the right incentives and support.

    For that reason, we have organized a series of Missions that will tackle different topics, in accordance with timelines proposed by our scientific advisory board. The very first Mission will happen in Davos, starting May 12th, when 100 talents will unite their cognitive power for 9 days, and kick-off the journey to free the mind code.
    Now Anthony, we kind of went back & forth when I found this article. So let's get your thoughts on what we're seeing with 'Mindfire' & the fact that it's coming out of Switzerland.


    Anthony Patch: I will present it as somewhat of a prediction...
    We will see a shift in the media coverage of AI - moving away from using the term 'AI' at the highest levels & applications of AI to using this term 'Artificial Organisms'.

    So make a note of that folks, you heard it first on the Kev Baker Show - 'Artifical Organisms' rather than speaking in terms of 'AI'. Now what does this mean?

    I'll cut right to the chase... In the past, we have described the data storage - our mainframe, where our memories lie - is within our DNA, its not in the human brain. We said this on the Wednesday show (15-Nov 2017). The brain is the processor. If you think about a graphics program that is running a desktop, in a tower - you're running your games through your graphics intensive PC or Mac - and you will have one of two drives, and then you'll have a terabite external drive, or larger hardrive within the system. The one, two or three, terabite system or drive, is much like our DNA. And then you'll have faster access drives on the motherboard - that's the same thing as our human brain.

    So, there are limited memories within the brain itself. The majority of them are stored in the DNA. This is why they are going to Artificial Organisms. This is a whole body approach. And within this article from Futurism.com, by Patrick Caughill on November 17, 2017 - that's our source.

    They're speaking in terms of exactly that. The DNA - representing the body. And the brain - representing the quantum computer - are now being utilized together, as an entire artificial intelligent, an artificial organism environment. It's no longer just counterfitting the brain, but counterfitting the DNA, as well.

    Kev Baker: Quoting once again from this article:
    “We cannot achieve True AI until we understand actual intelligence. Intelligence has evolved as a means of nature to successfully guide us through an ever-changing environment. This gave rise to behavior, emotions, and consciousness. These critical factors must be taken into account in how we develop AI. This is the purpose of the Mindfire Foundation,”
    Now this has echoes of Geordie Rose with his Kindred Company
    , Anthon - the fact that its trying to mimic everything from the real world, in an attempt to give it, imo, consciousness.

    Anthony Patch: Right. And, you're tying Elon Musk in, we're tying in Geordie Rose, with his robotics company, Kindred. We're tying in Eric Ladizinsky with D-Wave. We're connecting Ben Goertzel - and his SingularityNET.io - in with the Blue Brain Project. As we said, they're all feeding their research in to essentially just one location, which is Switzerland.

    So that's what Mindfire is part of. And this is where they're going to merge the DNA research that we've talked about with such laboratories as the Institute for Human Longetivity, Inc., of Craig Venter, in La Jolla, California, and there are many others.

    Let me give you another touchpoint on the Human Genome. The Human Genome was mapped utilizing a synchrotron particle accelerator - a very small one compared to CERN - but identical in its design & operation & that was a UC Berkely. So, this mapping of the Human Genome utilized the synchrotron particle accelerator. The same thing is happening at CERN utilizing that, not only for human DNA research, but mapping for the human brain.

    All of these sychrotrons around the world are quantum computers.

    -----------------

    A.I. LIVES MATTER

    @28:00

    Anthony Patch: If the robot is acting warm & fuzzy... Let's say, in the beginning is acting like a adolescent & is non-threatening, then people cozy up to it - they embrace it. They think its wonderful to have an A.I. robot around. And yet, underpinning this is a very dark side to it. And there are plenty of people - not just me & you, Kev - that have been raising this issue that are leaders in the scientific arena who have said, "We need to be careful with A.I. And as even as far back as 2014, our friend Elon Musk said, "We are letting the genie out of the bottle."

    So, the debate goes on. But yet, A.I. continues to advance. And I think the debate is just for public consumption, and I don't really believes that these guys are afraid of A.I. because even Elon Musk is incorporating A.I. into his vehicles.

    So, to say 'The genie is out of the bottle'... to say that 'we're dancing with the devil'... any of those things is really just for public consumption. So, you really need to look beyond the little catch phrases that they put out & understand this is all a part of a strong delusion.

    Folks, consider AI & Artificial Organisms to be that strong delusion, because it further says that perhaps even the 'elect' might be deceived. Obviously, when we get to the point of Artificial Organisms, we're getting to the point of the beast. Not just the beast system, but the image of the beast being created. We're talking about an Artificial, if you will - a humanoid... maybe, a hybrid, if you want...

    Certainly it is something that is artificially constructed from artificial DNA. And when I say that, I mean, digitized DNA. In which you can arrange, literally, at the quantum scale, the building blocks of DNA into any type of living organism you want. It has to have living material to start with. It has to have a base material, but then from there you can re-arrange. They cannot create life. Only God can do that. But when they're talking about creating an artificial organism, when I look at that in relation to Biblical scripture, we are looking at the creation of the image of the beast. And that is something that Kathleen Urquhart & myself will be talking about at length on the 16th of December in our one-day webinar that is coming up.

    This is the image of the beast being created. It is artificial. And it is the strong delusion. People are being deluded into thinking that Artificial Intelligence is somehow the panacea - the solution - to all of our problems as humans. And its quite the opposite.


    -----------------

    @1:33:30
    Anthony Patch: You may recall things back in the 80s & 90s called "Multi-Level Marketing." Well this is what bitcoin essentially is - a sophisticated form of multi-level marketing.

    It is also a ponzi-scheme. Because, the essence of a ponzi scheme is that the scheme stays alive, and the returns on investment are paid out to investors so long as there are new investors come in at "the ground floor" - to keep supporting the system - so that it has a system of paying-out. This is what bitcoin & cryptocurrencies are - they're ponzi schemes. Very simple to explain.

    And people are buying into it. They are biting into the bitcoin. And, they're playing the game. And as long as people believe that there's value in these cryptocurrencies, they will continue to trade their dollars & euros, etc., for cryptocurrencies.

    Now again, as review, most every business, large & small, realizes that it either has to adopt existing cryptocurrencies, or create their own. This is what Amazon, as I said on Friday (17-November 2017) Kev, I believe that Amazon very quickly will be releasing their own form of cryptocurrency.

    We saw on Friday that the U.S. Federal Reserve announced that they are issuing a FEDCoin. So, a huge ponzi scheme. But it is for the purpose of teaching AI! Every transaction is done to teach A.I. - that's what is underneath, folks.

    And, we talked about transparency in A.I. in terms of the developers of different A.I. platforms putting out into the public domain all of their research. Why would they do that - why would they make public all of their expensive research?

    Well, the scenario is - the same as a drug dealer - giving away sample drugs so as to hook people who then must return to the drug dealer, as the source, of their next fix. This is exactly what cryptocurrency is. It is getting people sucked into a system that they are dependent upon, and believe in. And that they believe is going to pay them a large return in a ponzi scheme. And so, they continue to propagate the notion that there is value in cryptocurrency so that more people will come in and add money to the system.

    So, this is exactly the 'drug dealer on the corner' system. And it is the 'beast' system. And when cryptocurrency is the only form of currency, you must take the 'mark of the beast' to participate in it. So, the drug dealer has you hooked.
    _________@1:19:20__________

    11.16.17
    The Female Supercomputer Designer
    Who Inspired Steve Jobs


    The designer and artist Tamiko Thiel gets her due in a new show at MoMA.

