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We have nightmares because our brain is running simulations to put us in jeopardy to see what we'll do or to acclimatize us to that idea that something bad could happen. It's just how human beings are wired because the entire time we were evolving we had to jump quick or the leopard would get us or whatever it was. It's Darwinian.
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Simulations directly relate to the process of and complications in photography. They also overtly create layers of fantasies, myths and interventions... The simulation confuses the idea of a truth. I've always been interested in this kind of theater and illusion at the foundation of belief.
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A truly intelligent person is not one who can simply spout words and numbers; it is someone who can react 'intelligently' to all the opportunities, simulations and problems provided by the environment. Real intelligence means engaging your brain with every aspect of life - you play sport with you brain; you relate to others brain-to-brain;
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I wonder if we are seeing a return to the object in the science-based museum. Since any visitor can go to a film like Jurassic Park and see dinosaurs reawakened more graphically than any museum could emulate, maybe a museum should be the place to have an encounter with the bony truth. Maybe some children have overdosed on simulations on their computers at home and just want to see something solid--a fact of life.
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Something as superfluous as "play" is also an essential feature of our consciousness. If you ask children why they like to play, they will say, "Because it's fun." But that invites the next question: What is fun? Actually, when children play, they are often trying to reenact complex human interactions in simplified form. Human society is extremely sophisticated, much too involved for the developing brains of young children, so children run simplified simulations of adult society, playing games such as doctor, cops and robber, and school. Each game is a model that allows children to experiment with a small segment of adult behavior and then run simulations into the future. (Similarly, when adults engage in play, such as a game of poker, the brain constantly creates a model of what cards the various players possess, and then projects that model into the future, using previous data about people's personality, ability to bluff, etc. The key to games like chess, cards, and gambling is the ability to simulate the future. Animals, which live largely in the present, are not as good at games as humans are, especially if they involve planning. Infant mammals do engage in a form of play, but this is more for exercise, testing one another, practicing future battles, and establishing the coming social pecking order rather than simulating the future.)
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Life in zero gravity is hard to simulate. We practice on the ground what we call 'the day in the life' simulations, but it's just practicing some of the tests. It can't prepare you for the fact that all of your tools float if you don't pay attention to where they are! If you don't Velcro things down, they're gonna float away.
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When your own success shocks you, you fail to sustain it and it becomes a curse instead of a blessing. Think through issues and make considerations before you encounter the real situation. Companies invest billions in research and development, including models and simulations to increase chances of success - all in an attempt to make success deliberate for a particular project.
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For most problems found in mathematics textbooks, mathematical reasoning is quite useful. But how often do people find textbook problems in real life? At work or in daily life, factors other than strict reasoning are often more important. Sometimes intuition and instinct provide better guides; sometimes computer simulations are more convenient or more reliable; sometimes rules of thumb or back-of-the-envelope estimates are all that is needed.
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Holland's and Kauffman's work, together with Dawkins' simulations of evolution and Varela's models of autopoietic systems, provide essential inspiration for the new discipline of artificial life, This approach, initiated by Chris Langton (1989, 1992), tries to develop technological systems (computer programs and autonomous robots) that exhibit lifelike properties, such as reproduction, sexuality, swarming, and co-evolution.
John Henry Holland
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NONMEM simulations are at the heart of most critical processes within the pharmaceutical and life sciences industries, where ensuring fast, accurate and affordable decision-making is a top-of-mind issue. ACCELLERANT for NONMEM responds to these challenges, allowing organizations to take full advantage of parallel and distributed computing for run time reduction and improved precision - without the need for costly and time-consuming application changes.
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Parallel to the training of the body a struggle against the poisoning of the soul must begin. Our whole public life today is like a hothouse for sexual ideas and simulations. Just look at the bill of fare served up in our movies, vaudeville and theaters, and you will hardly be able to deny that this is not the right kind of food, particularly for the youth. Theater, art, literature, cinema, press, posters, and window displays must be cleansed of all manifestations of our rotting world and placed in the service of a moral, political and cultural idea.
