The Mathematics of Clouds

“I very much enjoy looking at the wind moving trees around, and I love looking at the ocean, and clouds. I always think if there were only one place in the world where you could see clouds everybody would be flocking there, clouds are so fascinating and we just take them for granted, we don’t even look at them.

That’s one thing in an environment like a Mall: it’s hard to find any examples of what I call ‘gnarl’, natural gnarl, where you see a leaf waving in the wind, or a fire flame, or some flowing water. We often box ourselves up into these rooms.

When you see something like the leaves on a tree, that’s a good example, there may be a simple equation underlying it, like the laws of fluid flow. We’ve got a certain amount of air and a certain number of leaf positions, the leaves are complex compound pendulums, and they begin rocking in these unpredictable ways.

The distinction that’s new, and that we didn’t used to make, is that something can be deterministic but not predictable. We tend to think they are synonyms but they’re not. Something can be obeying some law of nature but it’s not predictable because what it’s doing is so complicated that the time it would take you to calculate what it was going to do would take longer than the thing actually doing it. So you could compute it but you can’t compute the world any faster than it is happening.”

Rudy Rucker in conversation with Rick Kleffel, January 2007.

When Alan Turing did his pioneering studies in the 1930s, defining the bedrock for the field of Computing, there was no such machine as a “computer”. When Turing talked of computers he was envisioning human beings with pen and paper carrying out repetitive sequential tasks, not machines. The lump of metal and matt plastic we now call a computer didn’t really find it’s way into our lives until fifty years later, long after Turing’s suicide in 1954.

In the early nineties I started a Computing degree at Exeter University, which I endured for about a year and a half before, bored senseless, I dropped out. I then went off to be arty for a few years to restore some kind of left-right hemisphere balance to my brain. I was so repulsed by my experience of early 90s ideas of Computing that I made efforts to stay as far away from computers as I could for the next five years.

It was only towards the end of the last decade, after the World Wide Web started to take off, and everyone suddenly discovered what they’d been doing recently with video cameras, photography and hypertext was now being called “New Media”, that I was drawn back in, and I made friends with the machines once more. It was also around this time that I started using a Mac, rather than a PC, which may also explain my shift in attitude.

But I sometimes think that my original attitude towards the study of Computing may not have been so negative if it was made apparent to me at university that Computing is not something you need a Computer to study. This took me a long time to realise, because I’d never really encountered this idea until recently. Computation is everywhere.

Computing is what our DNA does at it unravels. It is what a stream does as it finds it’s way downhill towards the ocean. It is what the planets do as they move in their orbits. It is what our bodies do as they maintain the balance needed to keep us upright. Computing is what I am doing now as I process these ideas, and output them as text. The only place computers really come into it is in attempting to simulate these computations, or allowing us to create simple computations of our own. And computers are rather limited in this capability. This is why I can say without contradiction that I find Computers quite boring, but Computation is fascinating. If you don’t believe me turn off your primitive adding machine and take a look around you.

Even the most elementary of phenomenon in the natural world – the fluttering of a leaf, the spray of the ocean, the weather – are way beyond what can be computed by the technology we have. And it is theorised, via the work of Turing, Godel, Hofstadter and others, that we could never develop technology capable of simulating such a level of computation – it is simply conceptually impossible. This is why, as Dr Rucker’s quote above says, an entirely deterministic idea of Universal Automatism doesn’t mean we have to live in a world that is in any way predictable.

If you intended to develop an enthusiasm for literature, you’d study the classics; Shakespeare, Milton, Blake; examples of writing done well. You wouldn’t examine till receipts. Just as I’m sure no one was drawn to architecture by seeing a particularly well-constructed shed. Like Determinism and Predictability, Computing and Computers are not synonymous, and the study of Computing is not something to be done in front of humming box of electronics. Computing is better studied watching the wind in the trees, sat by a stream, or looking at the clouds.



posted July 13th, 2007



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