# Complexity  Author:: M. Mitchell Waldrop ## Highlights > the very richness of these interactions allows the system as a whole to undergo spontaneous self-organization. ([Location 66](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=66)) > Complex systems are more spontaneous, more disorderly, more alive than that. At the same time, however, their peculiar dynamism is also a far cry from the weirdly unpredictable gyrations known as chaos. In the past two decades, chaos theory has shaken science to its foundations with the realization that very simple dynamical rules can give rise to extraordinarily intricate behavior; witness the endlessly detailed beauty of fractals, or the foaming turbulence of a river. And yet chaos by itself doesn’t explain the structure, the coherence, the self-organizing cohesiveness of complex systems. ([Location 81](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=81)) > Instead, all these complex systems have somehow acquired the ability to bring order and chaos into a special kind of balance. This balance point—often called the edge of chaos—is were the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either. The edge of chaos is where life has enough stability to sustain itself and enough creativity to deserve the name of life. The edge of chaos is where new ideas and innovative genotypes are forever nibbling away at the edges of the status quo, and where even the most entrenched old guard will eventually be overthrown. ([Location 85](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=85)) > The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive, and alive. ([Location 91](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=91)) > Prigogine’s central point was that self-organization depends upon self-reinforcement: a tendency for small effects to become magnified when conditions are right, instead of dying away. ([Location 498](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=498)) > And suddenly, says Arthur, “I recognized it as what in engineering we would have called positive feedback.” Tiny molecular motions grow into convection cells. Mild tropical winds grow into a hurricane. Seeds and embryos grow into fully developed living creatures. Positive feedback seemed to be the sine qua non of change, of surprise, of life itself. ([Location 500](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=500)) > that’s why you get patterns in any system: a rich mixture of positive and negative feedbacks can’t help producing patterns. ([Location 538](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=538)) > High technology could almost be defined as “congealed knowledge,” says Arthur. “The marginal cost is next to zilch, which means that every copy you produce makes the product cheaper and cheaper.” More than that, every copy offers a chance for learning: getting the yield up on microprocessor chips, and so on. So there’s a tremendous reward for increasing production—in short, the system is governed by increasing returns. ([Location 669](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=669)) > “The royal road to a Nobel Prize has generally been through the reductionist approach,” he says—dissecting the world into the smallest and simplest pieces you can. “You look for the solution of some more or less idealized set of problems, somewhat divorced from the real world, and constrained sufficiently so that you can find a solution,” he says. “And that leads to more and more fragmentation of science. Whereas the real world demands—though I hate the word—a more holistic approach.” Everything affects everything else, and you have to understand that whole web of connections. ([Location 1013](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=1013)) --- Title: Complexity Author: M. Mitchell Waldrop Tags: readwise, books date: 2024-01-30 --- # Complexity  Author:: M. Mitchell Waldrop ## AI-Generated Summary None ## Highlights > the very richness of these interactions allows the system as a whole to undergo spontaneous self-organization. ([Location 66](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=66)) > Complex systems are more spontaneous, more disorderly, more alive than that. At the same time, however, their peculiar dynamism is also a far cry from the weirdly unpredictable gyrations known as chaos. In the past two decades, chaos theory has shaken science to its foundations with the realization that very simple dynamical rules can give rise to extraordinarily intricate behavior; witness the endlessly detailed beauty of fractals, or the foaming turbulence of a river. And yet chaos by itself doesn’t explain the structure, the coherence, the self-organizing cohesiveness of complex systems. ([Location 81](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=81)) > Instead, all these complex systems have somehow acquired the ability to bring order and chaos into a special kind of balance. This balance point—often called the edge of chaos—is were the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either. The edge of chaos is where life has enough stability to sustain itself and enough creativity to deserve the name of life. The edge of chaos is where new ideas and innovative genotypes are forever nibbling away at the edges of the status quo, and where even the most entrenched old guard will eventually be overthrown. ([Location 85](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=85)) > The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive, and alive. ([Location 91](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=91)) > Prigogine’s central point was that self-organization depends upon self-reinforcement: a tendency for small effects to become magnified when conditions are right, instead of dying away. ([Location 498](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=498)) > And suddenly, says Arthur, “I recognized it as what in engineering we would have called positive feedback.” Tiny molecular motions grow into convection cells. Mild tropical winds grow into a hurricane. Seeds and embryos grow into fully developed living creatures. Positive feedback seemed to be the sine qua non of change, of surprise, of life itself. ([Location 500](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=500)) > that’s why you get patterns in any system: a rich mixture of positive and negative feedbacks can’t help producing patterns. ([Location 538](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=538)) > High technology could almost be defined as “congealed knowledge,” says Arthur. “The marginal cost is next to zilch, which means that every copy you produce makes the product cheaper and cheaper.” More than that, every copy offers a chance for learning: getting the yield up on microprocessor chips, and so on. So there’s a tremendous reward for increasing production—in short, the system is governed by increasing returns. ([Location 669](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=669)) > “The royal road to a Nobel Prize has generally been through the reductionist approach,” he says—dissecting the world into the smallest and simplest pieces you can. “You look for the solution of some more or less idealized set of problems, somewhat divorced from the real world, and constrained sufficiently so that you can find a solution,” he says. “And that leads to more and more fragmentation of science. Whereas the real world demands—though I hate the word—a more holistic approach.” Everything affects everything else, and you have to understand that whole web of connections. ([Location 1013](https://readwise.io/to_kindle?action=open&asin=B07WVV5J2R&location=1013))