Stephen Wolfram

That rule, I'm not sure I said it exactly right, but a rule very much like what I just said has the feature that if you started off from just one black cell at the top, it makes this extremely complicated pattern.

So some rules...

you get a very simple pattern.

Some rules, you have the rule is simple, you start them off from a sort of simple seed, you just get this very simple pattern.

But other rules, and this was the big surprise when I started actually just doing the simple computer experiments to find out what happens, is that they produce very complicated patterns of behavior.

So for example, this rule 30 rule has the feature you started off from just one black cell at the top,

makes this very random pattern.

If you look at the center column of cells, you get a series of values.

It goes black, white, black, black, whatever it is.

That sequence seems, for all practical purposes, random.

It's kind of like in math, you know, you compute the digits of pi, 3.1415926 whatever.

Those digits, once computed, I mean, the scheme for computing pi, you know, it's the ratio of the circumference to the diameter of a circle, very well defined.

But yet, once you've generated those digits, they seem, for all practical purposes, completely random.

And so it is with rule 30, that even though the rule is very simple, much simpler, much more sort of computationally obvious than the rule for generating digits of pi, even with a rule that simple, you're still generating immensely complicated behavior.

I find it that way.

Yeah.

I mean, look, it's been, it was a very intuition breaking experience.

thing to discover.

I mean, it's kind of like, you know, you point the computational telescope out there and suddenly you see, I don't know, you know, in the past, it's kind of like, you know, moons of Jupiter or something, but suddenly you see something that's kind of very unexpected.

And rule 30 was very unexpected for me.