Stephen Wolfram

Sort of the opposite way around from what you do in natural science.

But I'd had the experience of doing that, and so I was kind of like, okay, what happens if you sort of make an artificial physics?

What happens if you just make up the rules

by which systems operate.

And then I was thinking, you know, for all these different systems, whether it was galaxies or brains or whatever, what's the absolutely minimal model that kind of captures the things that are important about those systems?

Yes.

And so that's what ended up with the cellular automata, where you just have a line of black and white cells.

You just have a rule that says, you know, given a cell and its neighbors, what will the color of the cell be on the next step?

And you just run it in a series of steps.

And the sort of the ironic thing is that cellular automata are great models for many kinds of things.

But galaxies and brains are two examples where they do very, very badly.

They're really irrelevant to those two categories.

Yes.

Okay, so when I first started selling cellular automata, my first papers about them were, you know, the first sentence was always about the second law of thermodynamics.

It was always about how does order manage to be produced even though there's a second law of thermodynamics which tries to pull things back into disorder.

And my early understanding of that had to do with these are intrinsically irreversible processes in cellular automata that can form orderly structures even from random initial conditions.

But then what I realized, this was... Well, actually, it's...

It's one of these things where it was a discovery that I should have made earlier, but didn't.

So, you know, I had been studying cellular automata.

What I did was the sort of most obvious computer experiment.