a lifebox is a small interactive device to which you tell your life story. It prompts you with questions and organizes the information you give it. As well as words, you can feed in digital images, videos, sound recordings, and the like. It’s a bit like an intelligent blog. Once you get enough information into your lifebox, it becomes something like a simulation of you.

Not only is it unfeasible to digitally emulate the global weather; even simulating the turbulent flow of tap water is beyond our existing electronic machines. But—and this is my point—the processes may well be computations anyway.

Human thought is certainly a feasible computation for the human brain, it’s just not currently feasible for electronic computers.

when you can’t see a simple explanation for a natural phenomenon, this means that the phenomenon is not only complex, but of a maximal complexity. Anything that’s not obviously simple is in fact very gnarly.

Cyberspace was an alternate reality, it was the huge interconnected computation that was being collectively run by planet Earth’s computers around the clock. Cyberspace was the information network, but more than the Web, cyberspace was a shared vision of the Web as a physical space. 14

physics happens in parallel, that is, physics is being computed everywhere at once rather than within the circuitry of a single processor chip.

Any fluid flow is rich enough to generate random-looking patterns quite on its own. You don’t need any supplemental inputs to churn things up. The computation is class four on its own.

The original meaning of “gnarl” was simply “a knot in the wood of a tree.” In California surfer slang, “gnarly” came to be used to describe complicated, rapidly changing surf conditions. And then, by extension, something gnarly came to be anything with surprisingly intricate detail.

gnarly in the sense of being beautifully intricate, with purposeful-looking but not quite comprehensible patterns

patterns of the water are clearly very complicated, they aren’t random. The forms of the waves are, from moment to moment, predictable by the laws of fluid motion. Waves don’t just pop in and out of existence. Water moves according to well-understood physical laws. It’s a deterministic computation.

chaotic computer simulations will occasionally tighten in on characteristic rhythms and clusters that act as chaotic attractors. In either case, we’re dealing with a class four computation.

Unpredictable computer simulations are often produced either by running one algorithm many times (as with the famous Mandelbrot set) or by setting up an arena in which multiple instances of a single algorithm can interact (as in CAs).

We find the same spectrum of disorder across a wide range of systems—mathematical, physical, chemical, biological, sociological, and economic. In each domain, at the ordered end we have class one constancy and a complete lack of surprise. One step up from that is periodic class two behavior in which the same sequence repeats itself over and over again—as in the structure of a crystal. Adding a bit more disorder leads us into the class four or gnarly zone, the region in which we see interesting behaviors. And at the high end of the spectrum is the all-but-featureless randomness of class three.

The most orderly kind of gnarly behavior is quasiperiodic, or nearly periodic. Something like this might be a periodic function that has a slight, unpredictable drift. Next comes the strange attractor zone in which the system generates easily visible structures—like the gliders in a CA rule, or like standing waves in a stream. Then we enter a critical transition zone, which is the heart of the gnarl. In the language of chaos theory, a system undergoes a bifurcation when a system switches to a new attractor. This is when a system begins ranging over a completely different zone of possibilities within the space of all possible phenomena.

Bifurcation means nothing more than changing something about a system in such a way as to make its behavior move to a different attractor. 36

like a cartoon character with a halo of alertness rays.

thanks to atomism, we can’t really measure much past twenty digits, and even if we could, quantum mechanics makes space fairly meaningless out past the thirty-fifth digit.

if the fear of death is indeed the issue, why not find solace in thinking of the universe as an immense logical system of which you’re a tiny part? When your particular pattern ceases to exist, the grand computation will continue. Your allotted region of spacetime will “always” be around. Can’t that be enough? For that matter, what’s so terrible about death? Personally, I don’t really mind the notion of someday getting off the stage and no longer having to continue my long-winded computation—but maybe that’s just because I’m getting old.