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Nvidia's self-driving-car business grew out of a long-standing relationship with auto companies. Car guys used Nvidia chips for computer-aided design, then used Nvidia supercomputer chips to do crash simulations. When the car guys started thinking about autonomous vehicles, Nvidia leaped at the chance to help them solve the problem.
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Frank stared at her. "But you throw Ding Dongs at monsters." Iris looked horrified. "Oh, they're not Ding Dongs." She rummaged under the counter and brought out a package of chocolate covered cakes that looked exactly like Ding Dongs. "These are gluten-free, no-sugar-added, vitamin-enriched, soy-free, goat-milk-and-seaweed-based cupcake simulations." "All natural!" Fleecy chimed in. "I stand corrected." Frank suddenly felt as queasy as Percy.
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The photograph, then, becomes a representation of a representation of a disease that represents. In other words, in order to produce the most perfect images of hysteria, the hysteric - a woman whose illness simulates the symptoms of other diseases - was transformed, through hypnosis, into an artificial hysteric who perfectly simulated the simulations of hysteria. The medical photograph becomes a copy of a copy of a copy, a representation so far removed from the original that all duplicitous traits, were easily erased, leaving the deranged and chaotic nature of the original far behind. The photograph succeeded in turning the hysteric into a wholly artificial being, literally a flat, framed, unmoving image.
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Evolution has no foresight. Complex machinery develops its own agendas. Brains - cheat. Feedback loops evolve to promote stable heartbeats and then stumble upon the temptation of rhythm and music. The rush evoked by fractal imagery, the algorithms used for habitat selection, metastasize into art. Thrills that once had to be earned in increments of fitness can now be had from pointless introspection. Aesthetics rise unbidden from a trillion dopamine receptors, and the system moves beyond modeling the organism. It begins to model the very process of modeling. It consumes evermore computational resources, bogs itself down with endless recursion and irrelevant simulations. Like the parasitic DNA that accretes in every natural genome, it persists and proliferates and produces nothing but itself. Metaprocesses bloom like cancer, and awaken, and call themselves I.
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Recent brain scans have shed light on how the brain simulates the future. These simulation are done mainly in the dorsolateral prefrontal cortex, the CEO of the brain, using memories of the past. On one hand, simulations of the future may produce outcomes that are desirable and pleasurable, in which case the pleasure centers of the brain light up (in the nucleus accumbens and the hypothalamus). On the other hand, these outcomes may also have a downside to them, so the orbitofrontal cortex kicks in to warn us of possible dancers. There is a struggle, then, between different parts of the brain concerning the future, which may have desirable and undesirable outcomes. Ultimately it is the dorsolateral prefrontal cortex that mediates between these and makes the final decisions. (Some neurologists have pointed out that this struggle resembles, in a crude way, the dynamics between Freud's ego, id, and superego.)
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These computer simulations try only to duplicate the interactions between the cortex and the thalamus. Huge chunks of the brain are therefore missing. Dr. [Dharmendra] Modha understands the enormity of his project. His ambitious research has allowed him to estimate what it would take to create a working model of the entire human brain, and not just a portion or a pale version of it, complete with all parts of the neocortex and connections to the senses. He envisions using not just a single Blue Gene computer [with over a hundred thousand processors and terabytes of RAM] but thousands of them, which would fill up not just a room but an entire city block. The energy consumption would be so great that you would need a thousand-megawatt nuclear power plant to generate all the electricity. And then, to cool off this monstrous computer so it wouldn't melt, you would need to divert a river and send it through the computer circuits. It is remarkable that a gigantic, city-size computer is required to simulate a piece of human tissue that weighs three pounds, fits inside your skull, raises your body temperature by only a few degrees, uses twenty watts of power, and needs only a few hamburgers to keep it going.
