Stephen Wolfram

And so I've tried to track down, you know, how did people come to figure out this or that thing?

And there's always a long kind of sort of preparatory, you know, there's a need to be prepared in a mindset in which it's possible to see something.

I mean, in the case of Rule 30, I was around June 1st, 1984, was kind of a silly story in some ways.

I finally had a high resolution laser printer.

So I thought, I'm going to generate a bunch of pictures of the cellular automata.

And I generate this one, and I put it on some plane flight to Europe, and I have this with me.

And it's like, you know, I really should try to understand this.

I really don't understand what's going on.

And that was kind of the slowly trying to see what was happening.

It was not

It was depressingly unsudden, so to speak, in the sense that a lot of these ideas, like principle of computational equivalence, for example, you know, I thought, well, that's a possible thing.

I didn't know if it's correct.

Still don't know for sure that it's correct.

But it's sort of a gradual thing that these things gradually kind of become seem more important than one thought.

I mean, I think the whole idea of studying the computational universe of simple programs,

probably a decade, decade and a half to kind of internalize that that was really an important idea.

And I think if it turns out we find the whole universe lurking out there in the computational universe, that's a good brownie point or something for the whole idea.

But I think that the thing that's strange in this whole question about finding this different raw material for making models of things is

What's been interesting in the arc of history is for 300 years, it's kind of like the mathematical equations approach.

It was the winner.