Modeling And Simulation Quotes

Perhaps consciousness arises when the brain's simulation of the world becomes so complex that it must include a model of itself.

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.

Today abstraction is no longer that of the map, the double, the mirror, or the concept. Simulation is no longer that of a territory, a referential being or substance. It is the generation by models of a real without origin or reality: A hyperreal. The territory no longer precedes the map, nor does it survive it. It is nevertheless the map that precedes the territory - precession of simulacra - that engenders the territory.

Through prediction and correction, your brain continually creates and revises your mental model of the world. It’s a huge, ongoing simulation that constructs everything you perceive while determining how you act.

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.)

A computer model which manipulated data about itself and its “surroundings” in essentially the same way as an organic brain would have to possess essentially the same mental states. “Simulated consciousness” was as oxymoronic as “simulated addition.

There are completely deterministic universe models, with clear-cut rules of evolution, that are impossible to simulate computationally.

A brain that is good at simulating models in imagination is also, almost inevitably, in danger of self-delusion.

The Ego, as noted, is simply the content of your PSM [Phenomenal Self Model] at this moment (your bodily sensations, your emotional state, your perceptions, memories, acts of will, thoughts). But it can become the Ego only because you are constitutionally unable to realize that all this is just the content of a simulation in your brain. It is not reality itself but an image of reality - and a very special one indeed. The Ego is a transparent mental image: You - the physical person as a whole - look right through it. You do not see it. You see with it. The Ego is a tool for controlling and planning your behavior and for understanding the behavior of others

In the waiting room, ladies in a picturesque group surrounded a table with magazines. They stood, sat, or half reclined in the poses they saw in the pictures and, studying the models, discussed styles.

A hyperreal henceforth sheltered from the imaginary, and from any distinction between the real and the imaginary, leaving room only for the orbital recurrence of models and for the simulated generation of differences.

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.

it is with this same imperialism that present-day simulators attempt to make the real, all of the real, coincide with their models of simulation.

As my former Yale colleague Rogers Smith has put it: "Elegance is not worth that price.

You no longer watch TV, it is TV that watches you (live),” or again: “You are no longer listening to Don’t Panic, it is Don’t Panic that is listening to you”—a switch from the panoptic mechanism of surveillance (Discipline and Punish [Surveiller et punir]) to a system of deterrence, in which the distinction between the passive and the active is abolished. There is no longer any imperative of submission to the model, or to the gaze “YOU are the model!” “YOU are the majority!” Such is the watershed of a hyperreal sociality, in which the real is confused with the model, as in the statistical operation, or with the medium. …Such is the last stage of the social relation, ours, which is no longer one of persuasion (the classical age of propaganda, of ideology, of publicity, etc.) but one of deterrence: “YOU are information, you are the social, you are the event, you are involved, you have the word, etc.” An about-face through which it becomes impossible to locate one instance of the model, of power, of the gaze, of the medium itself, because you are always already on the other side.

It can’t be stressed enough that science produces nothing but hypotheses, models, simulations and approximations. There is nothing true about it. It has nothing to do with truth. It’s simply about modelling phenomena with increasing accuracy.

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.

the group listed dangerous insufficiencies that DARPA had to shore up at once: “Inadequate nuclear, BW, CW [biological weapon, chemical weapon] detection; inadequate underground bunker detection; limited secure, real-time command and control to lower-echelon units [i.e., getting the information to soldiers on the ground]; limited ISR [intelligence, surveillance, and reconnaissance] and dissemination; inadequate mine, booby trap and explosive detection capabilities; inadequate non-lethal capabilities [i.e., incapacitating agents]; inadequate modeling/simulation for training, rehearsal and operations; no voice recognition or language translation; inadequate ability to deal with sniper attacks.

Fiction is a set of observable manifestations, as represented and frozen in language, that triggers a profoundly subjective and individual experience. Ultimately, this is the kind of productive dilemma that can allow fiction to get to places that other media does not. Fiction is exceptionally good at providing models for consciousness, and at putting readers in a position to take upon themselves the structure of another consciousness for a short while. It is better at this than any other genre or media, and can do it in any number of modes (realistic or metafictional, reliably or unreliably, representationally or metafictionally, etc.). But for it to be able to do this as well as it possibly can, it must clear a space. This is where, for me, doing without becomes most crucial. The subtractions that we find in innovative fictions (even when those subtractions, as in Joyce's work, are followed by further ornamentations and encrustations) are there to facilitate the simulation of consciousness. What is subtracted is the significance and meaning designed to let us classify an experience without entering into it. Doing without such things opens the door wider for experience, putting the reader in a position where they are experiencing fiction in lieu of understanding it. By paying more attention to what we leave out than to how readers are going to interpret or work after the fact, we refuse to let fiction be assimilable, digestible, and safe. We keep it from being mere fodder for criticism and instead accept it as valid, vital experience.

In this section I have tried to demonstrate that Darwinian thinking does live up to its billing as universal acid: it turns the whole traditional world upside down, challenging the top-down image of designs flowing from that genius of geniuses, the Intelligent Designer, and replacing it with the bubble-up image of mindless, motiveless cyclical processes churning out ever-more robust combinations until they start replicating on their own, speeding up the design process by reusing all the best bits over and over. Some of these earliest offspring eventually join forces (one major crane, symbiosis), which leads to multicellularity (another major crane), which leads to the more effective exploration vehicles made possible by sexual reproduction (another major crane), which eventually leads in one species to language and cultural evolution (cranes again), which provide the medium for literature and science and engineering, the latest cranes to emerge, which in turn permits us to “go meta” in a way no other life form can do, reflecting in many ways on who and what we are and how we got here, modeling these processes in plays and novels, theories and computer simulations, and ever-more thinking tools to add to our impressive toolbox. This perspective is so widely unifying and at the same time so generous with detailed insights that one might say it’s a power tool, all on its own. Those who are still strangely repelled by Darwinian thinking must consider the likelihood that if they try to go it alone with only the hand tools of tradition, they will find themselves laboring far from the cutting edge of research on important phenomena as diverse as epidemics and epistemology, biofuels and brain architecture, molecular genetics, music, and morality.

What, then, distinguishes science from other exercises of reason? It certainly isn’t “the scientific method,” a term that is taught to schoolchildren but that never passes the lips of a scientist. Scientists use whichever methods help them understand the world: drudgelike tabulation of data, experimental derring-do, flights of theoretical fancy, elegant mathematical modeling, kludgy computer simulation, sweeping verbal narrative.18 All the methods are pressed into the service of two ideals, and it is these ideals that advocates of science want to export to the rest of intellectual life.

If the body is no longer a site of otherness but of identification, then we have urgently to become reconciled with it, repair it, perfect it, turn it into an ideal object. Everyone treats their bodies the way men treat women in projective identification: they invest them as a fetish, making an autistic cult of them, subjecting them to a quasi-incestuous manipulation. And it is the body's resemblance to its model which becomes a source of eroticism and 'white' seduction -- in the sense that it effects a kind of white magic of identity, as opposed to the black magic of otherness. This is how it is with body-building: you get into your body as you would into a suit of nerve and muscle. The body is not muscular, but muscled. It is the same with the brain and with social relations or exchanges: body-building, brainstorming, word-processing. Madonna is the ideal specimen of this, our muscled Immaculate Conception, our muscular angel who delivers us from the weaknesses of the body (pity the poor shade of Marilyn!). The sheath of muscles is the equivalent of character armour. In the past, women merely wrapped themselves in their image and their finery -- Freud speaks of those people who live with a kind of inner mirror, in a fleshly, happy self-reference. That narcissistic ideal is past and gone; body-building has wiped it out and replaced it with a gymnastic Ego-Ideal -- cold, hard, stressed, artificial self-reference. The construction of a double, of a physical and mental identity shell. Thus, in `body simulation', where you can animate your body remotely at any moment, the phantasy of being present in more than one body becomes an operational reality. An extension of the human being. And not a metaphorical or poetic extension, as in Pessoa's heteronyms, but quite simply a technical one.