    Tamiko Thiel working on CM-1 prototype, 1985. [Photo: © Tamiko Thiel]


    CM-2 with DataVault mass storage device, 1987. [Image: © Thinking Machines Corporation,
    1987/Steve Grohe (photo)/courtesy Tamiko Thiel]
    Last edited by turiya; 2nd December 2017 at 19:35.

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    Default Re: The Dark Secret at the Heart of AI

    In regards to the self driving cars, I saw a tv programme that actually made me weep. It was about the programming involved when multiple dangers detected. How does the car prioritize this?? Glad I'm not the one programming it, that's for sure - I weep for the programmers.

    Also they talked about how things like this might influence consumer decisions. Do I want a car that prioritizes ME? Or do I want a car that prioritizes children OVER me? Would anyone even want a car that has conditions programmed to kill them? It's just crazy to think about.

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    Default Re: The Dark Secret at the Heart of AI

    Quote Posted by petra (here)
    In regards to the self driving cars, I saw a tv programme that actually made me weep. It was about the programming involved when multiple dangers detected. How does the car prioritize this?? Glad I'm not the one programming it, that's for sure - I weep for the programmers.

    Also they talked about how things like this might influence consumer decisions. Do I want a car that prioritizes ME? Or do I want a car that prioritizes children OVER me? Would anyone even want a car that has conditions programmed to kill them? It's just crazy to think about.
    Interesting... Can you provide a link to that particular program video?
    I've always have been quite skeptical regarding driverless cars. Perhaps, its because that is what I do for a living.
    Have always felt it was all about control... Control over where people can go & when people can travel. I'm sure that there are people that feel it would be a great benefit... especially the elderly. Its common for the elderly to develop a difficulty in driving at night - a limited night vision.

    There is a Max Keiser Report in which they interview a man whose job is to monitor a driverless car that Lyft is developing. Its being tested in North Dakota. In that interview, it shows the driver doesn't touch the steering wheel. As, his job is to simply monitor the system & report what he finds.

    Funny, when Max asks him the question about him being in the transition to a driverless car and, eventually, he will not be needed to do his job... the driver didn't understand the point of the question. Max calls it the oncoming AI Apocalypse... @4:30

    Last edited by turiya; 23rd November 2017 at 18:56.

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    Default Re: The Dark Secret at the Heart of AI

    Quote Posted by turiya (here)
    Interesting... Can you provide a link to that particular program video?
    I wish I could but no, it was on my local cable TV and I have no idea what news I was even watching. The key word to look for is "ethics", and "ethical programming"

    I do web site development for a living, which is kind of like programming, and so I understand the need for control. If you don't control things, it makes a big mess! There are certain things though, that need human interaction. Without the human interaction, it would be dangerous. Safety first..... and for my own safety (and the safety of others!!)..... I want to control my car. ALL of it
    Last edited by petra; 23rd November 2017 at 19:19.

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    Default Re: The Dark Secret at the Heart of AI

    "No one really knows how the most advanced algorithms
    do what they do. That could be a problem."

    The CIA knows. The Ai builder just needs a proper diagnostics of coding and that solves the problem. It's not like the AI's algorithms are metaphysical and not trackable/surveillable with a proper setup.

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    Default Re: The Dark Secret at the Heart of AI

    Quote Posted by Omnisense (here)
    "No one really knows how the most advanced algorithms
    do what they do. That could be a problem."

    The CIA knows. The Ai builder just needs a proper diagnostics of coding and that solves the problem. It's not like the AI's algorithms are metaphysical and not trackable/surveillable with a proper setup.
    There's also the aptitude to understand the algorithms, and "how much of the CIA knows". Just thought I'd chuck a few more problems on there

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    Default Re: The Dark Secret at the Heart of AI

    With a normal, linear program, there is a logical order of steps that can be followed to see where the problem happened.

    Even so, any algorithms within the program are intact and indecipherable - they either give the right result or they don't.

    This sort of simulated learning does not have a linear program, instead it has a neural net of connections and sensor inputs. The program is as much in the architecture as it is in the coding. The logic of the program is both the linear coding and the physical system it runs on. The coding can still be tested and the source of the problem found ...but... the reason for any action is impossible to uncover because it is a function of algorithms, programming and architecture combined.
    Counter to our sovereign hope we're enthralled in mind by empty rote of frozen thoughts like knots in rope.

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    Default Re: The Dark Secret at the Heart of AI

    Quote Posted by Ernie Nemeth (here)
    With a normal, linear program, there is a logical order of steps that can be followed to see where the problem happened.

    Even so, any algorithms within the program are intact and indecipherable - they either give the right result or they don't.

    This sort of simulated learning does not have a linear program, instead it has a neural net of connections and sensor inputs. The program is as much in the architecture as it is in the coding. The logic of the program is both the linear coding and the physical system it runs on. The coding can still be tested and the source of the problem found ...but... the reason for any action is impossible to uncover because it is a function of algorithms, programming and architecture combined.
    Can you please elaborate on the point "the program is as much in the architecture as it is in the coding?" What do you mean by architecture-- the programming language? The operating system? The interface of the two?

    Also, if you would please, explain " the logic of the program is both the linear programming and the physical system it runs on"

    Are you saying these neural networks have a "life of their own" and output/result can't be determined?

    It almost sounds like multi-generation programming language and functions were derived that are too complicated for the programmer to determine the output, even given the input and the processing schematics that they, themselves, have coded.

    Without certain results, safety could be a huge issue!

    Maybe I just need to hear your explanations to understand better. Thank you for your patience in this process of increasing understanding.

    MM
    Last edited by Desert Dreamer; 24th November 2017 at 03:12.
    ~*~ "The best way to predict the future is to create it." - Peter Drucker ~*~ “To laugh often and much; to win the respect of intelligent people and the affection of children...to leave the world a better place...to know even one life has breathed easier because you have lived. This is to have succeeded.” -Ralph Waldo Emerson ~*~ "Creative minds always have been known to survive any kind of bad training." - Anna Freud ~*~

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    Default Re: The Dark Secret at the Heart of AI

    Sounds to me like it's impossible to reproduce the exact conditions. If the exact action cannot be reproduced, then of course it's impossible to uncover the reasoning behind that action in order to debug it further.

    Maybe I am way off, I'm just repeating the typical problem that I run into every time I try to debug something.

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    Default Re: The Dark Secret at the Heart of AI

    In a normal computer and linear program each line of the program is a sequential step in a logic tree designed to accomplish some given task - like a word processor for example. Every possible entry of the keyboard is accounted for in the program and various options are available but each must be accessed in sequential order and one at a time. This means that every time a keystroke is detected the program runs the entire logic tree until that particular keystroke and the resulting action is determined and executed. Every time a new entry is made, the program runs through its entire line by line code.

    Although in a learning machine there is a set of instructions, it does not account for every eventuality. Instead, an optimal range of desired outcomes are listed and the program attempts to match those criteria. No method of achieving the outcome is listed and the machine must find its own successful outcome by simple trial and error. The learning is achieved as the errors smooth out and the proper output begins to appear as if by magic. It is not intelligence, it is mimicry and repetition.

    Out of this clever but simple method more sophisticated techniques have been added, such as human training, where the machine's inputs are hooked directly to a human instructor who goes through the required motions until the machine learns to mimic the set of movements. One example of this type of learning is the painting robot in the car plant.

