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Immortal since Jun 17, 2010
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mad-scientist and computer programmer looking for something more interesting than most people accept as their future
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    Mon, Sep 26, 2011  Permanent link
    Categories: future, AI, human, War, meta
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    What you think your eyes see is mostly a memory. People think they're seeing what's in front of their eyes, but the way we think while awake is more like a dream than what's in front of our eyes. I often look straight at something and don't see it because I don't remember it. Next time you see something unlike anything you've seen before, close your eyes and think about drawing a picture of it. If you saw 2 birds behind it, are you sure you didn't see 3 birds? Was the first bird flapping its wings up or down just before you closed your eyes? My picture would be very blurry. If you were standing beside me, you wouldn't be able to tell my picture was of the same thing you're looking at. I used to have a visual memory, able to draw such a picture very accurately, but I decided there were more advantages to not thinking in such a strict logical way and slowly lost the ability. Theres 2 main reasons Monkeys have a visual memory and most Humans don't. Its a form of lossy-compression (Example: jpg, mp3, keeps the details you tend to notice) which saves memory, and it allows our thoughts to flow together in more flexible ways so we can imagine more possibilities.

    Scientists try to learn how Human brains work the hard way. They build expensive simulations, do experiments on animal brains, scan peoples' brains for electricity and blood flow patterns (functional MRI) while those people think certain things, write lots of papers, and still they are unable to write a few pages explaining to average people how Human intelligence works. I do some of that research, but I'm an expert on Human intelligence for a different reason: My mind has observed itself long enough to figure out half of how itself works. Many people have tried that, but they usually get stuck on the subjectivity and vagueness of their thoughts. Intuitively they know what a thought is, but they know of no way to figure out which neurons (brain cells) are connected to which thoughts, so they can not translate their knowledge of how their mind works into something science can use.

    Here's something unnecessary researchers want to try: A computer's video-card has a grid of brightness numbers, 1 for each colored light on the screen. If we could connect the visual part of a Human brain to a computer screen and see what its thinking (1 small group of neurons to each part of the screen), while we show the person various pictures and ideas, then we could learn how the visual-related neurons work, and then learn how the neurons connected to those work, and so on. We don't need to do that because each of us already has such a video screen in our minds. Its called "what we think our eyes see".

    Its not really what our eyes see. Its our most similar memories, twisted and rotated and re-interpreted to fill in the missing parts. Our brains throw away most of what our eyes see and fill in most of the parts from memory. While dreaming, almost the same thing happens. Our brains use nothing from our eyes and fill it all in from re-interpretations of our memory. We're mostly dreaming while awake, with the exception of a little information our brains pay attention to coming from our eyes and other senses.

    I will explain how to start with your vision, do some thought-experiments, and work backward to the other parts of your brain until you understand more about Human intelligence than scientists understand from their billions of dollars of research. I know enough about how Human intelligence works that I could build half of it and have artificial intelligence evolve the other parts, but it takes many years to fine-tune it and teach it like you teach a Human baby, like you would teach it math by giving it simulations of fingers and activating the neurons for 3 of its fingers to teach it the idea of 3, and you would teach it to multiply 2 times 5 by showing it its 2 simulated hands and they have 5 fingers each, or whatever type of simulated or robot body and senses you give it. This would be a robot or simulation so accurate it would learn ethics from the recursive thought of thinking of others as a variation of itself (a directed network where each node type is the idea of itself and one of the nodes is attached to a person) and thinking about the emotions (recursive thoughts leading to memories of pleasure or pain) itself had when things happened to itself. All that, I can define in math, but instead I'll take you through my series of thought-experiments of how I figured it out...