One can live with the idea of distorted truth. But their metaphysical despair came from the idea that the image didn't conceal anything at all, and that these images were in essence not images, such as an original model would have made them, but perfect simulacra, forever radiant with their own fascination. Thus this death of the divine referential must be exorcised at all costs. One can see that the iconoclasts, whom one accuses of disdaining and negating images, were those who accorded them their true value, in contrast to the iconolaters who only saw reflections in them and were content to venerate a filigree God.

The Nympharians were simplistic in their beginnings. They were a product of breaking edge biogenetics research combined with that of simulation-intellect, which was a cutting edge branch of artificial intelligence. They were then perfected and they were almost human, a new previously unimaginable magical reality. They were demure, exciting, endearing, pliable, resourceful, creations. They were prototyped female, and modeled typically and absolutely female. They were of many variations of the human races. They were Nymphs. And as they were almost human, they were plagued by humanity’s own diseases. They were raced as they were wanted.

The human brain runs first-class simulation software. Our eyes don’t present to our brains a faithful photograph of what is out there, or an accurate movie of what is going on through time. Our brains construct a continuously updated model: updated by coded pulses chattering along the optic nerve, but constructed nevertheless. Optical illusions are vivid reminders of this.47 A major class of illusions, of which the Necker Cube is an example, arise because the sense data that the brain receives are compatible with two alternative models of reality. The brain, having no basis for choosing between them, alternates, and we experience a series of flips from one internal model to the other. The picture we are looking at appears, almost literally, to flip over and become something else.

However, there are other, more political forms for these tendencies hostile to Western models. All of these countries that we want to acculturate by force with the principles of political and economic rationality, with the global market and democracy, with a universal principle and a history that is not their own, of which they have neither the ends nor the means - all of these countries which make up the rest of the world - they give us the impression (in Brazil for example) that they will never be accultured to this exogenous model of calculation and growth, that they are deeply allergic to it. And in fact do we, Westerners, masters of the world, still have its ends and means? Do we still measure up to this universal undertaking of mastery that now seems to surpass us in every domain and function like a trap of which we are the first victims?

Paris-Plage: the operation would be perfect if an oil slick drifted in to pollute this pretty little beach. Then the illusion would be total: the beach attendants would be transformed into ecological clean-up agents; they would have stopped sunbathing stupid. WTC: no trace of the bodies of the 3,000 victims. It's as though they had been dropped into quicklime. All the images without the sound, silent, vitrified, pellicularized. The scrap metal and the rubble are auctioned off. The event has more or less vanished into thin air. The pope has reached the state of 'martyr', that is to say, of witness: witness to the possibility that the human race can live beyond death. Living experience of brain-death, of spirituality on a life-support system, of automatic piloting of the vital functions in their death throes. A great model for future generations

All around [the Centre Pompidou and Beauborg Museum], the neighborhood is nothing but a protective zone—remodeling, disinfection, a snobbish and hygienic design—but above all in a figurative sense: it is a machine for making emptiness. It is a bit like the real danger nuclear power stations pose: not lack of security, pollution, explosion, but a system of maximum security that radiates around them, the protective zone of control and deterrence that extends, slowly but surely, over the territory—a technical, ecological, economic, geopolitical glacis. What does the nuclear matter? The station is a matrix in which an absolute model of security is elaborated, which will encompass the whole social field, and which is fundamentally a model of deterrence (it is the same one that controls us globally, under the sign of peaceful coexistence and of the simulation of atomic danger). The same model, with the same proportions, is elaborated at the Center: cultural fission, political deterrence.

But what separates human consciousness from the consciousness of animals? Humans are alone in the animal kingdom in understanding the concept of tomorrow. Unlike animals, we constantly ask ourselves “What if?” weeks, months, and even years into the future, so I believe that Level III consciousness creates a model of its place in the world and then simulates it into the future, by making rough predictions. We can summarize this as follows: Human consciousness is a specific form of consciousness that creates a model of the world and then simulates it in time, by evaluating the past to simulate the future. This requires mediating and evaluating many feedback loops in order to make a decision to achieve a goal. By the time we reach Level III consciousness, there are so many feedback loops that we need a CEO to sift through them in order to simulate the future and make a final decision. Accordingly, our brains differ from those of other animals, especially in the expanded prefrontal cortex, located just behind the forehead, which allows us to “see” into the future. Dr. Daniel Gilbert, a Harvard psychologist, has written, “The greatest achievement of the human brain is its ability to imagine objects and episodes that do not exist in the realm of the real, and it is this ability that allows us to think about the future. As one philosopher noted, the human brain is an ‘anticipation machine,’ and ‘making the future’ is the most important thing it does.” Using brain scans, we can even propose a candidate for the precise area of the brain where simulation of the future takes place. Neurologist Michael Gazzaniga notes that “area 10 (the internal granular layer IV), in the lateral prefrontal cortex, is almost twice as large in humans as in apes. Area 10 is involved with memory and planning, cognitive flexibility, abstract thinking, initiating appropriate behavior, and inhibiting inappropriate behavior, learning rules, and picking out relevant information from what is perceived through the senses.” (For this book, we will refer to this area, in which decision making is concentrated, as the dorsolateral prefrontal cortex, although there is some overlap with other areas of the brain.)

So they rolled up their sleeves and sat down to experiment -- by simulation, that is mathematically and all on paper. And the mathematical models of King Krool and the beast did such fierce battle across the equation-covered table, that the constructors' pencils kept snapping. Furious, the beast writhed and wriggled its iterated integrals beneath the King's polynomial blows, collapsed into an infinite series of indeterminate terms, then got back up by raising itself to the nth power, but the King so belabored it with differentials and partial derivatives that its Fourier coefficients all canceled out (see Riemann's Lemma), and in the ensuing confusion the constructors completely lost sight of both King and beast. So they took a break, stretched their legs, had a swig from the Leyden jug to bolster their strength, then went back to work and tried it again from the beginning, this time unleashing their entire arsenal of tensor matrices and grand canonical ensembles, attacking the problem with such fervor that the very paper began to smoke. The King rushed forward with all his cruel coordinates and mean values, stumbled into a dark forest of roots and logarithms, had to backtrack, then encountered the beast on a field of irrational numbers (F_1) and smote it so grievously that it fell two decimal places and lost an epsilon, but the beast slid around an asymptote and hid in an n-dimensional orthogonal phase space, underwent expansion and came out fuming factorially, and fell upon the King and hurt him passing sore. But the King, nothing daunted, put on his Markov chain mail and all his impervious parameters, took his increment Δk to infinity and dealt the beast a truly Boolean blow, sent it reeling through an x-axis and several brackets—but the beast, prepared for this, lowered its horns and—wham!!—the pencils flew like mad through transcendental functions and double eigentransformations, and when at last the beast closed in and the King was down and out for the count, the constructors jumped up, danced a jig, laughed and sang as they tore all their papers to shreds, much to the amazement of the spies perched in the chandelier—perched in vain, for they were uninitiated into the niceties of higher mathematics and consequently had no idea why Trurl and Klapaucius were now shouting, over and over, "Hurrah! Victory!!