    The architecture side of the machine is a chip that has been designed specifically for the task of simulated learning. Its connections are not usually addressable. That is, its memory slots cannot be accessed directly by the programmer. Instead, the connections in the chip are multiple and each memory slot has a connection to every other memory position. With these over-abundance of connections, inputs and outputs mix with no apparent order. But as the outputs come out they pass through a linear program. This is the program that controls the output. Not by listing every eventuality the machine might encounter but by describing a set of acceptable outcomes. The machine just churns away until it gets the right output by chance. When it gets the right output it 'remembers' the actions that gave it those results and begins a process of optimizing its performance to correctly determine the proper course of action for every input eventuality on the fly.

    This is what gives it the simulated perception of intelligence, but it is not. But it could one day 'accidentally' become sentient if the machine is sophisticated enough.
    Counter to our sovereign hope we're enthralled in mind by empty rote of frozen thoughts like knots in rope.

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    Default Re: The Dark Secret at the Heart of AI

    Quote This is what gives it the simulated perception of intelligence, but it is not. But it could one day 'accidentally' become sentient if the machine is sophisticated enough.


    Osho Speaks on Artificial Intelligence


    Osho,
    My friend, who has a PhD in computing, and whose thesis was on ‘artificial intelligence’, says that man is a biochemical computer and nothing more.

    The Buddha has said that all things are composite and there is no self, no soul, no spirit, no ‘I’, which seems to agree with my friend’s viewpoint. Could you please help me, because I feel that there is something missing from these views but I can’t see it myself.
    Prem Hamid,

    Man certainly is a biocomputer, but something more too. About ninety-nine point nine percent of people it can be said that they are only biocomputers and nothing more. Ordinarily one is only the body and the mind, and both are composites. Unless one moves into meditation one cannot find that which is something more, something transcendental to body and mind.

    The psychologists, particularly the behaviourists, have been studying man for half a century, but they study the ordinary man, and of course their thesis is proved by all their studies. The ordinary man, the unconscious man, has nothing more in him than the bodymind composite. The body is the outer side of the mind and the mind the inner side of the body. Both are born and both will die one day.
    But there is something more. That something more makes a man awakened, enlightened, a Buddha, a Christ. But a Buddha, or a Christ, is not available to be studied by Pavlov, Skinner, Delgado and others. Their study is about the unconscious man, and of course when you study the unconscious man you will not find anything transcendental in him. The transcendental exists in the unconscious man only as a potential, as a possibility; it is not yet realized, it is not yet a reality. Hence you cannot study it.

    You can study it only in a Buddha, but even then studying is obviously very difficult, just very close to the impossible, because what you will study in a Buddha will again be his behaviour. And if you are determined that there is nothing more, if you have already concluded, then even in his behaviour you will see only mechanical reactions, you will not see his spontaneity. To see that spontaneity you have also to become a participant in meditation.
    - A computer cannot feel boredom,
    - A computer cannot feel meaninglessness,
    - A computer cannot experience anguish.
    - A computer cannot start an enquiry about truth,
    - A computer cannot renounce the world and become a sannyasin (disciple),
    - A computer cannot go to the mountains or to the monasteries.
    - It cannot conceive of anything beyond the mechanical –
    and all that is significant is beyond the mechanical.
    Psychology can become only a real psychology when meditation becomes its foundation. The word ‘psychology’ means the science of the soul. Modern psychology is not yet a science of the soul.

    Buddha certainly has denied the self, the ego, the ‘I’, but he has not denied the soul and the self and the soul are not synonymous. He denies the self because the self exists only in the unconscious man. The unconscious man needs a certain idea of ‘I’, otherwise he will be without a centre. He does not know his real centre. He has to invent a false centre so that he can at least function in the world, otherwise his functioning will become impossible. He needs a certain idea of ‘I’.

    You must have heard about Descartes’ famous statement:
    cogito ergo sum – I think, therefore I am.”
    A professor, teaching the philosophy of Descartes, was asked by a student, “Sir, I think, but how do I know that I am?”
    The professor pretended to peer around the classroom. “Who is asking the question?” he said.
    “I am,” replied the student.
    One needs a certain idea of ‘I’, otherwise functioning will become impossible. So because we don’t know the real ‘I’ we substitute it by a false ‘I’ – something invented, composite.
    No biocomputer or any other kind of computer
    has any idea of self or no-self.
    Buddha denies the self because to him ‘self’ simply is another name for the ego, with a little colour of spirituality, otherwise there is no difference. His word is anatta. Atta means ‘self’, anatta means ‘no-self’. But he is not denying the soul. In fact he says when the self is completely dropped, then only you will come to know the soul. But he does not say anything about it because nothing can be said about it.

    His approach is via negativa. He says:
    You are not the body, you are not the mind, you are not the self. He goes on denying, eliminating. He eliminates everything that you can conceive of, and then he does not say anything what is left. That which is left is your reality: that utterly pure sky without clouds, no thought, no identity, no emotion, no desire, no ego – nothing is left. All clouds have disappeared… just the pure sky.
    It is inexpressible, unnameable, indefinable. That’s why he keeps absolutely silent about it. He knows it that if anything is said about it you will immediately jump back to your old idea of the self If he says, “There is a soul in you,” what you are going to understand? You will think that, “He calls it soul and we call it self – it is the same. The supreme self maybe, the spiritual self; it is not ordinary ego.” But spiritual or unspiritual, the idea of my being a separate entity is the point.

    Buddha denies that you are a separate entity from the whole. You are one with the organic unity of existence, so there is no need to say anything about your separateness. Even the word ‘soul’ will give you a certain idea of separateness; you are bound to understand it in your own unconscious way.

    Hamid, your friend says that “Man is a biochemical computer and nothing more.”

    Can a biochemical computer say that? Can a biochemical computer deny the self, the soul? No biocomputer or any other kind of computer has any idea of self or no-self. Your friend is doing it – certainly he is not a biochemical computer. No biochemical computer can write a thesis on artificial intelligence! Do you think artificial intelligence can write a thesis about artificial intelligence? Something more is needed.
    - A computer cannot have any awareness.
    - A computer is incapable of feeling silence.
    And these are the qualities which prove
    that man has something more than artificial intelligence.
    And he is absolutely wrong in thinking that Buddha says also the same thing:
    … That all things are composite and there is no self no soul, no spirit, no ‘I’.
    He is wrong to think that Buddha agrees with his viewpoint – not at all. Buddha’s experience is of meditation. Without meditation nobody can have any idea what Buddha is talking about. Your friend’s observation is from the standpoint of a scientific onlooker. It is not his experience, it is his observation. He is studying biochemical computers, artificial intelligence, from the outside. Who is studying outside?

    Can you conceive two computers studying each other? The computer can have only that which has been fed into it; it cannot have more than that. The information has to be given to it, then it keeps it in its memory – it is a memory system. It can do miracles as far as mathematics is concerned. A computer can be far more efficient than any Albert Einstein as far as mathematics is concerned, but a computer cannot be a meditator. Can you imagine a computer just sitting silently doing nothing, the spring comes and the grass grows by itself…?

    There are many qualities which are impossible for the computer. A computer cannot be in love. You can keep many computers together – they will not fall in love! A computer cannot have any experience of beauty. A computer cannot know any bliss. A computer cannot have any awareness. A computer is incapable of feeling silence. And these are the qualities which prove that man has something more than artificial intelligence.