    You can learn most of it from your visual memory. You only need to understand these few things about neurons:
    * Each part of "what we think our eyes see" is always connected to the same small group of neurons and is brighter when there is more electricity in those neurons.
    * Each neuron is connected to thousands of other neurons, and they connect and disconnect slowly over time.
    * A thought is the specific amount of electricity in some of your neurons, what each neuron tends to do when it receives certain amounts of electricity, and the strength and physical length of the neuron-to-neuron connections. A much smaller amount, a thought is the chemicals flowing around neurons.

    This started when I was thinking about what some research said, that it takes longer to recognize a picture of something if its upside down. What was really interesting about that is if it was turned 2 times more angle, then it takes 2 times longer to recognize it. Upside down is the biggest angle. The time it takes to recognize a picture of anything is linearly proportional to the angle its turned.

    I chose something I had rarely seen, so I could experience more of the process of thinking about a new subject. I thought about an elephant. When it was drawn on "what we think our eyes see", which is also the imagination and visual neurons for dreams, I confirmed that it did take longer to draw it in my mind upside down than the same way as in my memories of elephants. After I thought about the elephant from each new angle, I found I was able to think of that angle again instantly, but any new angle took the linear rotation time. It could be a rotation from any of my old memories or new thoughts from the last minute. As I thought of the elephant from more angles, the time to think of the angles between them became less. I confirmed what I had read. Human intelligence does rotation a little at a time and repeats until it gets to the right angle. Also, I learned that such rotations create new memories which can be used as the start for new rotations, so to do it faster, you usually start from the closest memory of a rotation to the one you want, a 3d memory of an elephant's parts rotated closest to the rotation you're thinking about now.

    Remember this is causing an image of an elephant to be drawn in electricity on your visual neurons. They're not arranged in a rectangle in your brain like on a screen. They're arranged however they're connected to your optical nerves. But if you figure out which neurons are connected to which part of "what we think our eyes see", which can be done using brain scanning machines, then you would see a picture of an elephant rotating in the electricity of those neurons. There is actually a picture of an elephant, made of electricity, somewhere in your brain, if you arrange the neurons the right way like you would see on a screen. Brainwaves are so advanced they can form into the shape of an elephant, or anything else you imagine. Its important to understand that's what we're looking at when we think about rotating an elephant in our minds. We're drawing an elephant onto our visual neurons, very similar to how a computer's video-card's memory works.

    The next thought-experiment shows a flaw in how we see 2 things at once. I chose 2 things I had never seen together, to experiment with how my brain combines ideas. I thought about the same elephant with a shoe floating 3 feet above it. The shoe was drawn onto my visual neurons quickly. But when I thought about rotating them together, viewing the shoe and elephant from a different location and angle, I could only see 1 thing at a time, the shoe or the elephant. Whichever I looked at, the other instantly started looking blurry. Is my imagination really that weak that it can't handle 2 things at once without blurring 1 of them? It only happened when rotating them together.

    I'm guessing that is because the 3d-rotation part of my brain normally only does 1 object at a time and rotates the shoe or the elephant and draws them on my visual neurons separately. I confirmed that when I noticed I could rotate them together as easily as if they were a single object only after thinking about them together for 30 seconds. It was a new type of thing in my mind, a shoe-over-elephant, and it was rotated with the same linear timing as the shoe or elephant alone. At first they had to be processed separately, so the visual neurons lost their image of one while the other was being drawn, but when shoe-over-elephant became a single object in my mind, it did not have those problems.

    That is the start of my theory on how objects are represented in 3d in Human minds. They are made of other 3d objects in relative positions and rotations and sizes and stretch amounts etc. Later I'll explain how such "objects within objects" are the same type of thinking as language, goals, emotions, and other types of thinking. It sounds complex, but its really the same simple ideas repeated in different ways for many kinds of thinking.

    The next thought-experiment is about counting and how we identify if 2 things we see are the same object or idea. Think about 3 of that same elephant, all standing the same direction. Its easy. Now think about 3 elephants with a shoe above each, the shoe-over-elephant object recently created in your mind. Also easy. Rotate all that. Since they're standing the same direction, it happens almost as fast as if there's just 1 shoe-over-elephant, because the same object is rotated and drawn 3 times from slightly different angles. Now think of 100 elephants standing the same direction. Also easy.