It’s at least conceivable that photons themselves are the averaged-out results of still more fundamental phenomena—not necessarily subparticles, but possibly something like network patterns or linked loops in a multidimensional superspace.

This odd sequence of spreading-wave-followed-by-collapse-into-particle is a standard pattern in quantum mechanics. Any system is to be thought of as an abstract wave that obeys deterministic analog laws until some kind of measurement is performed on the system.

While Einstein’s general theory of relativity was inspired by a specific geometrical vision of curved space, quantum mechanics seems to have arisen as the haphazard result of symbol pushing and mathematical noodling.

Seemingly fundamental entities such as photons, electrons, and their wave functions may in fact be emergent patterns based upon a low-level sea of computation.

superposed states, which serves, if nothing else, as a very useful metaphor for the human mind. “Superposed” connotes having multiple layers overlaid and merged.

A coherent system evolves peacefully through a series of superposed states, whereas a decoherent system has its states affected by entanglements with the environment.

In quantum mechanics, the only way to force a system to remain in a pure state is to continually decohere it; this is expressed in the folk saying, “A watched pot never boils.”

Once two particles have interacted in certain ways, their wave functions become permanently entangled, with the effect that when you measure one member of the pair, the wave function of the other member is affected as well—no matter how distant from each other the partners may be.

amanita mushrooms are lethal because they block the action of mRNA, leaving the cells to exhaust their specialized, short-lived proteins.

Looking within yourself, your brain’s electrochemical behavior is surely a class four activator-inhibitor process that could be thought of as a kind of morphogenesis. From the viewpoint of spacetime, an organism’s “form” includes its behavior patterns as surely as the pigmentation patterns of the being’s skin. My thoughts are forms that my body grows.

Perhaps the most famous class four activator-inhibitor pattern is a one-dimensional rule often discussed by Stephen Wolfram and Hans Meinhardt. This rule is expressed in the patterns found on cone shells. The growing lip of the shell is regarded as a row of cells, with each cell containing activator and inhibitor morphogens whose concentrations vary according to activator-inhibitor systems. As time goes on, the lip of the shell grows—the growth direction would be down the page in Figure 60. We can think of the shell’s default color as being dark, with “bumps” of white pigment forming with relative abruptness along the lip, then slowly melting away. All of this can be orchestrated by activator-inhibitor systems.

DNA isn’t a blueprint, it’s a set of tweak parameters.

Homeostasis is a hierarchy of self-adjusting computations, with no frantic central controller trying to figure everything out.

Gnarly Neighbors No organism lives on its own—creatures eat each other, deal with each other’s changes to the environment, form symbiotic partnerships, and share genetic material. Once again we can single out three levels of ecological computation. At the high level, the population size of a species varies according to its interactions with the environment and with other species. Very often we can summarize the relations as a simple set of mathematical rules, and when we carry out simulations of these rules, we discover interestingly chaotic patterns in time and space. Species may compete or prey upon one another, but they can also behave symbiotically, which involves a medium level of computational ecology. In symbiosis, different species help each other to flourish—humans are symbiotic with, for instance, cattle. Where you find cows, you find humans, and vice versa. If this connection seems too loose, consider our even tighter bonds with the bacteria who populate our guts. Over the millennia, various species have gone beyond symbiosis to merge physically. Many features of modern cells are thought to have once been independent organisms. Nuclei, mitochondria, chloroplasts, flagellae—all may once have had lives of their own. Symbiotic and merged-in creatures function as subcomputations of the host creature’s computation. Actually, if you think about symbiosis, you end up at the highest possible level: seeing our planet as covered with a single seamless web of life that comprises the Earth-wide superorganism called Gaia. A common reaction to the Gaia notion is to object that we’re separate individuals. But the bacteria living in your intestines are also separate individuals as well as being part of a higher-level organism. At perhaps the lowest level, creatures share DNA across species boundaries. A very large part of human DNA, for instance, is the same as is found in other organisms—evolution tends not to throw out old gene sequences. The symbiotic merging of species is another cause of DNA sharing. And yet another reason for the diffusion of DNA across the ecosystem is that bacteria commonly swap stretches of their genomic material, quite independent of reproduction.