    Artificial intelligence can do scientific work, mathematical work, calculation – great calculation and very quick and very efficiently, because it is a machine. But a machine cannot be aware of what it is doing. A computer cannot feel boredom, a computer cannot feel meaninglessness, a computer cannot experience anguish. A computer cannot start an enquiry about truth, it cannot renounce the world and become a sannyasin, it cannot go to the mountains or to the monasteries. It cannot conceive of anything beyond the mechanical – and all that is significant is beyond the mechanical.
    A policeman starts chasing a car after noticing that the driver is a computer, a robot – wearing a hat, smoking a cigar and driving with one hand hanging out of the window.
    He finally succeeds in stopping the car. He approaches it and sees to his surprise that there is a man sitting next to the computer.
    “Are you mad?” exclaims the officer, “letting your computer drive?”
    “Excuse me, officer,” replies the man, “I asked him for a lift!”
    Yes, in stories it is possible, but not in reality.
    Mr. Polanski enjoys playing with cuckoo clocks. One rainy Sunday morning he takes his cuckoo clock apart and puts it back together again.
    At twelve o’clock the family gathers, waiting for the pretty little bird to sing its song… nothing happens. They wait till one o’clock – no cuckoo. At two o’clock they are still waiting for the bird to appear. Finally, at three o’clock, the little door opens and the cuckoo comes out.
    “Dammit!” it squeaks. “Do any of you guys know the time?”
    Osho, I Am That, Chpt 4, Q 1
    Last edited by turiya; 26th November 2017 at 02:35.

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    Default Re: The Dark Secret at the Heart of AI

    Lynette Zang:
    "I want to know what the bankers have planned for us... hyperinflation is happening now... And I'm reading right now a report from the IMF on the advantages of taxation in a completely digital world, where they're talking about having the ability to look at your whole-life-time of earnings, spending, wealth accumulation & how easy it is to do that will this blockchain technology, so they can really do a nice wealth-transfer from one group to another easily. And create all these complicated tax structures with this blockchain system. But it is not outside the system. It is the system.

    While you'll see bitcoin, or any of the cryptos making new highs, etc. - that's to get you into the system. It is not outside the system - it is the system. Its got to crash, because that's the way they conclude the transition."
    Guess Who's Spewing the Ultimate FUD
    (Fear - Uncertainty - Doubt)
    (Nov 22, 2017)
    _______________
    The following is a linear graph on when all of the banks & the bigger companies & major corporations, including DTC - the legal registered owner of all those fiat products - started to get involved in bitcoin & the blockchain technology & the other cryptos.




    ____________________________
    King of BlockChain Peter Thiel - #bitcoin
    #Ripple #Etherium #Aragon #Augur

    (Nov 23, 2017)

    Peter Thiel is being considered to chair
    Trump’s intelligence advisory board


    Posted Sep 20, 2017 by Taylor Hatmaker



    The Trump administration’s PIAB site is not functional at this time, but the Obama administration offers its archived description of the board’s role:
    The Intelligence Oversight Board oversees the Intelligence Community’s compliance with the Constitution and all applicable laws, Executive Orders, and Presidential Directives.

    It complements and supplements, rather than duplicates the oversight roles of the Director of National Intelligence, Department and Agency Inspectors General and General Counsels, and the Congressional Oversight Committees.
    Thiel might be controversial, but he’s a logical fit for the key intelligence advisory role. His data mining company Palantir is probably most famous for its contracts with government intelligence agencies, and he’s a longtime Trump ally who has never wavered in response to the kind of controversial choices by the Trump administration that provoke outspoken backlash from most corners of Silicon Valley. Under a normal presidency, his investment in companies with active government contracts might stir up conflict of interest questions with the PIAB role, but it’s hard to imagine that being a hurdle under a president who actively promotes his family business from the highest office in the land.

    As a senior aide to the White House told Vanity Fair, “Peter has indicated that if he takes the P.I.A.B. position he intends to take a comprehensive look at the U.S. intelligence community’s information-technology architecture.” The source added that “He is super-concerned about Amazon and Google [and Facebook]… He’s concerned about the monopolistic tendencies of [all three] companies and how they deny economic well-being to people they disagree with.” If the latter part of that quote holds up, it’s a strange and telling priority set for the man who put Gawker out of business. It also has way more to do with regulation than intelligence, but Thiel’s vision of a governmental paradigm shift has always been broad.
    Source
    Last edited by turiya; 26th November 2017 at 00:24.

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    Default Re: The Dark Secret at the Heart of AI

    Latest Jason Goodman interview with Quinn Michaels.... the connection between cryptocurrencies & A.I.....

    Crypto Conspiracy and the Road
    to the AI Singularity

    (Nov 25, 2017)
    @11:00
    Quinn Michaels:
    The crypto conspiracy is that when I research alot of the bigger coins they're all backed by huge, mammoth dot coms, or movie studios - like Time-Warner is a backer in Discord & other people who are backing Discord chatter are also backing cryptocurrency.

    And so, all these companies start creating a spiderweb trail of dots. And, when you connect them, it leads you to believe... that when you put Artificial Intelligence in the center of it, its a big giant conspiracy of all the 'dot coms' & everyone in the world keeping a secret & spending all out tax money on all these crypto miners & these A.I. research programs. Because, I've calculated between Peter Thiel & Marc Andreessen & just Google Ventures, they've dumped somewhere in the vicinity of $10+ billion dollars into cryptocurrency in the last 5 years.

    Jason Goodman: For so many people cryptocurrency its still a new thing. Most people have heard of Bitcoin, Litecoin, Ethereum - those are the biggest. I've been looking at some of the alternative ones we spoke about - Tezos thing. And there's something here called Dash, which is digital cash...

    I was looking around at all these different things. And it seems that there are new, crazy cryptocurrencies popping out all the time. We just heard from the founder of Wikipedia saying these intitial coin offerrings are essentially a scam. The M.I.T. Technology Review has this article which is saying Hijacking Computers to Mine Cryptocurrency is All the Rage. I speak to Charles Ortel about cryptocurrency and he is very, very wary of it. He doesn't trust it he feels that its a scam. Now, we've got articles from major news sites - CNBC, MIT - talking about the ways in which these things are being operated by scammers. And you've identified this crypto conspiracy. But yet, you're still dealing in cryptocurrency, right?


    Quinn Michaels: I do because I'm learning how the systems work. And I'm watching the markets & I'm watching how things grow. And I allow people to send me cryptos as offerings. I don't think its bad. I wasn't so agreeable to the technology before I did alot of deep research & found out the 'real crypto' is made by people at Stanford. Its made by people at M.I.T. & its back by the biggest dot coms in the world.

    Jason Goodman: What's the 'real crypto'?

    Quinn Michaels: The 'real crypto' is what they're going to come out when their crypto conspiracy succeeds. Certain things should stabilize - the ones that all the dot coms have invested billions of dollars in should stabilize. And basically, it looks like they're setting up the guys that all all the patsy schemes to force regulation later. So that way, all their big companies are set up to transfer bitcoin into credit cards & do - like coinbase's New York Stock Exchange backing - so when the crime happens, you have all these people in place that are saying - "Hey look, we got in on it early! And now, we have all these services to provide these big businesses." - Because, Peter Thiel & Andreeson are all making enterprise cryptocurrency tools.

    They have got way too much money invested in this just to let it crash. So it looks like - because Peter Thiel follows scapegoating logic, it looks like they've invested with the intention to get people all sucked into the ponzi schemes - to force regulation - to benefit them later. You know, kind of like - create the problem, then offer the solution. Like, "Hey, we have this new technology that solves your problems from these 'scam' coins.


    Jason Goodman: Oh... Well, the classic Hegelian dialectic, right?
    Last edited by turiya; 28th November 2017 at 22:35.