    Here's the surprising part. If 100 elephants are easy to visualize, then 2 elephants standing opposite directions should also be easy. But its not. I experience the same blurring of 1 of 2 objects (the elephant standing forward or the one standing backward) when I pay attention to the other object, the same as happened between the shoe and elephant before it became shoe-over-elephant. Similarly, after thinking about such 2 elephants long enough, that problem goes away, and they can be rotated, moved, duplicated and rotated again, etc, as one object made of 2 of each part of an elephant. Your mind has to represent 2 of each part of an elephant because it has to know that the tail of one elephant is beside the trunk of the other elephant, for example. If you think of it as 2 elephants, instead of a single object, then you have the linear rotation time (before drawing on your visual neurons) every time you switch your attention to the other elephant.

    After it becomes 1 object in your mind, think of that two-elephants-one-reversed object and a duplicate of it rotated and beside it, so you have 4 total elephants each at a different angle. Its easier now, while at first you had problems with 2 elephants at different angles. You can continue making the total be 1 object, rotating and moving a duplicate of it, and doubling the number of elephants each time, until you have as many elephants as you want in your visual neurons, each rotated differently.

    You'll notice during your duplication of elephants that some of the parts of some of the elephants disappear until you pay attention to them again. How does your mind know what to replace the missing parts with? First your mind looks at two-elephants-one-reversed to see how each 2 elephants are standing relative to each other. Then recursively you look at the specific elephant in that. Then recursively you look at your definition of elephant for the smaller parts of elephants, and its drawn that way on your visual neurons.

    You may also notice that when you pay attention to your definition of elephant, that more than 1 elephant gets those parts updated at once. For example, I had forgotten that elephants had tusks, but when I remembered, they were drawn on all 4 elephants. First your mind updates elephant, then two-elephants-one-reversed, then both examples of two-elephants-one-reversed which you're thinking about simultaneously. Its a hierarchy, but your mind can represent non-hierarchy things too, as I'll explain later with fractals.

    The next thought-experiment is about wildcards in ideas, patterns that have places for other patterns to fit in. How does your mind decide which ideas to plug into which other ideas?

    We remember the shoe-over-elephant well. Now think of 3 elephants standing the same direction. The one on the right has a shoe over it. Rotate all that until it becomes 1 object. Now we will generalize the shoe-over-elephant object to wildcard-over-elephant. The elephant on the left has an apple over it. The elephant in the middle has an orange over it. Visualize that from various rotations. Now pay attention to the shoe (over the right elephant). The shoe-over-elephant object is a stronger memory than the apple and orange, so the shoe should not change unless you try to change it. What surprised me is what happened next when I payed attention to the 2 other elephants. What is over each of them? It switched quickly between apple and orange a few times per second, over each of those 2 elephants, because I did not have a strong memory of which elephant got which fruit. The shoe did not change, but the apple and orange did. After choosing where I wanted each fruit to be and thinking about it longer, I was able to rotate the whole thing (3 elephants with 3 things over them) without the objects switching places. Why did they switch places? Because 2 things were combined with 2 wildcard-over-elephant, but there was no strong preference between which way to combine them. My visual neurons displayed both possibilities, switching between them a few times per second.

    So far, I've explained these types of thinking:
    * 2d grid of visual neurons, absolute positions instead of relative. In math its called a matrix, but there's also the layers of edge-detection and connections to the "3d grid" described below.
    * 3d grid of object positions and rotations and sizes relative to other 3d objects. In math its called a sparse-matrix. Later I'll explain how rotation, speed, and acceleration are also dimensions attached to each of those 3 dimensions, and some ideas use a 4d grid with time, but there is no rotation between the 3d and time dimensions of the 4d grid.
    * Hierarchy of ideas, and I've claimed (but not yet explained) that it is more generally a network (of nodes pointing at nodes) which allows cycles, where some nodes are ideas and some are wildcards. In math, its called a directed-network.