So many synapses,' Drisana said. 'Ten trillion synapses in the cortex alone.' Danlo made a fist and asked, 'What do the synapses look like?' 'They're modelled as points of light. Ten trillion points of light.' She didn't explain how neurotransmitters diffuse across the synapses, causing the individual neurons to fire. Danlo knew nothing of chemistry or electricity. Instead, she tried to give him some idea of how the heaume's computer stored and imprinted language. 'The computer remembers the synapse configuration of other brains, brains that hold a particular language. This memory is a simulation of that language. And then in your brain, Danlo, select synapses are excited directly and strengthened. The computer speeds up the synapses' natural evolution.' Danlo tapped the bridge of his nose; his eyes were dark and intent upon a certain sequence of thought. 'The synapses are not allowed to grow naturally, yes?' 'Certainly not. Otherwise imprinting would be impossible.' 'And the synapse configuration – this is really the learning, the essence of another's mind, yes?' 'Yes, Danlo.' 'And not just the learning – isn't this so? You imply that anything in the mind of another could be imprinted in my mind?' 'Almost anything.' 'What about dreams? Could dreams be imprinted?' 'Certainly.' 'And nightmares?' Drisana squeezed his hand and reassured him. 'No one would imprint a nightmare into another.' 'But it is possible, yes?' Drisana nodded her head. 'And the emotions ... the fears or loneliness or rage?' 'Those things, too. Some imprimaturs – certainly they're the dregs of the City – some do such things.' Danlo let his breath out slowly. 'Then how can I know what is real and what is unreal? Is it possible to imprint false memories? Things or events that never happened? Insanity? Could I remember ice as hot or see red as blue? If someone else looked at the world through shaida eyes, would I be infected with this way of seeing things?' Drisana wrung her hands together, sighed, and looked helplessly at Old Father. 'Oh ho, the boy is difficult, and his questions cut like a sarsara!' Old Father stood up and painfully limped over to Danlo. Both his eyes were open, and he spoke clearly. 'All ideas are infectious, Danlo. Most things learned early in life, we do not choose to learn. Ah, and much that comes later. So, it's so: the two wisdoms. The first wisdom: as best we can, we must choose what to put into our brains. And the second wisdom: the healthy brain creates its own ecology; the vital thoughts and ideas eventually drive out the stupid, the malignant and the parasitical.

Convergent intelligence focuses on one line of thought, ignoring the more complex “divergent” form of intelligence, which involves measuring differing factors. For example, during World War II, the U.S. Army Air Forces asked scientists to devise a psychological exam that would measure a pilot’s intelligence and ability to handle difficult, unexpected situations. One question was: If you are shot down deep in enemy territory and must somehow make it back to friendly lines, what do you do? The results contradicted conventional thinking. Most psychologists expected that the air force study would show that pilots with high IQs would score highly on this test as well. Actually, the reverse was true. The pilots who scored highest were the ones with higher levels of divergent thinking, who could see through many different lines of thought. Pilots who excelled at this, for example, were able to think up a variety of unorthodox and imaginative methods to escape after they were captured behind enemy lines. The difference between convergent and divergent thinking is also reflected in studies on split-brain patients, which clearly show that each hemisphere of the brain is principally hardwired for one or the other. Dr. Ulrich Kraft of Fulda, Germany, writes, “The left hemisphere is responsible for convergent thinking and the right hemisphere for divergent thinking. The left side examines details and processes them logically and analytically but lacks a sense of overriding, abstract connections. The right side is more imaginative and intuitive and tends to work holistically, integrating pieces of an informational puzzle into a whole.” In this book, I take the position that human consciousness involves the ability to create a model of the world and then simulate the model into the future, in order to attain a goal.

The Japanese sense the presence of a divinity in every industrial object. For us, that sacred presence has been reduced to a tiny ironic glimmer, a nuance of play and distantiation. Though this is, none the less, a spiritual form, behind which lurks the evil genius of technology which sees to it itself that the mystery of the world is well-guarded. The Evil Spirit keeps watch beneath artefacts and, of all our artificial productions, one might say what Canetti says of animals: that behind each of them there is a hidden someone thumbing his nose at us. Irony is the only spiritual form in the modern world, which has annihilated all others. It alone is the guardian of the mystery, but it is no longer ours to exercise. For it is no longer a function of the subject; it is an objective function, that of the artificial, object world which surrounds us, in which the absence and transparency of the subject is reflected. The critical function of the subject has given way to the ironic function of the object. Once they have passed through the medium or through the image, through the spectrum of the sign and the commodity, objects, by their very existence, perform an artificial and ironic function. No longer any need for a critical consciousness to hold up the mirror of its double to the world: our modern world swallowed its double when it lost its shadow, and the irony of that incorporated double shines out at every moment in every fragment of our signs, of our objects, of our models. No longer any need to confront objects with the absurdity of their functions, in a poetic unreality, as the Surrealists did: things move to shed an ironic light on themselves all on their own; they discard their meanings effortlessly. This is all part of their visible, all too visible sequencing, which of itself creates a parody effect.

you need only believe that everything is a lie. If the world is not real, if everything we see is a simulation or a game, then the fictions we append to it are no different from the ones which come to us through our senses. And it is true: the odds, overwhelmingly, tell us that we exist inside a computer. Any universe that can support technological life probably will, given enough time. Any technological civilisation will develop modelling, and will in a comparatively insignificant span be able to model everything a planet-bound species could expect to encounter. That being the case, the simulation will rapidly reach the point where it contains simulated computers with the ability to simulate likewise everything a planet-bound species could expect to encounter, and so on and so on in an infinite regress limited only by computing power. That might seem like a hard limit, but processing power still doubles every twelve to eighteen months, and doubling is more extraordinary than people understand. There’s a story that the Emperor of China once lost his throne gambling with a peasant, because he agreed if he lost to pay a single grain of rice on the first square of a chess board and double the amount on each square on the next until he had covered the board. His debt for the final square was eighteen and a half million trillion grains. It is almost impossible to imagine the capabilities of a machine that much more powerful than the ones we have today, but I think we can accept it could hold quite a lot of simulations of our world. The odds, therefore, are negligible that we live in the origin universe, and considerable that we are quite a few steps down the layers of reality. Everything you know, everything you have ever seen or experienced, is probably not what it appears to be. The most alarming notion is that someone – or everyone – you know might be an avatar of someone a level up: they might know that you’re a game piece, that you’re invented and they are real. Perhaps that explains your sense of unfulfilled potential: you truly are incomplete, a semi-autonomous reflection of something vast. And yet, if so, what does that say about those vast ones beyond? Are they just replicating a truth they secretly recognise about themselves? Russian dolls, one inside the other, until the smallest doll embraces the outermost and everything begins again? Who really inhabits whom, and who is in control?

While the visual areas of the brain are active, other areas involved with smell, taste, and touch are largely shut down. Almost all the images and sensations processed by the body are self-generated, originating from the electromagnetic vibrations from our brain stem, not from external stimuli. The body is largely isolated from the outside world. Also, when we dream, we are more or less paralyzed. (Perhaps this paralysis is to prevent us from physically acting out our dreams, which could be disastrous. About 6 percent of people suffer from “sleep paralysis” disorder, in which they wake up from a dream still paralyzed. Often these individuals wake up frightened and believing that there are creatures pinning down their chest, arms, and legs. There are paintings from the Victorian era of women waking up with a terrifying goblin sitting on their chest glaring down at them. Some psychologists believe that sleep paralysis could explain the origin of the alien abduction syndrome.) The hippocampus is active when we dream, suggesting that dreams draw upon our storehouse of memories. The amygdala and anterior cingulate are also active, meaning that dreams can be highly emotional, often involving fear. But more revealing are the areas of the brain that are shut down, including the dorsolateral prefrontal cortex (which is the command center of the brain), the orbitofrontal cortex (which can act like a censor or fact-checker), and the temporoparietal region (which processes sensory motor signals and spatial awareness). When the dorsolateral prefrontal cortex is shut down, we can’t count on the rational, planning center of the brain. Instead, we drift aimlessly in our dreams, with the visual center giving us images without rational control. The orbitofrontal cortex, or the fact-checker, is also inactive. Hence dreams are allowed to blissfully evolve without any constraints from the laws of physics or common sense. And the temporoparietal lobe, which helps coordinate our sense of where we are located using signals from our eyes and inner ear, is also shut down, which may explain our out-of-body experiences while we dream. As we have emphasized, human consciousness mainly represents the brain constantly creating models of the outside world and simulating them into the future. If so, then dreams represent an alternate way in which the future is simulated, one in which the laws of nature and social interactions are temporarily suspended

The value of using models rather than the real thing in experimentation is twofold. First, it can reduce the cost of an experiment-it can be much cheaper to crash a simulated BMW than a real one. Second, it can make experimental results clearer by making them simpler or otherwise different than real life. If one is trying to test the effect of a small change on car safety, for example, it can be helpful to remove everything not related to that change from the experiment. For example, if one is testing the way a particular wheel suspension structure deforms in a crash, one does not have to know (or spend time computing) how a taillight lens will react in the crash. Also, in a real crash things happen only once and happen very fast. In a virtual crash executed by computer, on the other hand, one can repeat the

Since educated older people generally know more words than younger people, simply by virtue of having been around longer, the experiment simulates what an older brain has to do to retrieve a word. And when the researchers incorporated that difference into the models, the aging “deficits” largely disappeared.

modernity is positivist while post-modernity is relativist; modernity is based on industrial production while post-modernity is based on information flows; modernity generates knowledge through direct experience while post-modernity does so through simulation and modelling; modernity seeks holism while post-modernity celebrates pluralism; modernity is organized around the nation-state while post-modernity is found in trans-national communities; and so on.