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  29. Link to Post #15
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    Default Re: The Dark Secret at the Heart of AI

    From the end of September.... Lynette Zang on the cryptos....

    The Drive to Cryptocurrencies,
    Who is Really Driving This Bus?

    (Sep 28, 2017)
    Officially, there is only 4 cents in value left out of the original 100 cents and as the value of the dollar has declined, so have interest rates. So here we are at the end of the currencies lifecycle and the only place to go now is to attack principal and that’s where negative interest rates fit in. Thus the push to cyber space. There are those that believe cryptocurrencies bypass central banks. But what if they don’t? What if they actually support the goals of the established system? What would that mean if everything we earned, owned and spent was controlled by a small group of technocrats? Today’s webinar explores these questions and more.

    https://www.itmtrading.com/blog/driv...-lynette-zang/






    Last edited by turiya; 30th November 2017 at 23:57.

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    Default Re: The Dark Secret at the Heart of AI

    SGT video shows you what is real wealth... and just WHO it is that is the richest in the world...

    Rothschild TRILLIONS Quantified
    (Nov 27, 2017)

    VIDEO
    Do you honestly believe Jeff Bezos is the world's richest man? A guy who started selling books over the internet 20 years ago!? History tells a different story. The Rothschilds are worth several hundred TRILLION dollars. Here's the quantifiable numbers. It's a simple matter of math, market manipulation and compounding interest. The family bragged about the wealth they made as a result of the Battle of Waterloo. They even bankrolled a Hollywood movie about it in 1934 starring Boris Karloff as Nathan Rothschild, 'The House of Rothschild' which you can watch here: https://www.youtube.com/watch?v=MqCTv...

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    Default Re: The Dark Secret at the Heart of AI

    As you can see, the cryptos are now taking off at rocket-speed... believe it - the take down of the economy will happen in a sudden flash... catching everyone totally off-guard, with no time to really think rationally about what will be taking place - the shift into a cashless monetary system...

    Dave of X22Report.com has been watching the indicators as to when the cabal, the Deep State, the Banksters are preparing & getting ready to take the economy down & implement this new cashless system... cued the video to play @ 11:50

    The Cabal Has Entered The Second Stage Event,
    The Setup Is Almost Complete - Episode 1435b
    (Nov 29, 2017)

    VIDEO

    https://youtu.be/i9PejnihHhE?t=11m50s
    Last edited by turiya; 2nd December 2017 at 00:51.

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    Default Re: The Dark Secret at the Heart of AI

    A bit of a spat going on between Quinn Michaels vs Clif High... Quinn's initial video that Quinn made criticized Clif High has since been taken down... Clif, who has been promoting Bitcoin & other cryptocurrencies for quite some time, does have a tendency to overdo his own knowledge base... just a personal observation...

    Btw, here's one of the video segments of Clif High that Quinn Michaels is referring to (Clif initially calls Quinn an idiot): https://youtu.be/EueDsKi25vo?t=20m20s

    The following vid was created by a third party... no doubt on the side of Clif - the opposing side to Quinn - which suggests it would be probably the character known as Defango... I suspect Degango has recorded remnants of it & other of Quinn Michaels vids... Nerds get testy with each other just like other non-nerds...

    Quinn Michaels Vs Clif High Pt 1
    (Nov 17, 2017)
    From the Comments section:

    quinn michaels 1 week ago

    wow... you guys really don't know what you are talking about. You could have invited me to your little conference so I could help with your incorrect understanding.

    Here is a blip from the actual Etherium paper... from the people who wrote it:
    Ethereum, taken as a whole, can be viewed as a transaction-based state machine: we begin with a genesis state and incrementally execute transactions to morph it into some final state. https://ethereum.github.io/yellowpaper/paper.pdf
    You guys might want to read that paper from Etherium before you start talking out your butts. I'd suggest you think twice before posting anymore videos about me cause if I see anymore I'm going to make all of you look really bad.
    In the meantime, down below will be shown the recent Jason Goodman interview of Clif High...

    Clif High On Bitcoin, AI and
    the Future of Cryptocurrency

    (Streamed live 12 hours ago - Dec 1, 2017)
    @1:57
    Clif High: I've been in bitcoin since before the Mt Gox crash. I remember the great day when bitcoin achieved parody with the U.S. dollar one for one. So, been in it a long time.

    Jason Goodman: When did bitcoin start?

    Clif High: Nominally, it began circulating in late 2009 in the form of a 'white paper'. And so, bitcoin was an idea then, an idea of a currency that ran on a thing called the 'blockchain' which was a consensus machine. And that consensus machine could operate across time zones, across geographic barriers instantly, or close to it. And, we could have a system where we could have an electronic currency that couldn't be double-spent because of the consensus machine that was the blockchain.

    Jason Goodman: And the blockchain, that we've established, is basically a ledger that is stored on every computer that's involved with bitcoin, is that correct?

    Clif High: No, it's a ledger that's stored in every computer that is mining or has a copy of the entire chain.

    So, it used to be that when you got into bitcoin, you would download a bitcoin wallet. And the first thing that it would do would be to connect to the blockchain & take 5 or 6 days, depending on when it was... It would then connect - you had to let it run until it had an entire copy of the chain on your pc - and then it was relatively fast. Since then, we've got a bit more diversified in our understanding of this. We've separated the concept of the wallets from the mining - mining is done by specialized software, etc. So, its not fair to say that every machine that has a bitcoin on it has a copy of the blockchain, although many, that are old, do.

    Jason Goodman: To be clear... You & I became aquainted, most recently, because of some of the controversial statements that Quinn Michaels has made on this channel. And, I understand that you've disagreed, in large part, with some of the things that Quinn said. Quinn was basically saying that A.I. & cryptocurrency are tied together, and you say that's not the case.

    Clif High: Correct. That's not the case. AI can be quite sophisticated. Its still a brute-force software that just goes through & makes choices based on the inputs. But the blockchain is more solid, but at the same time, far less sophisticated. The blockchain is a consensus algorithm, and that's all it is. And this algorithm is shared in software that's run on the mining machines. And they're all synched on atomic clocks.

    And that's essentially all that it is. To merge the idea of A.I. in with the software that is the blockchain &/or the cryptocurrencies does everthing a disservice. It muddies the water for those that are afraid of A.I. that have watched too many movies of... you know, the giant robot that comes & eats us all. Or, the computer that decides its alive... that kind of thing. Anyways, those people become scared. They don't want to mess with the cryptocurrencies or get involved. And it also denigrates the A.I., which is a very sophisticated level of programming involving collection of data that they refer to as 'machine learning' but the machine doesn't really learn... We just stuff databases with finer granularity that we can sift through on a finer level - really, is all that it amounts to.

    So, I did have some dispute with the statements that were made, yes.

    Jason Goodman: Sure. And on your website, HalfpastHuman.com, you've been involved in predictive linguistics & artificial intelligence plays a role there somehow, right? You've been doing AI stuff there for quite a while?

    Clif High: I began doing AI when I first got into programming on my own system using a language called Prolog. It was one of two languages back in the day - late '80s / early '90s - that was touted as being an artificial intelligence language - the other one being Lisp. I chose Prolog for a number of different reasons, but its programming & logic were for predicate calculus. And it was used to make, what we called at the time, Expert systems. And an Expert system is basically a brain dump from somebody that knows how to do something to a Coder that encodes it in software.