    Sound is experienced similar to the 2d visual neuron grid. Human ears detect around 1500 different tones and a volume for each, many times per second. You can easily remember what you heard a few seconds ago and predict what you will hear a few seconds from now, therefore time is one of the dimensions of sound, a dimension represented almost the same way as left/right or up/down is represented in your visual neurons. The other dimension is the 1500 notes. Brightness is like their volume. I say the 1500 notes are a dimension, instead of 1500 unordered things, because you can hear the same music with all notes increased in tone, and you will recognize it as the same music. That's similar to how you recognize the same object visually if its to your left or in the center of your vision.

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    This is my response to a debate between Ben Goertzel and Hugo De Garis who both build artificial intelligence and speculate about what it leads to and the possibility aliens may have already done it. Normal religions help us understand the universe as much as a 1000 year old physics book. That leaves a lot of questions... If you're not more confused about what the universe really is after reading this, then you must have missed something. If there is a god or not depends on your definition of "god", and most people don't bother to define it. I might be an atheist or not, and science might be able to test some things most people think can't even be defined or understood.

    "From cosmism to deism"

    "Is God an Alien Mathematician?"
    Then the thread was deleted and moved to:

    You can find my response at the bottom of the second link. Here it is:

    If the universe equals math then a lot of things fit together

    Most of what we've observed in science is very well approximated by small math equations. That's a fact. If the equations were a little different then physics probably wouldn't get past the first few steps of forming life. That's an other fact. Physics that is very (instead of a little) different could form different kinds of life, but the point is this part of the universe that we live in works so much better than a randomly selected physics that, to learn what physics (or "hyper-physics") really is, we must figure out why such a rare or improbable thing happened. There are 2 main categories of explanation: Rare and Improbable.

    If its Improbable but exists anyways, that implies something intelligent. Most religions and "Is god an alien mathematician" are in this category.

    If its Rare instead of Improbable, then enough things exist that, without needing anything intelligent to design it, this part of the universe just happened to be 1 of those many things. Max Tegmark's "Mathematical Universe Hypothesis" (summarized as "All structures that exist mathematically exist also physically") is the simplest idea in this category.

    The We-Are-Rare and We-Are-Improbable categories should both be considered in science, including theories of superintelligent artilectual intelligences.

    Hugo de Garis is probably right about "humanity has invented on the order of about 100,000 different gods over the broad sweep of history, and across the planet. These many gods are so obviously invented", but if we say it as "100,000 theories of which most have been proven false" then we find the real problem in religions: They don't learn from their mistakes. They continue creating variations of failed theories instead of thinking in new ways.

    Theories are better when they are simpler and explain more things. The "Is god an alien mathematician" idea is compatible with some kinds of Buddhism, which Ben Goertzel said can be argued it "isn't really a religion." Ignoring the parts about what people should and shouldn't do and the details about things that happen on Earth, one of its bigger ideas is the emptiness of reality. If the "Mathematical Universe Hypothesis" is true, then the universe simply is math, and math is purely abstract so doesn't really exist. On average, math and therefore the universe sum to nothing, but its parts individually exist because we're here experiencing them. The "Mathematical Universe Hypothesis" requires there be an infinite number of superintelligent alien mathematicians, but it also requires there be an infinite number of everything else you can define in math.

    Ben Goertzel sees "Is god an alien mathematician" as a variation of the "simulation argument." Since technology will probably advance enough for artilects to appear god-like compared to us and create recursions of universes, the argument is we're probably in one of those simulations. You forgot to weight the probabilities. Its true there are many simulations in our computers today, but if we weight by the number of particles, all the simulations together are small compared to the particles in the computers which run the simulations, therefore if you're made of some particles then its more likely you're part of a computer (or are nowhere near a computer) than a simulation in that computer.

