We should also bear in mind that simple physical systems governed by simple laws can nonetheless generate novel behavior. Indeed, over the last few decades chaos theory has amply demonstrated the unpredictability and surprising behavior that certain seemingly simple physical systems can display. So even though the laws of physics may be understood, the long-term effects of those laws can be utterly novel. To suggest that the Universe is computational and controlled by software-like laws does not imply that the future is determined. Indeed, chaos theory teaches us that novelty and unpredictable surprise are an inherent feature of reality.
Is Reality a Bit Fishy?
The laws of physics, such as they are, require an initial input state in which to manifest themselves. This initial state would appear to be the initial conditions at the time of the alleged big bang, conditions that many cosmologists have argued had to have been highly specific in order that the Universe evolve in the way it has. Here we face a deep mystery. Why that particular set of initial conditions, and why those laws of physics?
In many of his books, Paul Davies (whom I quoted earlier) concludes that the Universe appears to be a bit fishy. Davies refuses to accept that the laws of physics and the initial conditions just happen to have been that way. It appears too good to be true, especially as we are around to speculate upon it. Either one accepts these fundamental properties of Nature as being unexplainable “brute facts,” or one can try to account for them in some kind of metaphysical way.
As we are once more entering unusual territory, let’s quickly recap. We have been trying to understand reality as an ongoing computation in which all of the Universe’s information is being relentlessly processed via countless state transitions. This informational process has led to the (novel) formation of galaxies, stars, planets, life,
If this line of reasoning already suggests the presence of a God of some kind, then it is because our vocabulary is severely limited when it comes to discussing these types of issue. This is a relatively new area of thought, for only in the last few decades have scientists begun to seriously contend with why things are the way they are, with why the Universe appears to be somewhat fishy. These are legitimate questions to ask, although they extend well beyond the limited scope of science.
I believe that since we are inextricably caught up in the unfolding Universe, wherever it might be leading, then it is surely in our interests to confront the situation head on. In fact, we should demand to be enlightened as to what is really going on here. As I have made clear, natural entheogens and their ability to foster transcendental forms of cognition are perhaps the greatest tools at hand for coming to terms with these questions about reality. Create the right sort of neurochemical alchemy, bring the right sort of natural ingredients into place, and information seems to conveniently orchestrate itself into revelatory patterns of understanding. This is the method, perhaps, whereby Nature resolves an understanding of itself through the vehicle of consciousness.
However, before we go on to form a conclusion from our informational view of things, it will be useful here to show in more detail how the computational processing of information according to a few very basic rules can nonetheless yield organized forms and structures. In particular I would like to welcome to this chapter the extraordinary world of the cellular automaton. This is not as dull as it sounds, and since such a system is very simple to grasp, it lends itself well to our computational/informational paradigm.
The Game of Life
A cellular automaton is a classic computational-cum-informational system able to yield lifelike phenomena, and it is therefore a model that captures, at least in part, Nature’s life-making capacity. Oddly enough, the study of these systems has its roots in a novel Mexican mushroom, only this time the mushroom in question is the malignant mushroom cloud of the atomic bomb.
The atomic bomb was created in the army laboratories of Los Alamos in New Mexico as part of America’s Manhattan Project. In fact, it was in response to the cautionary word of Einstein himself that the USA originally attempted to crack the atom for weaponry purposes. In 1939, Einstein, who was then seeking asylum in the USA, wrote to President Roosevelt concerning Germany’s widespread and zealous search for uranium. It was painfully clear to Einstein that the implications of his E=MCA? equation were being followed through to their ultimately explosive end and that the USA would do well to keep abreast of this disturbing development. On the strength of Einstein’s warning, American authorities galvanized themselves into developing an atomic bomb before Germany managed it, and thus the Manhattan Project was born.
After the end of World War II, the Manhattan Project built a prototypical electronic computer system called ENIAC (Electronic Numerical Integrator and Computer). This was the first operational, general-purpose, electronic digital computer, and it was initially used to solve various ballistic calculations. The success of this “giant brain,” as the press called it, stimulated the development of other computing machines and helped pave the way for the modern computer industry.
Computations on ENIAC were supervised at Los Alamos in part by eminent mathematician John von Neumann. Although von Neumann was a mathematical wizard, his ethical stance was a little questionable. Not only was he an extremely vocal advocate for the total nuclear destruction of Russia before that country developed a nuclear capability, and not only did he feel that it was safe to carry out and closely observe nuclear test explosions (he was later to die of bone cancer, probably caused by witnessing nuclear explosions at Bikini Atoll), he even devised plans to dye the polar ice caps in order to melt them. He also helped design the nuclear bombs that were detonated over Japan.
Despite these cheery idiosyncrasies, it was von Neumann who first began to study the computational properties of cellular automata on the bulky computers at Los Alamos. Von Neumann had always been fascinated by the idea of self-replicating machines, though he believed that ultimately this was not possible using only vacuum tubes, transistors, and the like. However, by utilizing the new computers that were at hand, von Neumann was able to implement a computer program in which simulated life-forms were able to replicate themselves. The program was the original cellular automaton. That these self-replicating, computer-generated entities were not made of flesh or machine parts did not matter, as it was their logical and organizational structure that defined them. This was one of the first real insights into the simulational power of computers. They could create convincing forms of life.
Von Neumann’s work was given a whole new lease on life (literally) by Cambridge mathematician John Conway, who in 1970 invented a cellular automaton called the Game of Life. The game is deceptively simple, yet it is able to generate an endless amount of complexity and variation. It also mirrors the computational quality of biological life.
The Game of Life is referred to as a cellular automaton because it proceeds within a grid of cells (like graph paper) and because the game’s progression is entirely automatic. The game progresses according to four rules. These four rules are applied again and again to the current state of the cells in the grid. Cells are either occupied or not—which means the system holds binary values. Cells are digital, on or off, alive or dead. These are the four simple rules:
1. Any live cell with fewer than two live neighbors dies, as if caused by underpopulation.
2. Any live cell with two or three live neighbors lives on to the next generation.
3. Any live cell with more than three live neighbors dies, as if by overcrowding.
4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction.
An initial configuration of on/off (that is, live or dead) cells is provided as input, and then the four seemingly