    For instance, you can do a Brain dump on a mechanic & he could diagnose... and we could do a chunk of software that would do diagnostics on a car based on what a human said about it - the kind of noises, and this sort of thing. So all it is, is that person's expert analysis translated into software. And so AI at the time, was called Expert systems. It was a lot less sophisticated than now, because it was all, basically, manual - one human had to tell another human who typed it all into an encoding platform we called software, and then it would run & we'd get feedback from it.

    So, I've been doing this since about '89. And I use some of the aspects of neural.... of natural language processing in my own system for predictive linguistics, which these days is called Sentiment Analysis. The large corporations don't hire predictive linguistic experts, they hire people that are expert in Sentiment analysis software, or some language around that kind of a different categorization of the subject. So, you'll see that its well established with all the corporations that are doing any form of marketing, from Google all the way down to your local tire company.

    Jason Goodman: So Sentiment analysis, that's like some computer program is looking at some comments on a youtube video and saying, "Hey, some angry about this, let's put some trolley comments in along this line."

    Clif High: Not quite that sophisticated. The software that I've run into... that is out & about, isn't so definitive as to say they're angry. It comes back with results that are more nuanced, where it says,
    • "This comment shades towards negative." Or,
    • "This comment shades towards positive." Or,
    • "This comment appears to be neutral." Or,
    • "This is a complex comment that has both aspects."
    And then you have a further level of an algorithm that decides what to do - based on whether you're a 'bad guy' or you're trying to market, or whatever.

    Jason Goodman: There was a recent article by Business Insider that said that bitcoin mining was going to consume all of the world's electric power generation, or something, by 2030. What do you think about this?

    Clif High: Its hyperbole - basically, bullsh!t, because a bitcoin miner is just a bunch of graphics cards. In order to consume all of the electricity on the planet, imagine how many graphics cards would have to be in operation? You'd have to have at least 50-80 in your place right there, I'd have to have another couple hundred here, and everybody on the planet would have a few hundred - just to be able to get this going.

    Its a FUD - fear, uncertainty & doubt. And its a way of click-bait, a way of getting eyes to your particular message.

    Jason Goodman: So you don't think that this is a significant concern... that the growing demand for bitcoin will be taxing on the world's electricity supply? I mean, people would stop mining if it was costing more for the electric bill than the value of the bitcoin, right?

    Clif High: Correct. Correct. Also, the mining operations have change dramatically in the last seven years. When it was first started off was basically a bunch of people that had spare computers sitting around, wrote alot of their own software, etcetera. But there's no reason to suppose that in order to supply bitcoin, we need to have vast quantities of miners. This is not like a forest & we're dealing with firewood, right? We don't have to grow more trees in order to produce more wood for more people just because there's demand.

    Here, we have the ability to just do stuff within in the same environment & create more bitcoin just based on the algorithms involved. So, we're going to create the bitcoin just because we're mining. We're only going to mine at a certain rate, no matter what. So, its an instance of... we've got 17+ million bitcoin, now. Say that demand went up 10-fold, it just means we're going to have to share smaller & smaller bits because we're not going to get anymore bitcoin any faster no matter how many miners we put on.

    Jason Goodman: You mean fractions of bitcoin

    Clif High: Correct. Correct. Satoshis. And see, the thing is that bitcoin is controlled at its core by the Consesus algorithm of the blockchain, but also by this thing that's called the Hash. And the Hash is an algorithm that encodes & encrypts the private & public keys involved in the transaction. That Hash increasing becomes more difficult over time. And so, the harder you mine bitcoin, the more it resists being mined.

    It does not make any sense to envision a world where you have to put more electricity into trying to do it faster.

    Jason Goodman:
    So, is this just disinformation being put out by people who are owning banks, and have an interest in keeping the petro-dollar & fiat currencies... [/COLOR][/I]

    Clif High: Its only speculation. The only we can say for sure is that it was click-bait from that [Business Insider] website, because they've hot all those ads there. They're trying to use whatever they can to get you to come & read their site.... There was a provocative headline... you know.

    Jason Goodman: Well, bitcoin right now is at an amazing $10,790, according to Coinbase. I know alot of people have different exchanges that they like to look at. And you know, the other day I went down to Wall Street & made a video, "Is Wall Stree Bullish on Bitcoin". I'm sure you won't be surprised to learn that they were not bullish on bitcoin at all...
    @14:00
    People are fearful of it [blockchain-cryptos] being hacked, and you mentioned the Mt Gox situation. That was a hack, wasn't it?

    Clif High: Nope. Nope, it was not a hack. Okay, Mt Gox started out as a trading site for intangible goods based around a role-playing game. It was something... the game online... mystery, or something like that. It was a card game & you could sell & swap the tokens within the game, and then they added on bitcoin.

    When they did that, they made a certain strategic decision. The decision was to not always have 100 percent of the bitcoins that everybody was buying. What they actually did..... they would do it, initially, they maybe had someone buy 6 bitcoins, and they bought 10. Then thereafter, they had somebody buy another 7, only they're not moving them off the exchange, they just left the bitcoins there. It was fractional reserve bitcoin sales based on...

    And so, it was all internal. They claimed it was a hack in order to get out from underneath this inverse pyramid. They claimed it was a hack. There was no hack involved. What had happened was they had not bought enough bitcoin. People were trading the bitcoin back & forth at a furious rate on Mt Gox.

    One day, Mt Gox got a situation where someone had amassed alot of bitcoin & then tried to take them off the exchange, and some of them didn't exist. And so, everything crashed at that point.

    The blockchain per se can't be hacked. It theoretically could be taken over, or if you got 51% of all the miners to agree, then they could change software, or they could decide to do something & they would own the blockchain. But short of that, you can't in any way alter the blockchain itself. Bitcoin rides on top of the blockchain. And it can't be hacked per se, either. You could do something stupid. You could take your private key, print it out, show it to everybody online, and you'd lose your bitcoin. Because, you were stupid & you shared private information. But your wallet on your pc cannot be hacked by someone squirreling through to come & take your bit coin - like the NSA has backdoors in all of the pcs, etc., and they can come & steal all of your bitcoin.

    And theoretically, they maybe could - but the actual practicality of it is an absurd idea. Its just not going to happen. If you're not connected, obviously you can't be hacked. The use of that word [hacked] relative to the blockchain really annoys me because its so inaccurate. We've not yet had a hack on any of the blockchains. We've had some spectacular screw-ups, okay. And this is bound to occur with software in anything that humans do. And, some of them are quite interesting. I happen to know of $14 million worth of Etherium that's locked up behind a smart contract that they can't figure out how to open up. Ha ha ha!

    If you got bitcoin, and you buy it off the exchange, and it makes a transaction on the blockchain, and it goes to your pc & your pc is destroyed, your bitcoin is not destroyed, as long as you have elsewhere - the keys to that bitcoin or the password & stuff that allows you to recreate that wallet in its entirety to connect to the blockchain, it can recover & kickup from where you were. And this is true no matter where on the planet you end up having to be.

    So in that sense, its much better than gold or silver or cash that's sitting in your house, and a giant wave or a storm or something, comes & takes your house out. Well here, if that occurs, you just walk on over to some place that's dry & warm & stuff - go into a motel - open up your laptop, download another wallet, recreate the whole thing & you're back in business.

    Jason Goodman: Now let's get back to A.I. for a second. Because another topic that we've been talking about a bit is "strong A.I." And that has been coming up quite alot lately with Sophia from Hanson Robotics. But of course, you know, Sophia is the 1st robotic citizen of Saudi Arabia. But there is something with blockchain... I've heard one of the guys who is the principle at SingularityNET - Dr Ben Goertzel - they've got this AGI token. Does that have nothing to do with cryptocurrency or blockchain.

