Stephen Wolfram

But then there's this whole layer of kind of formalization that got developed.

which is the whole story of intellectual history and the whole depth of learning, that formalization turned into things like logic, mathematics, science, and so on.

And that's the kind of thing that allows one to build these towers of things you work out.

It's not just, I can immediately figure this out.

It's no, I can use this kind of formalism to go step by step and work out something which was not immediately obvious to me.

And that's kind of the story of what we're trying to do computationally is to be able to build those kind of tall towers of what implies what implies what and so on.

And as opposed to kind of the, yes, I can immediately figure it out.

It's just like what I saw somewhere else in something that I heard or remembered or something like this.

So the question is sort of how do you think about computation?

And there's a couple of points here.

One is what computation intrinsically is like,

And the other is what aspects of computation we humans with our minds and with the kinds of things we've learned can sort of relate to in that computational universe.

So if we start on the kind of what can computation be like, it's something I've spent some big chunk of my life studying, is imagine that you're, you know, we usually write programs where we kind of know what we want the program to do.

And we carefully write many lines of code and we hope that the program does what we intended it to do.

But the thing I've been interested in is if you just look at the kind of natural science of programs.

So you just say, I'm going to make this program.

It's a really tiny program.

Maybe I even pick the pieces of the program at random, but it's really tiny.

And by really tiny, I mean, you know, less than a line of code type thing.

You say, what does this program do?