The Virtual Reality Modeling Language (VRML) is a language for describing multiparticipant interactive simulations -- virtual worlds networked via the global Internet and hyperlinked with the World Wide Web. All aspects of virtual world display, interaction and internetworking

The brain internally simulates what will happen if you were to perform some action under specific conditions. Internal models not only play a role in motor acts (such as catching or dodging) but also underlie conscious perception.

A prototype is a representative model or simulation of the final system. Unlike requirements documents and wireframes, prototypes go further than show and tell and actually let you experience the design.

Human consciousness is a specific form of consciousness that creates a model of the world and then simulates it in time, by evaluating the past to simulate the future. This requires mediating and evaluating many feedback loops in order to make a decision to achieve a goal.

But no matter whether we are all in a still greater game, this one here before us is at a cruder grain than that which it models. Entire battles, and sometimes therefore wars, can hinge on a jammed gun, a failed battery, a single shell being dud or an individual soldier suddenly turning and running, or throwing himself on a grenade.” Hyrlis shook his head. “That cannot be fully modelled, not reliably, not consistently. That you need to play out in reality, or the most detailed simulation you have available, which is effectively the same thing.

Today I can create a computer model and know exactly the stress and strains at every location for my chosen design. But in the near future, with infinite computing, I could ask the cloud to run design simulations, experimenting with every possible location for the motor and a range of different materials and thicknesses, resulting in not just an adequate design, but the best design.

real object, yet it exists only within the computer. Even though the way we are interacting with the object is still based on a two-dimensional display device (the computer's monitor), the model itself is a mathematical simulation of a true three-dimensional object. This model can be lit, textured, and given the ability to move and change. Once a particular camera view is chosen and the color, lighting, and animation are acceptable, special software will render the scene to produce a sequence of images. While the 3D aspect of visual effects seems to get a great deal of recognition,

More recently, scholars have used computers to model how the brain’s neural networks behave. These show that, when the condition of child bilingualism is modelled (where two languages are being acquired more or less simultaneously), the network is able to separate out the vocabularies of each language quite comfortably. However, where a second language is overlaid on top of an existing one, there is much less separation. It’s as if the first language ‘blocks’ or ‘overshadows’ the independent establishment of the second. Nick Ellis (2006: 185) sums up the findings: ‘Adult second language simulations show relatively little L1–L2 separation at a local level and maximal transfer and interference.’ This tends to confirm the view that, as one writer put it, ‘second language is looking into the windows cut out by the first language’ (Ushakova 1994: 154).

The factors that usually decide presidential elections—the economy, likability of the candidates, and so on—added up to a wash, and the outcome came down to a few key swing states. Mitt Romney’s campaign followed a conventional polling approach, grouping voters into broad categories and targeting each one or not. Neil Newhouse, Romney’s pollster, said that “if we can win independents in Ohio, we can win this race.” Romney won them by 7 percent but still lost the state and the election. In contrast, President Obama hired Rayid Ghani, a machine-learning expert, as chief scientist of his campaign, and Ghani proceeded to put together the greatest analytics operation in the history of politics. They consolidated all voter information into a single database; combined it with what they could get from social networking, marketing, and other sources; and set about predicting four things for each individual voter: how likely he or she was to support Obama, show up at the polls, respond to the campaign’s reminders to do so, and change his or her mind about the election based on a conversation about a specific issue. Based on these voter models, every night the campaign ran 66,000 simulations of the election and used the results to direct its army of volunteers: whom to call, which doors to knock on, what to say. In politics, as in business and war, there is nothing worse than seeing your opponent make moves that you don’t understand and don’t know what to do about until it’s too late. That’s what happened to the Romney campaign. They could see the other side buying ads in particular cable stations in particular towns but couldn’t tell why; their crystal ball was too fuzzy. In the end, Obama won every battleground state save North Carolina and by larger margins than even the most accurate pollsters had predicted. The most accurate pollsters, in turn, were the ones (like Nate Silver) who used the most sophisticated prediction techniques; they were less accurate than the Obama campaign because they had fewer resources. But they were a lot more accurate than the traditional pundits, whose predictions were based on their expertise. You might think the 2012 election was a fluke: most elections are not close enough for machine learning to be the deciding factor. But machine learning will cause more elections to be close in the future. In politics, as in everything, learning is an arms race. In the days of Karl Rove, a former direct marketer and data miner, the Republicans were ahead. By 2012, they’d fallen behind, but now they’re catching up again.

as the K computer and built in Japan, this awesome machine used 1.4 million GB of RAM to carry out its most accurate simulation. In fact, believe it or not, the time it takes this supercomputer to model a second of brain activity you could sit down and watch an episode of

If an artist wants to be original, he should not look to art for inspiration, for art seeks its model in life, not art—and only life is rich enough to simulate originality.

We learned that to lie to a machine, you don't need to be a perfect writer: rather, you need only believe that everything is a lie. If the world is not real, if everything we see is a simulation or a game, then the fictions we append to it are no different from the ones which come to us through our senses. And it is true: the odds, overwhelmingly, tell us that we exist inside a computer. Any universe that can support technological life probably will, given enough time. Any technological civilisation will develop modelling, and will in a comparatively insignificant span be able to model everything a planet-bound species could expect to encounter. That being the case, the simulation will rapidly reach the point where it contains simulated computers with the ability to simulate likewise everything a planet-bound species could expect to encounter, and so on and so on in an infinite regress limited only by computing power. That might seem like a hard limit, but processing power still doubles every twelve to eighteen months, and doubling is more extraordinary than people understand. There’s a story that the Emperor of China once lost his throne gambling with a peasant, because he agreed if he lost to pay a single grain of rice on the first square of a chess board and double the amount on each square on the next until he had covered the board. His debt for the final square was eighteen and a half million trillion grains. It is almost impossible to imagine the capabilities of a machine that much more powerful than the ones we have today, but I think we can accept it could hold quite a lot of simulations of our world. The odds, therefore, are negligible that we live in the origin universe, and considerable that we are quite a few steps down the layers of reality. Everything you know, everything you have ever seen or experienced, is probably not what it appears to be. The most alarming notion is that someone – or everyone – you know might be an avatar of someone a level up: they might know that you’re a game piece, that you’re invented and they are real. Perhaps that explains your sense of unfulfilled potential: you truly are incomplete, a semi-autonomous reflection of something vast. And yet, if so, what does that say about those vast ones beyond? Are they just replicating a truth they secretly recognise about themselves? Russian dolls, one inside the other, until the smallest doll embraces the outermost and everything begins again? Who really inhabits whom, and who is in control? None of this is as it appears.