    Clif High: Sure. But its an attempt to tokenize an AI market. Okay, these guys are not saying they're going to merge AI with the blockchain & your coins are at risk from AI. SingularityNET is, in fact, attempting to create a marketplace for AI software. And have a lot of people cooperate by creating AI software, putting it out there to do work, and then getting paid through the software doing the work through their platform. And their platform is going to use those tokens as its means of expression between the parties involved.

    It would be like if I were to take part of my software & have a little predictive linguistics module & offer it for 'work for hire' on Singularity - I could do that. And then it would go out and negotiate contracts & do work for people - its sort of like having an API - Application Programming Interface - into your software that you then allow people to use for money.

    Jason Goodman: So we recently heard a statement from the founder of Wikipedia, from perhaps CNBC.... And he's saying that "Initial coin offerings, although they're the hotest craze in cryptocurrency, they're an absolute scam." That's from Jimmy Wales. What do you think about that statement?

    Clif High: Not much. I mean, that's his opinion. I don't find that to be the case. Actually, its a new - ICOs, as opposed to IPOs - its a new take on funding. And it cuts out the banks. It cuts out a huge... its called Disintermediation. It slices out a huge level of the middle. Its going to do away with all the people that made bonuses on offering shares of somebody elses company to their clients, and taking money from all the parties in the transaction in all these different areas, okay.

    So, its going to cut out all the Wall Street people that are in the middle of IPOs. IPOs are dying as a funding mechanism. And the reason they're dying has to do with their structural incoherence & incompetence in today's age, and the costs that are involved that need not be there. And then we have an electronic, easier to understand, peer-to-peer method that allows funding to occur.

    And so in that sense - no, it's not a scam - its a legitimate way to fund an enterprise of any kind, these days, in terms of a commercial offering. If you're going to produce a product, if you're going to come out with new software, if you're going to send rocket ships to the moon, you don't want to mess around with IPOs & have bankers take 35% of everything that's involved.

    If you can also lower everybody's cost & get more money, you'd be foolish not to. And, there's a benefit also to the investors, here. In usual IPOs, you have all these lock-up periods, times you can't sell the shares that you've put money into, the returns... the huge returns - 50, 60, 80 baggers - they call them in Wall Street, right? Those go to the venture capitalists that are patient, that have managed to corner capital, and keep it locked up, and then feed it out under these particular circumstances. And so, those kind of gains are never seen by the ordinary guy who buys into the IPO, and then basically gets a little tiny returns, if any at all, on that investment within the system.

    Here, we have in a different type of structure, where instantly that the ICO is done & the coin is available, in some cases, it can be traded. So, if you bought, and five minutes later you think you've made a big mistake, someone is going to offer you money at a discount to take that mistake off your hands - betting that later on it will turn out to not be a big mistake - and they'll make money on it. And, maybe individuals will think "its not a mistake, maybe I'll buy a couple more." And they hold onto these things, and they're small investors, and they don't necessarily meet the qualifications for sophisticated investors regarding, you know, as the SEC, etcetera, would see it. But nonetheless, these people are ones making the 50, 60, 70 & 80, and sometimes, hundred of thousands of times return on their investment. And the firms are getting money in a cleaner, easier fashion.

    The whole thing can be managed with smart contracts. If you don't get a certain amount, you can undo it all & send all the money back. When did that ever happen with an IPO? ...where... Oh, you don't meet the float you wanted to get... And so, you decide, "Okay, we don't have enough to do the deal." And everybody gets their money back.

    Its never happened in any bank that I know of.

    Jason Goodman: Okay. Another that happened when I was doing "Is Wall Street Bullish on Bitcoin", I went down there, because when I woke up in the morning, bitcoin was over $11,400 or something incredibly high. And when I was doing that Livestream, people on the stream were telling me that bitcoin crashed. And here's an article right here where it says bitcoin crashed... What this is talking about, of course, is this case the U.S. vs Coinbase, where the IRS successfully sued Coinbase, saying that they want private information about people who are buying or selling more that $20,000 worth of cryptocurrency on the Coinbase exchange, there.

    What do you think about all this?


    Clif High: It really muddies the water, legally. Because, the IRS has previously considered cryptocurrency to be a capital gains category commodity - not a currency. Now, they're starting to try & extend the Know your customer (KYC) laws from banking over to the cryptocurrency exchanges, as though these were, in fact, currencies. Okay...

    Jason Goodman: But isn't it suppose to a currency?

    Clif High: No. The government says, 'No.' That these are not currencies. They don't want competition to their monopolistic offering of the dollar, correct. Right, they got a monopoly on the dollar currency, and they don't want it abrogated at all. And so they've always declared that cryptocurrencies were fine - go out & play all you want. But its like buying magic pumpkins out of a game for the next time play the game. Its a capital gain expenditure, right. Its a $400 million market. And that maket's been going on for 15 or 20 years in that level of activity. IRS has always treated that as a captial gains endeavor.

    So now, it sounds like what they're trying to do with Coinbase is A) they're understanding how fast its changing - the whole fiat, the whole financial sector landscape underneath them that accounts for 18% of the U.S. economy, B) it sounds like they're trying to start thinking of these things as currencies, and C) it sounds like they've made a deal with Coinbase. And Coinbase, effectively said $20,000 is the limit - "We're not going to give you any information on the people that are below this." They've worked out a solution. Which I think is, again, muddying the waters, in terms of how we think about this. Because it seems as though a few years down the road, IRS will be considering these things to be actual currency. And it will be going through a kind of a Forex kind of an approach for taxation, as opposed to the straight capital gains comodity kind of a taxation. And this is going to be a big shift - is in fact a big shift - is in fact occurring now.

    Actually, it doesn't bode very well for the government. Its going to drive them crazy trying to decide what amount can be taxed & what kind of transaction shift with cryptocurrency, is where you can have trading transaction that's settled... okay, unlike Wall Street - where nothing is settled since probably 1999 - there's been no actual trading of stock certificates, or bond certificates, or any of that. Everybody dumps everything that they buy on their 401k to a company called CEDE & Co. And this one individual owns all the stocks in the U.S. & it never settles, okay. So you never actually collect on any of the stock purchases or sales. You get fiat back occasionally. But these transactions settle - they're individually directed - so, they don't go through a 1099 reporting organization & its going to be just hellacious for the government to input all this level of tranaction from all these millions of people that are voluntarily tell them, "Well yeah, I traded a tenth of an ether & I got 115 Populous coins, and I traded 7 of those, and I got 50 of these, and 15,000 bim coins - that kind of a thing, right?

    [Seems to me, this last thing that Clif has said is specifically why an A.I. quantum computer system would need to be an essential part of the cryptocurrency / blockchain equation - just saying, Clif. ]
    (Taking a break for now. Will come back later to transcribe more, as Clif gets to rambling on so quickly that its helpful to see what he says in a written form...)
    Last edited by turiya; 3rd December 2017 at 02:09.

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  37. Link to Post #19
    United States Avalon Member turiya's Avatar
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    Default Re: The Dark Secret at the Heart of AI

    More from Anthony Patch & Kev Baker...

    Enochian Magic, Tesla 3, 6, 9 &
    RESURRECTION Of The DEAD

    (Apr 17, 2017)
    Explained: “If you knew the magnificence of the three, six and nine, you would have a key to the universe.” – Nikola Tesla — Geometry of the Matrix is the Cube, while the “elite” employ the Sphere. Also, Enochian language and math in communications with Fallen Angels, it’s relevance to D-Wave’s development of quantum bits... FULL NOTES HERE.... http://www.kevbakershow.com/patch-tes...