    I agree that large things (which small-brained Humans would call "universes" instead of "places with different physics") can be created by artilects with enough intelligence, and we could be in one, but considering my Weighted Simulation Argument, and considering that we don't know how far up the tree (or fractal or peer-to-peer-network) of recursive universes we are (We can't see below quantum physics yet), I expect theres a lot of potential in this part of the universe that we're just starting to learn how to use. An event as small as splitting a particle and its antiparticle could be seen as creating a new universe to those who experience the universe in a different way or size or pattern than we do.

    Math contains and is contained by an infinite variety of fractals, and the universe could equal math. How do you know your theoretical superintelligent artilects are more advanced than what we do by accident or what we do intentionally as mathematicians to physics in a statistical way (which we would not see since the effects are too small or too big)? When, for example, Ben Goertzel says "I've had my share of strange spiritual experiences, which have made me sometimes feel very directly in contact with transhuman intelligences", shouldn't we consider that some part of it could be real? And if we go that far, shouldn't we consider that Humans may intuitively know (through brains interactions with quantum physics) something these "transhuman intelligences" do not know? Why should we only consider theories where power is in a hierarchy/tree (this universe inside that universe) instead of fractal or network or strange-loop or emergent shapes? I will not make the assumption that there must be something higher or lower than me. Theres too many questions to ask first.
    Thu, Jan 20, 2011  Permanent link
    Categories: alien, AI, philosophy, religion, Fractal, math
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    What is the universe? Why is it here? How can we use it? Those questions have been debated for all of recorded history, but I've never heard of anyone who tried to answer all 3 questions with the same answer. I will list some observations, some theories which try to explain them, and a way to use the theory to design a faster than light engine (a warp drive) using cheap technology like lasers and parts of LCD (liquid crystal display) screens.

    The picture above is E8 (described below), what they think physics looks like at the deepest level they know about. It looks a lot like a sphere, or did you think the laws-of-physics were flat? What creates spheres? Gravity.

    DEFINITION: Laws-of-physics is the statistical behavior of a subset of the universe, usually the subset closest to Earth.

    OBSERVATION: The only known laws-of-physics is very accurately approximated by small math equations.

    OBSERVATION: The only known laws-of-physics has arbitrary-appearing (not like pi or e or integers) constants in its equations.

    OBSERVATION: The only known laws-of-physics has never been observed changing (same equations), or only a small amount.

    OBSERVATION: When in superposition, 1 particle/wave can be in thousands of places at once without being between those places, and when 1 of those thousands of places is touched, 1 gets more dense and the others get less dense.

    OBSERVATION: Quantum wavefunctions can be split by a half-mirror and reassembled by the same process in reverse at a different half-mirror. Its branches can cancel each other out or strengthen each other, depending on the angles and number of bounces etc.

    OBSERVATION: More often than would happen randomly or through normal communication or observing the environment etc, there are small statistical dependencies between the brains of people and/or quantum physics devices. See the "main results" list at  for the results of those experiments. Also you can watch a mind over matter video I did in 2002 at  ("Psi wheel in a clear closed box 2" at youtube), or many similar videos. Lots of people have done strange mental things.

    OBSERVATION: The E8 math structure very accurately approximates the only known laws-of-physics. It is many rotations of a 57-dimensional shape in 248-dimensional space, where each dimension represents a quantum particle/wave type. There are levels of organization built on top of levels between 248 particle types (including some not observed) and the small number of types at the top of the Standard Model.

    THEORY: The Copenhagen theory of quantum physics is an approximation of the most infinite version of Manyworlds theory, similar to how Newton's equations are an approximation of Einstein's equations.

    THEORY (by Max Tegmark): "All structures that exist mathematically exist also physically."