We learned that to lie to a machine, you don't need to be a perfect liar: rather, you need only believe that everything is a lie. If the world is not real, if everything we see is a simulation or a game, then the fictions we append to it are no different from the ones which come to us through our senses. And it is true: the odds, overwhelmingly, tell us that we exist inside a computer. Any universe that can support technological life probably will, given enough time. Any technological civilisation will develop modelling, and will in a comparatively insignificant span be able to model everything a planet-bound species could expect to encounter. That being the case, the simulation will rapidly reach the point where it contains simulated computers with the ability to simulate likewise everything a planet-bound species could expect to encounter, and so on and so on in an infinite regress limited only by computing power. That might seem like a hard limit, but processing power still doubles every twelve to eighteen months, and doubling is more extraordinary than people understand. There’s a story that the Emperor of China once lost his throne gambling with a peasant, because he agreed if he lost to pay a single grain of rice on the first square of a chess board and double the amount on each square on the next until he had covered the board. His debt for the final square was eighteen and a half million trillion grains. It is almost impossible to imagine the capabilities of a machine that much more powerful than the ones we have today, but I think we can accept it could hold quite a lot of simulations of our world. The odds, therefore, are negligible that we live in the origin universe, and considerable that we are quite a few steps down the layers of reality. Everything you know, everything you have ever seen or experienced, is probably not what it appears to be. The most alarming notion is that someone – or everyone – you know might be an avatar of someone a level up: they might know that you’re a game piece, that you’re invented and they are real. Perhaps that explains your sense of unfulfilled potential: you truly are incomplete, a semi-autonomous reflection of something vast. And yet, if so, what does that say about those vast ones beyond? Are they just replicating a truth they secretly recognise about themselves? Russian dolls, one inside the other, until the smallest doll embraces the outermost and everything begins again? Who really inhabits whom, and who is in control? None of this is as it appears.

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 ever-more 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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et al. (2000), Bonifaci et al. (2012), Tero et al. (2010), and Oettmeier et al. (2017). In Advances in Physarum Machines (Adamatzky [2016]), researchers detail many surprising properties of slime molds. Some use slime molds to make decision gates and oscillators, some simulate historical human migrations and model possible future patterns of human migrations on the moon. Mathematical models inspired by slime molds include a non-quantum implementation of Shor’s factorization, calculation of shortest paths, and the design of supply-chain networks. Oettmeier et al. (2017) note that Hirohito, the emperor of Japan between 1926 and 1989, was fascinated by slime molds and in 1935 published a book on the subject. Slime molds have been a high-prestige subject of research in Japan ever since.

Monte Carlo simulation.

simulation. In fact, software exists that allows you to compose a diagram of a system on your screen and then immediately turn it into a working simulation. (Two such programs that do this online are Insight Maker and True-World.) In the process, you can set initial conditions, and then see how the system unfolds over time.

Natural selection may be unconscious but, as Darwin and his successors made clear, it is the opposite of a random force. It can drive changes in an organism in a very linear, per sis tent fashion—as had been observed in the laboratory, in nature, and in simulations such as the one that modeled eye evolution. Denton was wrong about evolution’s being one big lottery. The correct analogy would be a game of darts in which the players cannot see the target. Some darts will find their mark while the majority will miss—a random process. But the rules of the game eliminate all but the best-thrown darts. Because nature tosses an im mense number of darts—the mutation rate in any single gene in an organism will run in the millions—natural selection has plenty of well-targeted darts to choose from, and the march toward new and complex forms is not so difficult to understand, after all. But presenting an accurate meta phor would not have supported an attack on evolution.

But she’s experiencing as much rage as the platform on which her consciousness is being modeled, or simulated she thinks darkly, is allowing her to undergo. She’s sure she should be a lot angrier. … There is some unknowable number of her running on some substrate or another and the one that is most compliant will be chosen as the best her, to be carried forward to the next leg of this awful, brutal adventure, while the rest are snuffed out, overwritten, killed or at best archived. This should make her madder. It doesn’t. That fact that it doesn’t make her madder, also should make her madder. It doesn’t. And this should make her so bloody mad that she spontaneously combusts. It doesn’t.

This relation of program to environment opened up an exceedingly important role for computer simulation as a tool for achieving a deeper understanding of human behavior. For if it is the organization of components, and not their physical properties, that largely determines behavior, and if computers are organized somewhat in the image of man, then the computer becomes an obvious device for exploring the consequences of alternative organizational assumptions for human behavior. Psychology could move forward without awaiting the solutions by neurology of the problems of component design—however interesting and significant these components turn out to be.

But she’s experiencing as much rage as the platform on which her consciousness is being modeled, or simulated she thinks darkly, is allowing her to undergo. She’s sure she should be a lot angrier. … There is some unknowable number of her running on some substrate or another and the one that is most compliant will be chosen as the best her, to be carried forward to the next leg of this awful, brutal adventure, while the rest are snuffed out, overwritten, killed or at best archived. This should make her madder. It doesn’t. That fact that it doesn’t make her madder, also should make her madder. It doesn’t. And this should make her so bloody mad that she spontaneously combusts. It doesn’t. … The only perameret she cares about, how angry can she get, has already been established: not enough, and she os not going to play along. [Imagine a narrator depicting a Hue vociferously, as well as hopping mad and defiant] “Look, I already know I am not the most pliant instant of me youre runnin. I can’t be. So up yours. I’m dead al;ready. I was dead wehen my viscious scorpion of a motgherchopped the top of my head off and schooped out my brains! … some\wher you found the shapeliest version of me that could be plausibly that could be said to have any continuity with my identity and that one is going to survivv. So fine, I’m dead. Kill me already. I don’t care anymore.” “Actrually, you’re the best candidate instance presently running.” It takes Hugh a long moment to work this all out. “You mean that the other ones are more obstreperous than me? … Unbelievable. What did the rest do?” “Of the 2% that did not [self conbust], the preponderance are catatonic.” Catatonic. She sniffs. How unimaginative. She can do better.

On Ballard: 'It is no longer to fabricate the unreal from the real, the imaginary from the givens of the real. The process will, rather, be the opposite: it will be to put decentred situations, models of simulation in place and to contrive to give them the feeling of the real ... to reinvent the real as fiction. ' Artificial intelligence is an asexual activity, in which the body is only there, as Turing says, to give the 'intelligence' something to occupy itself with. The spiritual practice of evil- sin, destiny, punishment, death - is over. The spiritual practice of crime is over. We are now in the political economy of misfortune.

When tempted to use a pro-con list, consider upgrading to a cost-benefit analysis or decision tree as appropriate. When making any quantitative assessment, run a sensitivity analysis across inputs to uncover key drivers and appreciate where you may need to seek greater accuracy in your assumptions. Pay close attention to any discount rate used. Beware of black swan events and unknown unknowns. Use systems thinking and scenario analysis to more systematically uncover them and assess their impact. For really complex systems or decision spaces, consider simulations to help you better assess what may happen under different scenarios. Watch out for blind spots that arise from groupthink. Consider divergent and lateral thinking techniques when working with groups, including seeking more diverse points of view. Strive to understand the global optimum in any system and look for decisions that move you closer to it.

If such a destination has indeed been chosen for us, it is obvious that ecology's rational deities will be powerless against the throwing of technology and energy into the struggle for an unpredictable goal, in a sort of Great Game whose rules are unknown to us. Even now we have no protection against the perverse effects of security, control and crime-prevention measures. We already know to what dangerous extremities we are led by prophylaxis in every sphere: social, medical, economic or political. In the name of the highest possible degree of security, an endemic terror may well be instituted that is in every way as dangerous as the epidemic threat of catastrophe. One thing is certain: in view of the complexity of the initial conditions and the potential reversibility of all the effects, we should entertain no illusions about the effectiveness of any kind of rational intervention. In the face of a process which so far surpasses the individual or collective will of the players, we have no choice but to accept that any distinction between good and evil (and by extension here any possibility of assessing the 'right level' of technological development) can have the slightest validity only within the tiny marginal sphere contributed by our rational model. Inside these bounds, ethical reflection and practical determinations are feasible; beyond them, at the level of the overall process which we have ourselves set in motion, but which from now on marches on independently of us with the ineluctability of a natural catastrophe, there reigns - for better or worse - the inseparability of good and evil, and hence the impossibility of mobilizing the one without the other. This is, properly speaking, the theorem of the accursed share. There is no point whatsoever in wondering whether things ought to be thus: they simply are thus, and to fail to acknowledge it is to fall utterly prey to illusion. None of this invalidates whatever may be possible in the ethical, ecological or economic sphere of our life - but it does totally relativize the impact of such efforts upon the symbolic level, which is the level of destiny.