    ______________

    By Kev Baker on April 18, 2017 CERN, Special Reports




    ANTHONY PATCH BREAKS DOWN THE SECRETS OF TESLA 3, 6 & 9 AND EXPLAINS HOW IT TRULY IS THE KEY TO THE UNIVERSE.

    The Anthony Patch Show… Episode#18.
    In this episode of the Anthony Patch Show, Tony & Kev go over a number of topics and cover Tony’s most recent revelations!

    We get into…. “If you knew the magnificence of the three, six and nine, you would have a key to the universe.” – Nikola Tesla — Geometry of the Matrix is the Cube, while the “elite” employ the Sphere.

    Also, Enochian language and math in communications with Fallen Angels, it’s relevance to D-Wave’s development of quantum bits and computers. The goal revealed: Immortality through modification of DNA using the 3,6,9 of tetrahedrons and its spherical arrangement.

    The video does have the relevant images that were used in the chatroom during the live show. Hopefully this will make it easier for the listener to understand just what is being said.

    So, lets get into it....

    TESSERACT VS TETRAHEDRONS…. THINK OUTSIDE THE BOX!

    FROM ANTHONY PATCH….
    What I am trying to convey is the fact that during the time of John Dee and Edward Kelley, the late 1500s, they were trying to describe geometric shapes using only their written language.

    Enochian Alphabet

    They were not mathematicians in the sense of computing equations in order to describe a given geometric shape.

    The Fallen Angels they were communicating with, used only letters because of their lack of formal education in math.

    Both were highly intelligent and produced long descriptions of the geometry they were being given.

    Where D-Wave comes into this is, they know all the math there is to know, at least for now.

    Therefore, in communication with these same Fallen Angels, they at D-Wave can communicate purely mathematically.

    The chipsets containing thousands of qubits are arranged as were the letters of the Enochian alphabet on the Great Tablet. Note the Tablet is divided into four smaller squares. This is the present-day, Quaternary programming of 5G WifFi. It is based upon 4, rather than 2. This is the superposition and supersymmetry in physical form/layout.

    The cross in the center joins these 4 sections, forming first into a tesseract cube in 3D. Then, forming into the circular shield in 3D, a sphere. The end point is the 600.

    The 600 is actually comprised of the Tree of Life. Several of them, when curved, forming the sphere, and one tree running directly up through its center.



    This is the navigational chart for the Universe. This is how Fallen Angels travel and their lines of communications with humans on Earth.

    Again, it all begins with the single tetrahedron. Where the Egyptians got stuck was with the cube. Therefore, the square-based pyramids, rather than a tetrahedronal pyramid. This is where Dee and Kelley got stuck. They could not describe using the Enochian alphabet, a 600 composed of tetrahedrons. It was just too complex for words.

    Intuitively, Dee and Kelley understood the geometry, but could not compose the equations in describing beyond the basic Euclidean shapes based upon everyday observations of “nature” around them.

    D-Wave first constructed qubits based upon the Enochian alphabet.



    Then, they received the Enochian mathematics, the algorithms, equations and Quaternary programming language. What I first coined as “Quaternary” programming using 0, 1, 3, 4 leaving out the 2 as being redundant within 4. Little did I know while composing Covert Catastrophe in late 2011.

    Today, I am convinced they have moved from tesseract, to the shield (a filter of information), to the 600 of today.

    Recall, I discovered an article from Cornell post-publication of Covert Catastrophe, proposing the arrangement of qubits as a tetrahedron. That is the smoking gun for the 600 as a quantum computer.



    Having now a better understanding of their communication languages, including the math, I am even more convinced the Holy Spirit was revealing to me back in late 2011 not only their computer, but the true model of the Universe upon which it was configured and is now operating.

    Remember from my Knoxville presentation. First, it had to be properly configured, matching that of the Universe. Then, tuning it by way of the proper number of qubits contained within this structure to tune it. They matched it to the CMB, Cosmic Microwave Background radiation wavelength.

    D-Wave moved from simple Cartesian coordinates in building a computer based upon qubits, to one using Spherical Harmonics, the computational, therefore communication system processing numbers along both the surface of a sphere, and within its internal dimensions.

    It is the combination of surface and internal configurations, therefore processing of information composed entirely of numbers arranged in a combinatorial programming language based upon 4, Quaternary.

    If you look at the simple tetrahedron, how many surfaces and corners is its shape composed of?



    TESLA 3, 6 & 9.

    Nikola Tesla was a Serbian-American inventor, electrical engineer, mechanical engineer, physicist, and futurist who is best known for his contributions to the design of the modern alternating current electricity supply system.

    Tesla made a number of profound statements over the course of his life and one that stands out is the following….



    In the days prior to the show, Tony Patch started to realise just what it was that Tesla was talking about. The image below hill hopefully allow you to follow the information Tony is relaying here…..

    3, 6 & 9 DECODED!
    Count how many separate, straight lines there are here. Start at the peak of the pyramid, counting down the right side, using only the top, orange triangle. That is the first line. Keep doing this, using on that line that is part of an individual color.

    Count each line. There are 9.

    Now, count using only the “outside” lines forming the entire pyramid itself. 3.

    Continue now to include the lines “inside” this larger, singular pyramid. Another 3.
    If you add the 3 outside with the 3 inside lines = 6

    Tesla was referring to the tetrahedron when he spoke of the 3, 6, 9.
    It is the model of the Universe.

    666 and the tetrahedron and parallel dimensions come from the tetrahedron.
    6 straight edges. The edges are where parallel dimensions meet, come together, communicate with one another.

    Given that a tetrahedron is 3-dimensional, not flat, you bring the 3s together, forming 666. Don’t know why I did not see this before. Maybe I did, but forgot until just now. Getting old. 666 forms into the 600-cell. Satan just steals what God creates.
    More at this link
    Last edited by turiya; 3rd December 2017 at 01:57.

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  39. Link to Post #20
    Avalon Member norman's Avatar
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    Default Re: The Dark Secret at the Heart of AI

    Joseph Stigliz, the former chief economist of the World Bank, wants bitcoin banned.

    https://www.coindesk.com/bitcoin-out...stiglitz-says/

    "Bitcoin is successful only because of its potential for circumvention, lack of oversight," Joseph Stigliz, currently a professor at Columbia University, said in an interview on Bloomberg Television today, as the cryptocurrency reached new all-time highs this week.

    However, Stiglitz, who also chaired the U.S. President's Council of Economic Advisers during the Clinton Administration, said he does support technological innovation in payments, but thinks digital money should still be fiat created and controlled by the government.


    "Let’s move away from paper into the 21st century of a digital economy," he said.


    Like many other members of the Davoisie, Stiglitz – who won the Nobel Memorial Prize in Economic Sciences in 2001 – called the run-up in bitcoin's price unjustified and unsustainable.


    "It’s a bubble that’s going to give a lot of people a lot of exciting times as it rides up and then goes down," he said. "The value of a bitcoin today is expectations of what the bitcoin is going to be tomorrow."


    And even though bitcoin is a decentralized network, with participants scattered around the globe, Stiglitz seemed to think Washington could easily nip it in the bud.

    "If the government says 'the reason bitcoin is being used is circumvention,' they could close it down at any moment," he said. "And then it collapses."
    .................................................. my first language is TYPO..............................................

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