DNA really isn’t like a blueprint. DNA serves, rather as a recipe for a bunch of proteins that become involved in autocatalytic reactions that just happen to create the forms of the organism in question.

Lindenmayer’s collaborator Przemyslaw Prusinkiewicz had created a tweakable computer program to grow three-dimensional forms resembling that exact plant in the vacant lot: stems, leaves, flowers, seeds, and all. Where I’d seen a weed, Lindenmayer saw a computation.

biological fractals only branch a finite number of times.

Evolution is a long-running parallel computation by the individuals in an ecology.

evolution leads to adaptation, that is, to the development of species tuned to the world’s available niches.

It’s my impression that successful life-forms are always gnarly—in the sense of having class four behavior. That is, they tend to lie at the interface between order and apparent randomness.

society as a whole can also be said to compute, using its members as networked parallel processors.

5.1: Hive Minds. People’s motions and emotions play off those of their peers, leading to emergent group behaviors. Your brain is an individual node of society’s hive mind. The hive mind is in some sense conscious, but it is a mind quite unlike any individual person’s. • 5.2: Language and Telepathy. Language is the primary communication medium linking society’s members. Speech encodes mental states, which in turn represent the world at various levels of abstraction. It’s interesting to look at language as a kind of network itself, in that a word is viewed as having links to the other words you associate with it. This network obeys a certain kind of statistical pattern known as an inverse power law. • 5.3: Commercial and Gnarly Aesthetics. Society has a group memory that’s based both on oral transmission of knowledge and on information-dense artifacts such as books, paintings, buildings, movies, Web pages, and computer programs. I’ll discuss why it is that inverse power laws also characterize the popularity of our cultural information artifacts. Inverse power laws mean that only a few authors and artists can earn a living, and that a handful of familiar chain stores soak up the lion’s share of the retail business. Nevertheless, nothing stays on top forever; I’ll discuss how this fact relates to what computer scientists call self-organized criticality. At the end of the section I explore literary aesthetics in terms of gnarl. • 5.4: Power and Money. In government and in the marketplace, powerful forces are forever trying to turn society into a controllable class two computation. But no regime lasts forever, and no corporations are immortal. The unpredictability of society’s class-four computation acts as a perennial force for revolution. • 5.5. The Past and Future History of Gnarl. First point: The history of the world isn’t only about presidents, wars, and kings. Society’s computation consists of all its members’ actions, and an historian does well to focus on art, science, technology, and popular culture. Second point: Looked at in a certain way, the history of technology is a history of mankind’s increasing mastery of various forms of computation. I include a table listing a possible future sequence of computation-related inventions.

think of pigeons circling a city square, a band of sparrows in a hedge, or a gang of seagulls going after a beachgoer’s picnic. From time to time a single bird’s action can decisively affect the whole flock, but normally the motions emerge from the interactions of the birds’ computations.

think about the vast parallel computation that the conversations around us perform. You have the opportunity to stop identifying with your limited body, and to share in the networked computation of the group mind.

The stories presented by a society’s media can be regarded as the society’s image of the world. In this context, we can think of a society’s collective communication and information resources as the society’s brain.

computers already dominate Earth. There’s really nothing to overthrow, no power to seize. Our machines are the cells the planetary computer is made up of. And we devote considerable energy to building and maintaining these machines. We’re already their freakin’ servants.

So far as I know, no experimenter has ever taught an individual ant anything, not even a solution to the simplest Y-maze. So how does an ant colony think? By communication. As the ants react to one another’s signals, group behaviors emerge.

Part of being a colorful speaker or writer is having the gift of choosing words whose subsidiary meanings complement, contrast with, or comment upon the primary meaning.