[ I will be speaking on some of my experiences involving software at Garum Day, an event in Bilbao, Spain, on Feburary 16, 2011. Part of my talk, and today’s post, will derive from the “Computer Hacker” chapter of my memoir, Nested Scrolls: A Writer’s Life, due out from PS Publishing in April, 2011, and Forge Books in Fall, 2011. ]

My new hacker friend John Walker was a founder and the CEO of a booming Sausalito corporation called Autodesk, and in 1988 he asked me if I’d be interested to come work for him. Autodesk had done very well with their drafting software, and they had a big surplus in the bank. Walker wanted to explore some radically new kinds of software products.

Autodesk’s core business was a product called AutoCAD, an electronic drafting program used worldwide by architects and industrial designers. Walker didn’t want me to work on that. Instead he was starting a small Advanced Technology Division, headed by Eric Lyons, and, for the moment, me and one or two other guys.

My first project was to produce some cellular automata software with Walker. He was an insanely talented programmer. He worked at the level of a grand master in chess, or at the level of a mathematician at the Institute for Advanced Study. Over Autodesk’s one-week-long Christmas break, Walker wrote an assembly language program that eliminated any need for a special card such as the so-called cellular automaton machine I’d been carrying around.

My role in this was to create some sample CA rules for our new software to run, and to write a manual explaining it all. I got deeply into the task. Walker and I and finished our project over the course of several months. When we were done, we’d produced a slick, boxed software package called CA Lab: Rudy Rucker’s Cellular Automata Laboratory, which sold for about $50 and went on the market in 1989. In those pre-Internet days, some people were actually willing to buy software of this kind on disks. I did demos of it at a number of computer trade fairs, always having to parry the same old question.

“What’s it good for?”

“You stare CAs for hundreds and hundreds of hours and they eat your brain, okay?”

We sold a decent number of copies, and Walker had the idea that we could develop a whole line of software packages for hackers to enjoy. These packages were meant to be like books, but interactive, illustrating new aspects of science. Walker wanted to call the line the Autodesk Science Series.

The second package in the series was James Gleick’s Chaos: The Software, designed to let users play with some of the programs mentioned in Gleick’s best-selling book Chaos.

What was the chaos craze all about? Chaos is another new idea whose true origins lie in computer science. We all know about simple, deterministic processes that do something utterly predictable—like a cannonball flying along a predetermined parabola through the air. We also know about completely messy natural processes, such as the crackling static we might hear on a radio.

Chaotic processes lie midway between the extremes of predictability and randomness. On the one hand, a chaotic process doesn’t settle into any kind of dull and simple pattern. On the other hand, a chaotic process isn’t actually random. It’s generated by some fairly simple and deterministic law of math or physics.

There’s a certain overlap here with Charles Bennett’s notion of logical depth . A chaotic pattern is logically deep in that it’s generated by a concise rule that uses a long computation in order to produce the patterns that you see.

The hard thing to grasp about a messy-looking chaotic process is that it is in fact deterministic. If, for instance, you set about computing the successive digits of pi, you’ll always end up with that same number sequence, 3.1415926… So all the digits of pi are in some sense predetermined. But yet—and this is the subtle point—the digits aren’t predictable, at least not predictable by any rapidly-acting rule of thumb. Yes, someone like Bill Gosper can compute the billionth digit of pi, but he needs to run a powerful computer through quite a few cycles in order to come up with the answer. There are some good modern formulae, bu there’s no quick and dirty pencil-and-a-scrap-of-paper shortcut for finding the billionth digit of pi. It’s going to take you about a billion steps, no matter what. Pi is gnarly, pi is chaotic, pi is logically deep.

In his bestselling Chaos, Gleick talked about some mathematical systems that were known to generate chaotic patterns. Among these were the Lorenz attractor and the Mandelbrot set, and we put simulations of these into the Autodesk Chaos software, along with some other funky things.

Working on this second Autodesk program all through 1989 and 1990 was a lot harder for me than working on CA Lab had been. The big difference was that this time Walker didn’t step in and write the bulk of the code. Instead I worked with another Autodesk programmer, a knowledgeable and irascible guy called Josh Gordon. Truth be told, my own programming skills were still pretty rudimentary. I was in over my head. And Josh was never shy about telling me this. But somehow we struggled to a conclusion and in 1991 we shipped this second product, too.

Later, on my own, I’d write a third science series program called Artificial Life Lab, which would be published as a disk with a book in 1993, not by Autodesk, but by the low-end Waite Group Press in the North Bay. I might mention that, annoyingly, the Waite Group refused to pay me my royalties on the Japanese edition of the book.

The three software packages that I worked on, CA Lab, Chaos, and Artificial Life Lab, are all long out of print by now, but you can download them for free from my website. Note that eventually we had to change the name of CA Lab to Cellab. A company called Computer Associates was threatening to sue us for infringing on their sacred trademarked initials CA. As if cellular automata hadn’t been around much longer than them!

[Today, some reworked travel notes from 1999 that may make their way into my novel-in-progress Turing & Burroughs. Photos from around Los Gatos and Berkeley in the last week of January, 2011.]

Alan Turing sat on the balcony of his room near Las Cruces, New Mexico, looking at the beautiful silhouette of some low mountains across a plowed field, the range like a long jawbone with teeth in it¬—a cow or dog jawbone that one might find in the woods. A dove sat on a twisting piñon branch in the shade of the tree’s main trunk, an iconic silhouette. A train not too far off was sounded its horn for the crossings in this land of trains.

A red squirrel ram up a twisty pine tree: the squirrel fit the tree, and the two of them fit Alan’s perceptions of what he should see. Everything fit. It struck him that he and the plants and animals and the skugs were all of a piece, they were all part of the same wetware world.

Before getting back on the road in the morning, Alan took a walk, admiring the clumps of prickly pear cactus, the lobbed with buds along their rims, and with yellow and red flowers sprouting amid the thorns. He liked how the cacti were so perfectly placed among the grasses and the dry red rocks. Nature’s wise and lovely designs, at the fertile border between order and chaos. Little lizards lifted up their striped tails to run away.

[Detail of “Turing and the Skugs,” see my paintings page for more info.]

Alan came across a hillside cemetery with a few cracked stones amid long grass and thick-trunked old cypresses, the trees not immensely tall. In the wind-blown grass, Alan accidentally stepped on something alive. It was a rather large lizard who’d been resting there, sluggish in the early sun. The weight of Alan’s foot had broken off most of the lizard’s tail, and it was frantically twitching on the ground. The lizard himself remained motionless. Alan had the notion the was wounded lizard was keeping himself under strict control, as opposed to his cut-off tail which had no control at all, desperately writhing.

With the federal police after him and his fellow skuggers, he needed to be like the lizard and not like the tail.