    LOGIC: If Tegmark is right then: For any subset of the universe, there are an infinite number of unique ways to simulate that subset and recursively simulations of simulations to infinite depth, all averaging to nothing because of the symmetry of math. Since the universe is nothing on average, it doesn't really exist and does not need to be created. Parts of it exist alone, but together they do not.

    DEFINITION: Pattern is any subset of math. A wavefunction or any subset of it is a pattern. A statistical similarity between 2 patterns or subsets of them is a pattern.

    THEORY "Gravity For Patterns": The universe is the set of all possible wavefunctions of patterns instead of simply wavefunctions of particles/waves, and patterns attract patterns more when they are more similar.

    LOGIC: If Gravity For Patterns is right then: Collapsing a wavefunction is the superpositioned parts falling toward each other, pulled by the mostly-collapsed parts (the parts of reality they agree on) being similar patterns. The E8 shape is 1 of many possible shapes, and (possibly, but not necessarily practical) new shapes can be rotated in while E8 is gradually rotated out, to locally change the laws-of-physics to any arbitrary pattern you can amplify through chaos-theory.

    THEORY: The "statistical dependencies between the brains of people and/or quantum physics devices" are caused by such a rotation between E8 and whatever pattern fits the combination of brainwaves/devices which become statistically dependent, and that is probable to happen because infinite recursions of "Gravity For Patterns" (patterns about patterns attracting) will pattern-match any 2 patterns in 2 brains and ***exponentially*** increase the chance such patterns will connect through the multiverse. Its exponential because the recursion of patterns always finds an effective path between the 2 patterns. It finds an infinite number of other things, but the gravity part gradually changes that, and a small change goes exponential because of the recursion.

    THEORY: A faster than light engine (a warp drive) can be created using a distributed (not hierarchy) network of programmable crystals (a more advanced kind of LCD screen - Liquid Crystal Display) which are controlled by programmable lasers which are controlled in realtime by artificial intelligence which is given the task of controlling the crystals formed as early as possible (the precognitive effect in Humans, in a machine). The purpose of these cheap grids of programmable crystals is to grow crystals in multiverse directions which eventually grow far enough to touch each other in this distributed network. That system would be the way to access the "patterns" described in the theory above, to (a small amount) rotate out laws-of-physics (probably an E8 shape) and rotate in a warp field. This is all done by resonance of the patterns (Like Tesla's "earthquake machine"), not by brute-force pushing in the same direction until it works (That would take infinite energy, as relativity equations say). The way it works depends on large symmetric patterns, like a global telepathy network or the same built with a network of machines (using LCD crystals the same way as the analog parts of brains access Gravity For Patterns). Either way, it needs continuous use of a lot of intelligence, which can be done through a network Human minds and computers connected through psychology software and the internet, or it could be done using pure artificial intelligence if we knew more about how intelligence works. The intelligence is used to control the growth of the crystals in multiverse directions by controlling the brightness of the lasers. To extend the warp field around large areas like a planet or solar system (theoretically if the curved spacetime isn't vibrating too much from the large mass), put the crystals and computers around it in a sphere shape in space, and connect them with lasers pointing at each other which point at the LCD crystals of each other, so the waves of spacetime intersecting the lasers will be measured in the fractal patterns in the LCD crystals caused by the distorted laser light hitting it. That is how the machines would communicate with each other to know how to adjust their crystals to adjust to the way spacetime is vibrating. If done accurately enough, it should work for a starship, maybe for moving planets and stars, but probably not anything as big as a black-hole because its spacetime vibrations would be too big. First, we should try to build a machine that can push small things around using Gravity For Patterns. Then work up to the starships.

    Gravity For Patterns is Ben F Rayfield's theory of everything, including how the laws-of-physics form and how to locally change them using small amounts of energy and large amounts of intelligence.
    Sun, Dec 19, 2010  Permanent link
    Categories: AI, Theory, gravity, pattern, warp drive, multiverse, LCD, tegmark
    Sent to project: Polytopia
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