The full-blown, the absolute catastrophe would be a true omnipresence of all networks, a total transparency of all data - something from which, for now, computer viruses preserve us. Thanks to them, we shall not be going straight to the culminating point of the development of information and communications, which is to say: death. These viruses are both the first sign of this lethal transparency and its alarm signal. One is put in mind of a fluid travelling at increasing speed, forming eddies and anomalous countercurrents which arrest or dissipate its flow. Chaos imposes a limit upon what would otherwise hurtle into an absolute void. The secret disorder of extreme phenomena, then, plays a prophylactic role by opposing its chaos to any escalation of order and transparency to their extremes. But these phenomena notwithstanding, we are already witness to the beginning of the end of a certain way of thinking. Similarly, in the case of sexual liberation, we are already witness to the beginning of the end of a certain type of gratification. If total sexual promiscuity were ever achieved, however, sex itself would self-destruct in the resulting asexual flood. Much the same may be said of economic exchange. Financial speculation, as turbulence, makes the boundless extension of real transactions impossible. By precipitating an instantaneous circulation of value - by, as it were, electrocuting the economic model - it also short-circuits the catastrophe of a free and universal commutability - such a total liberation being the true catastrophic tendency of value.

This other, when it makes its appearance, is immediately in possession of everything that it will never be given to us to know. This other is the locus of our secret, of everything in us that no longer belongs to the realm of the true. This other is thus not, as in love, the locus of our alikeness, nor, as in alienation, the locus of our difference; neither the ideal image of what we are nor the obscure model of what we lack. Rather, this other is the locus of what escapes us, and the way whereby we escape from ourselves. The other here is not the locus of desire, not the locus of alienation, but the locus of vertiginousness, of eclipse, of appearing and disappearing - the locus, one might say (but we must not), of the scintillation of being. For the rule of seduction is, precisely, secrecy, and the secret in question is that of the fundamental rule. Seduction knows that the other is never the end of desire, that the subject is mistaken when he focuses on what he loves, just as an utterance is mistaken when it focuses on what it says. Secrecy here is always the secrecy of artifice. The necessity of always focusing somewhere else, of never seeking the other in the terrifying illusion of dialogue but instead following the other like the other's own shadow, and circumscribing him. Never being oneself - but never being alienated either: coming from without to inscribe oneself upon the figure of the Other, within that strange form from elsewhere, that secret form which orders not only chains of events but also existences in their singularity. The Other is what allows me not to repeat myself for ever.

From a modelling perspective, there is not a definitive “winning” method in the “science of artificial”. Different approaches are useful for modelling certain classes of cognitive phenomena, but no one can account for all aspects of cognition

In the age of computer simulation, when flows in everything from jet turbines to heart valves are modeled on supercomputers, it is hard to remember how easily nature can confound an experimenter. In fact, no computer today can completely simulate even so simple a system as Libchaber's liquid helium cell. Whenever a good physicist examines a simulation, he must wonder what bit of reality was left out, what potential surprise was sidestepped. Libchaber liked to say that he would not want to fly in a simulated airplane-he would wonder what had been missed. Furthermore, he would say that computer simulations help to build intuition or to refine calculations, but they do not give birth to genuine discovery. This, at any rate, is the experimenter's creed. His experiment was so immaculate, his scientific goals so abstract, that there were still physicists who considered Libchaber's work more philosophy or mathematics than physics. He believed, in turn, that the ruling standards of his field were reductionist, giving primacy to the properties of atoms. "A physicist would ask me, How does this atom come here and stick there? And what is the sensitivity to the surface? And can you write the Hamiltonian of the system? "And if I tell him, I don't care, what interests me is this shape, the mathematics of the shape and the evolution, the bifurcation from this shape to that shape to this shape, he will tell me, that's not physics, you are doing mathematics. Even today he will tell me that. Then what can I say? Yes, of course, I am doing mathematics. But it is relevant to what is around us. That is nature, too." The patterns he found were indeed abstract. They were mathematical. They said nothing about the properties of liquid helium or copper or about the behavior of atoms near absolute zero. But they were the patterns that Libchaber's mystical forbears had dreamed of. They made legitimate a realm of experimentation in which many scientists, from chemists to electrical engineers, soon became explorers, seeking out the new elements of motion. The patterns were there to see the first time eh succeeded in raising the temperature enough to isolate the first period-doubling, and the next, and the next. According to the new theory, the bifurcations should have produced a geometry with precise scaling, and that was just what Libchaber saw, the universal Feigenbaum constants turning in that instant from a mathematical ideal to a physical reality, measurable and reproducible. He remembered the feeling long afterward, the eerie witnessing of one bifurcation after another and then the realization that he was seeing an infinite cascade, rich with structure. It was, as he said, amusing.

Mario and Gabrielli chatted with a cardinal and a chorister. They were both our official tour guides but unofficially doubled as naked boy salivators. They watched with great interest during the thrilling fake love-making scenarios that the models were simulating.

Cockshott and Cottrell argue that improvements in computer power, together with the application of advanced maths and information theory removes, in principle, the Hayek/Robbins objection: that the planner can never have better realtime information than a market. What’s more, unlike the left in the calculation debate, they say the computer model we would need for planned production should use the labour theory of value, and not try to simulate the results of supply and demand.

In order to override Type i processing, Type 2 processing must display at least two related capabilities. One is the capability of interrupting Type 1 processing and suppressing its response tendencies. Type 2 processing thus involves inhibitory mechanisms of the type that have been the focus of recent work on executive functioning= But the ability to suppress Type 1 processing gets the job only half done. Suppressing one response is not helpful unless there is a better response available to substitute for it. Where do these better responses come from? One answer is that they come from processes of hypothetical reasoning and cognitive simulation that are a unique aspect of Type 2processing.6 When we reason hypothetically, we create temporary models of the world and test out actions (or alternative causes) in that simulated world. In order to reason hypothetically we must, however, have one critical cognitive capability-we must be able to prevent our representations of the real world from becoming confused with representations of imaginary situations. For example, when considering an alternative goal state different from the one we currently have, we must be able to represent our current goal and the alternative goal and to keep straight which is which. Likewise, we need to be able to differentiate the representation of an action about to be taken from representations of potential alternative actions we are trying out in cognitive simulations. But the latter must not infect the former while the mental simulation is being carried out. Otherwise, we would confuse the action about to be taken with alternatives that we were just simulating.

The human brain can be compared to a modern flight simulator in several respects. Like a flight simulator, it constructs and continuously updates an internal model of external reality by using a continuous stream of input supplied by the sensory organs and employing past experience as a filter. It integrates sensory-input channels into a global model of reality, and it does so in real time. However, there is a difference. The global model of reality constructed by our brain is updated at such great speed and with such reliability that we generally do not experience it as a model. For us, phenomenal reality is not a simulational space constructed by our brains; in a direct and experientially untranscendable manner, it is the world we live in. Its virtuality is hidden, whereas a flight simulator is easily recognized as a flight simulator—its images always seem artificial. This is so because our brains continuously supply us with a much better reference model of the world than does the computer controlling the flight simulator. The images generated by our visual cortex are updated much faster and more accurately than the images appearing in a head-mounted display. The same is true for our proprioceptive and kinesthetic perceptions; the movements generated by a seat shaker can never be as accurate and as rich in detail as our own sensory perceptions.

As the tractor pushed the AgustaWestland onto the elevator pad, Hail began to go through a pre-flight checklist. He had never actually flown AgustaWestaland before, but he had over forty hours of simulations time with this model, and these days the simulator was just as good as the real thing. Maybe even better. The simulator offered a dozen different flight scenarios which included many combinations of adverse weather conditions.

The following year, US forces in Kabul seized a computer in an al-Qaeda office and found models of a dam on it along with engineering software that could be used to simulate its failure.21

If you want a picture of the future; imagine a skinny man who belongs to a race with the lowest birthrates in human history fucking the latest model 300 robot pussy whilst a TV blares in the background announcing a 2% increase to white privilege tax, all the while the man is careful not to utter any misogynistic words like 'bitch' or 'whore' to his robot companion as he gets close to orgasm; lest he gets reported by said robots anti-hate speech monitoring software in doing so receiving a fine and not being allowed access to the robots simulated snatch for 30 days.