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Neel cuts in: "Where'd you grow up?" "Palo Alto, " she says. From there to Stanford to Google: for a girl obsessed with the outer limits of human potential, Kat has stayed pretty close to home. Neel nods knowingly. "The suburban mind cannot comprehend the emergent complexity of a New York sidewalk." "I don't know about that, " Kat says, narrowing her eyes. "I'm pretty good with complexity." "See, I know what you're thinking, " Neel says, shaking his head. "You're thinking it's just an agent-based simulation, and everybody out here follows a pretty simple set of rules"- Kat is nodding-"and if you can figure out those rules, you can model it. You can simulate the street, then the neighborhood, then the whole city. Right?" "Exactly. I mean, sure, I don't know what the rules are yet, but I could experiment and figure them out, and then it would be trivial-" "Wrong, " Neel says, honking like a game-show buzzer. "You can't do it. Even if you know the rules- and by the way, there are no rules-but even if there were, you can't model it. You know why?" My best friend and my girlfriend are sparring over simulations. I can only sit back and listen. Kat frowns. "Why?" "You don't have enough memory." "Oh, come on-" "Nope. You could never hold it all in memory. No computer's big enough. Not even your what's-it-called-" "The Big Box." "That's the one. It's not big enough. This box-" Neel stretches out his hands, encompasses the sidewalk, the park, the streets beyond-"is bigger." The snaking crowd surges forward.
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In the absence of expert [senior military] advice, we have seen each successive administration fail in the business of strategy - yielding a United States twice as rich as the Soviet Union but much less strong. Only the manner of the failure has changed. In the 1960s, under Robert S. McNamara, we witnessed the wholesale substitution of civilian mathematical analysis for military expertise. The new breed of the "systems analysts" introduced new standards of intellectual discipline and greatly improved bookkeeping methods, but also a trained incapacity to understand the most important aspects of military power, which happens to be nonmeasurable. Because morale is nonmeasurable it was ignored, in large and small ways, with disastrous effects. We have seen how the pursuit of business-type efficiency in the placement of each soldier destroys the cohesion that makes fighting units effective; we may recall how the Pueblo was left virtually disarmed when it encountered the North Koreans (strong armament was judged as not "cost effective" for ships of that kind). Because tactics, the operational art of war, and strategy itself are not reducible to precise numbers, money was allocated to forces and single weapons according to "firepower" scores, computer simulations, and mathematical studies - all of which maximize efficiency - but often at the expense of combat effectiveness. An even greater defect of the McNamara approach to military decisions was its businesslike "linear" logic, which is right for commerce or engineering but almost always fails in the realm of strategy. Because its essence is the clash of antagonistic and outmaneuvering wills, strategy usually proceeds by paradox rather than conventional "linear" logic. That much is clear even from the most shopworn of Latin tags: si vis pacem, para bellum (if you want peace, prepare for war), whose business equivalent would be orders of "if you want sales, add to your purchasing staff, " or some other, equally absurd advice. Where paradox rules, straightforward linear logic is self-defeating, sometimes quite literally. Let a general choose the best path for his advance, the shortest and best-roaded, and it then becomes the worst path of all paths, because the enemy will await him there in greatest strength... Linear logic is all very well in commerce and engineering, where there is lively opposition, to be sure, but no open-ended scope for maneuver; a competitor beaten in the marketplace will not bomb our factory instead, and the river duly bridged will not deliberately carve out a new course. But such reactions are merely normal in strategy. Military men are not trained in paradoxical thinking, but they do no have to be. Unlike the business-school expert, who searches for optimal solutions in the abstract and then presents them will all the authority of charts and computer printouts, even the most ordinary military mind can recall the existence of a maneuvering antagonists now and then, and will therefore seek robust solutions rather than "best" solutions - those, in other words, which are not optimal but can remain adequate even when the enemy reacts to outmaneuver the first approach.
Edward N. Luttwak
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