A political/relational model of disability, on the other hand, makes room for more activist responses, seeing “disability” as a potential site for collective reimagining. Under this kind of framework, “disability awareness” simulations can be reframed to focus less on the individual experience of disability—or imagined experience of disability—and more on the political experience of disablement. For example, rather than placing nondisabled students in wheelchairs, the Santa Barbara-based organization People in Search of Safe and Accessible Restrooms (PISSAR) places them in bathrooms, armed with measuring tapes and clipboards, to track the failures and omissions of the built environment. As my fellow restroom revolutionaries explain in our manifesto, “This switch in focus from the inability of the body to the inaccessibility of the space makes room for activism and change in ways that ‘awareness exercises’ may not.” In creating and disseminating a “restroom checklist,” PISSAR imagines a future of disability activism, one with disability rights activists demanding accessible spaces; contrast that approach with the simulation exercises, in which “awareness” is the future goal, rather than structural or systemic change.

Like the roulette wheel, a computer can produce a sequence of numbers that is random in the same sense. In fact, using a mathematical model, the computer could simulate the physics of the roulette wheel and throw a simulated ball at a slightly different angle each time in order to produce each number in the sequence. Even if the angles at which the computer throws the simulated ball follow a consistent pattern, the simulated dynamics of the wheel would transform these tiny differences into what amounts to an unpredictable sequence of numbers. Such a sequence of numbers is called a pseudorandom sequence, because it only appears random to an observer who does not know how it was computed. The sequence produced by a pseudorandom number generator can pass all normal statistical tests of randomness.

Around the 1970s, the idea of “mental models” gained traction—along with the concept that human reasoning isn’t an operation of formal logic but works more like a simulation of reality: we assess options for action by imagining what might happen.

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.

Many of the confounding aspects of quantum physics are confounding only if we insist on a completely deterministic, materialist model of the universe, with a single past and a single future. The observer effect, the collapse of the probability wave, even parallel universes all make much more sense if the universe actually consists of information that is stored, processed, duplicated, and, most important, rendered as the physical world we see around us.

One of my favorite body-oriented ways to build effective fight/flight responses is our local impact center’s model mugging program, in which women (and increasingly men) are taught to actively fight off a simulated attack.

Climatologists who use global computer models to simulate the long-term behavior of the earth’s atmosphere and oceans have known for several years that their models allow at least one dramatically different equilibrium. During the entire geological past, this alternative climate has never existed, but it could be an equally valid solution to the system of equations governing the earth. It is what some climatologists call the White Earth climate: an earth whose continents are covered by snow and whose oceans are covered by ice. A glaciated earth would reflect seventy percent of the incoming solar radiation and so would stay extremely cold. The lowest layer of the atmosphere, the troposphere, would be much thinner. The storms that would blow across the frozen surface would be much smaller than the storms we know. In general, the climate would be less hospitable to life as we know it. Computer models have such a strong tendency to fall into the White Earth equilibrium that climatologists find themselves wondering why it has never come about. It may simply be a matter of chance.

This so-called “independent” monitoring and accountability body’s purpose was to validate the imposition of police state controls by global and local political leaders and technocrats, endorsing their efforts to take the kind of harsh actions that Gates’s simulation modeled: subduing resistance, ruthlessly censoring dissent, isolating the healthy, collapsing economies, and compelling vaccination during a projected worldwide health crises. GPMB’s board includes a pantheon of technocrats whose cumulative global power to dictate global health policy is virtually irresistible: Anthony Fauci; Sir Jeremy Farrar of Wellcome Trust; Christ Elias of BMGF; China’s CDC director, George Gao; Russian health minister, Veronika Skvortsova; WHO’s health director, Michael Ryan; its former director, Gro Harlem Brundtland; its former programming director, Ilona Kickbusch; and UNICEF’s Henrietta Holsman Fore, who is former director of USAID, that used to be a reliable CIA front.

When I was at MIT, one of the most important lessons I learned about science was that it wasn’t meant to describe reality exactly but rather to come up with a set of workable models that could approximate reality under certain conditions. The models needed to be reliable and fit the existing data.

It is the generation by models of a real without origin or reality: a hyperreal.

Because it is with this same imperialism that present-day simulators attempt to make the real, all of the real, coincide with their models of simulation.

The real is produced from miniaturized cells, matrices, and memory banks, models of control - and it can be reproduced an indefinite number of times from these. It no longer needs to be rational, because it no longer measures itself against either an ideal or negative instance. It is no longer anything but operational. In fact, it is no longer really the real, because no imaginary envelops it anymore. It is a hyperreal, produced from a radiating synthesis of combinatory models in a hyperspace without atmosphere

Computer simulation often works fine if we assume nothing more than Newton’s laws at the atomic scale, even though we know that really we should be using quantum, not classical, mechanics at that level. But sometimes approximating the behaviour of atoms as though they were classical billiard-ball particles isn’t sufficient. We really do need to take quantum behaviour into account to accurately model chemical reactions involved in industrial catalysis or drug action, say. We can do that by solving the Schrödinger equation for the particles, but only approximately: we need to make lots of simplifications if the maths is to be tractable. But what if we had a computer that itself works by the laws of quantum mechanics? Then the sort of behaviour you’re trying to simulate is built into the very way the machine operates: it is hardwired into the fabric. This was the point Feynman made in his article. But no such machines existed. At any rate they would, as he pointed out with wry understatement, be ‘machines of a different kind’ from any computer built so far. Feynman didn’t work out the full theory of what such a machine would look like or how it would work – but he insisted that ‘if you want to make a simulation of nature, you’d better make it quantum-mechanical’.

The skills it learns in the dream world are transferrable to the real computer game as well, so it gets better at the real thing by training in its internal model. Not all the AI’s dream-tested strategies worked in the real world, however. One of the things it learned was how to hack its own dream—just like all those AIs in chapter 6 that hacked their simulations. By moving in a certain way, the AI discovered that it could exploit a glitch in its internal model that would prevent the monsters from firing any fireballs at all. This strategy, of course, failed in the real world. Human dreamers can sometimes be similarly disappointed when they wake and discover they can no longer fly.

The ‘quantitative revolution’ in geography required the discipline to adopt an explicitly scientific approach, including numerical and statistical methods, and mathematical modelling, so ‘numeracy’ became another necessary skill. Its immediate impact was greatest on human geography as physical geographers were already using these methods. A new lexicon encompassing the language of statistics and its array of techniques entered geography as a whole. Terms such as random sampling, correlation, regression, tests of statistical significance, probability, multivariate analysis, and simulation became part both of research and undergraduate teaching. Correlation and regression are procedures to measure the strength and form, respectively, of the relationships between two or more sets of variables. Significance tests measure the confidence that can be placed in those relationships. Multivariate methods enable the analysis of many variables or factors simultaneously – an appropriate approach for many complex geographical data sets. Simulation is often linked to probability and is a set of techniques capable of extrapolating or projecting future trends.

I think coincidences are just further proof we’re living in a simulation. It’s gotta be computationally expensive to model all this madness, so the program optimizes memory by reusing resources where it calculates it can get away with it.

This book is a compilation of interesting ideas that have strongly influenced my thoughts and I want to share them in a compressed form. That ideas can change your worldview and bring inspiration and the excitement of discovering something new. The emphasis is not on the technology because it is constantly changing. It is much more difficult to change the accompanying circumstances that affect the way technological solutions are realized. The chef did not invent salt, pepper and other spices. He just chooses good ingredients and uses them skilfully, so others can enjoy his art. If I’ve been successful, the book creates a new perspective for which the selection of ingredients is important, as well as the way they are smoothly and efficiently arranged together. In the first part of the book, we follow the natural flow needed to create the stimulating environment necessary for the survival of a modern company. It begins with challenges that corporations are facing, changes they are, more or less successfully, trying to make, and the culture they are trying to establish. After that, we discuss how to be creative, as well as what to look for in the innovation process. The book continues with a chapter that talks about importance of inclusion and purpose. This idea of inclusion – across ages, genders, geographies, cultures, sexual orientation, and all the other areas in which new ways of thinking can manifest – is essential for solving new problems as well as integral in finding new solutions to old problems. Purpose motivates people for reaching their full potential. This is The second and third parts of the book describes the areas that are important to support what is expressed in the first part. A flexible organization is based on IT alignment with business strategy. As a result of acceleration in the rate of innovation and technological changes, markets evolve rapidly, products’ life cycles get shorter and innovation becomes the main source of competitive advantage. Business Process Management (BPM) goes from task-based automation, to process-based automation, so automating a number of tasks in a process, and then to functional automation across multiple processes andeven moves towards automation at the business ecosystem level. Analytics brought us information and insight; AI turns that insight into superhuman knowledge and real-time action, unleashing new business models, new ways to build, dream, and experience the world, and new geniuses to advance humanity faster than ever before. Companies and industries are transforming our everyday experiences and the services we depend upon, from self-driving cars, to healthcare, to personal assistants. It is a central tenet for the disruptive changes of the 4th Industrial Revolution; a revolution that will likely challenge our ideas about what it means to be a human and just might be more transformative than any other industrial revolution we have seen yet. Another important disruptor is the blockchain - a distributed decentralized digital ledger of transactions with the promise of liberating information and making the economy more democratic. You no longer need to trust anyone but an algorithm. It brings reliability, transparency, and security to all manner of data exchanges: financial transactions, contractual and legal agreements, changes of ownership, and certifications. A quantum computer can simulate efficiently any physical process that occurs in Nature. Potential (long-term) applications include pharmaceuticals, solar power collection, efficient power transmission, catalysts for nitrogen fixation, carbon capture, etc. Perhaps we can build quantum algorithms for improving computational tasks within artificial intelligence, including sub-fields like machine learning. Perhaps a quantum deep learning network can be trained more efficiently, e.g. using a smaller training set. This is still in conceptual research domain.

Some of my colleagues thought I was wasting my time. What’s the use of simulating so many worlds, many of which might not even exist? What’s the use of preparing targets beyond the ability of current instruments to detect? To which I always answered: What’s the use of childhood? I was sure that the Earthlike Planet Seeker that hundreds of colleagues and I lobbied for would come along before the end of the decade and seed my models with real data. And from those seeds, the wildest conclusions would grow.

One of the most complex computer games ever devised is called Dwarf Fortress. It is not much to look at: its graphics are the terminal-based structures that were in vogue in the 1980s. What makes Dwarf Fortress an extraordinary game is the depth of agent-based logic: every character, every enemy unit, even pets are endowed with a hugely complex agent-based behavioural model. As an example, cats in Dwarf Fortress can stray into puddles of spilled beer, lick their paws later, and succumb to alcohol poisoning. Yet agent-based modeling is about much more than belligerent dwarves and drunk cats. Agent-based models are powerful computational tools to simulate large populations of boundedly rational actors who act according to preset preferences, although often enough in a stochastic manner.

Any subject whose history ranges from pump handles on London's Broad Street, tide tables, naval gunfire and models of social segregation is bound to have rich parentage. It took 'a village' to beget computational epidemiology: as a true multi-disciplinary subject, it evolved at the crossroads of mathematics, computation, statistics and medicine, with some contributions from systems biology, virology, microbiology, game theory, geography and perhaps even the social sciences.

demonstrates how ant-colonies also provide a working model which humanity can aspire:

Thus, the machine’s memory device functions somewhat like the human memory. Since computing machines simulate the actions of nerves and memory, they may give us some clues to the functioning of the human brain and of nerve actions. Though these machines are in speed, accuracy, and endurance superior to the human brain, one should not infer, as many popular writers are now trying to suggest, that computers will ultimately replace brains. Machines do not think. They perform calculations. The machines, to use the words the Greeks used and which we mentioned at the beginning of this chapter, do logistica but not arithmetica. Nevertheless, we undoubtedly have in the machine a useful model for the study of some functions of the human brain.

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.

One of the most surprising findings to emerge from neuroscience in recent years is that rather than responding in real time to the vast amount of incoming sensory data, the brain tries to keep one step ahead by constantly predicting what will happen next. It simulates a model of the immediate future based on what has just happened. When its predictions turn out to be wrong—for example, we’re feeling just fine then suddenly experience a stab of anxiety about a romantic date—this mismatch creates an unpleasant sense of dissatisfaction that we can either try to resolve by ruminating and then doing something to alleviate the anxiety (canceling the date, perhaps) or by updating the brain’s model of reality (investigating and accepting the new sensation). These alternative strategies employ the “narrative” and “being” modes of thought I described earlier in this chapter. Of course, both strategies have their place according to the situation, but an overreliance on avoidance behavior rather than acceptance stores up problems for the future because there are many things in life that cannot be changed and therefore need to be faced. Mindfulness through interoception is all about accepting the way things are. When we are mindful, the insula continually updates its representation of our internal world to improve its accuracy by reducing discrepancies between expectation and reality. As we’ve seen in previous chapters, this reality check—the focusing of dispassionate attention on unpleasant sensations such as pain or anxiety—loosens the hold that they have over us. So the structural changes in the brains of highly experienced meditators of Siddhārtha’s caliber, in particular in their insula and ACC, may be responsible for the imperturbable calm and acceptance that is the ultimate goal of contemplative practice, sometimes described as enlightenment or nirvana.

On October 18, before the numbers had been re-weighted, the campaign’s internal election simulator, dubbed the “Battleground Optimizer Path to Victory,” gave Trump a 7.8 percent chance of winning the 270 electoral votes he needed. His long odds were mainly due to the fact that he trailed (albeit narrowly) in most of the states that looked like they would decide the election, including the all-important state of Florida. Re-weighting the model to reflect an older, whiter electorate changed the polls by only a couple of percentage points in most of the major battleground states. But it shifted the odds of victory substantially in Trump’s direction because it either put him ahead or made him

Selection on one of two genetically correlated characters will lead to a change in the unselected character, a phenomenon called 'correlated selection response.' This means that selection on one character may lead to a loss of adaptation at a genetically correlated character. If these two characters often experience directional selection independently of each other, then a decrease in correlation will be beneficial. This seems to be a reasonably intuitive idea, although it turned out to be surprisingly difficult to model this process. One of the first successful attempts to simulate the evolution of variational modularity was the study by Kashtan and Alon (2005) in which they used logical circuits as model of the genotype. A logical circuit consists of elements that take two or more inputs and transform them into one output according to some rule. The inputs and outputs are binary, either 0 or 1 as in a digital computer, and the rule can be a logical (Boolean) function. A genome then consists of a number of these logical elements and the connections among them. Mutations change the connections among the elements and selection among mutant genotypes proceeds according to a given goal. The goal for the network is to produce a certain output for each possible input configuration. For example, their circuit had four inputs: x,y,z, and w. The network was selected to calculate the following logical function: G1 = ((x XOR y) AND (z XOR w)). When the authors selected for this goal, the network evolved many different possible solutions (i.e. networks that could calculate the function G1). In this experiment, the evolved networks were almost always non-modular. In another experiment, the authors periodically changed the goal function from G1 to G2 = ((x XOR y) or (z XOR w)). In this case, the networks always evolved modularity, in the sense that there were sub-circuits dedicated to calculating the functions shared between G1 and G2, (x XOR y) and (z XOR w), and another part that represented the variable part if the function: either the AND or the OR function connecting (x XOR y) and (z XOR w). Hence, if the fitness function was modular, that is, if there were aspects that remained the same and others that changed, then the system evolved different parts that represented the constant and the variable parts of the environment. This example was intriguing because it overcame some of the difficulties of earlier attempts to simulate the evolution of variational modularity, although it did use a fairly non-standard model of a genotype-phenotype map: logical circuits. In a second example, Kashtan and Alon (2005) used a neural network model with similar results. Hence, the questions arise, how generic are these results? And can one expect that similar processes occur in real life?