Stephen Wolfram: Computation & The Future of Mankind 1 @Singularity Summit 2011

Stephen Wolfram presented a lecture on complexity, mathematics, and computer models.  It was in our opinion, probably the most interesting lecture of that day.

We will transcribe Stephen Wolfram's lecture titled, Computation and the Future of Mankind, which was delivered at the Singularity Summit 2011 in New York City.  Any annotations we make will be in orange color and non-italics.  His words will be in white italics.

Lecture
What I wanted to do today is as far as I'm concerned is have fun and talk about the future.  Which is something kind of recreational for me, because what I normally do is work sort of in the trenches, trying to actually build the future, one brick at a time, or, at least on big project at a time.

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I've been doing that for a little more than twenty years I guess.  I've built a fairly tall tower, from which it is possible to do a series of interesting things.  Things are moving quite fast right now.  An example from yesterday is an iPhone 4S which has a button to pull up Siri, talk to it and you can ask all kinds of questions.  Quite often it will compute answers kind of, Star Trek computer style using our Wolfram Alpha knowledge engine.
There's a lot to say about Wolfram Alpha and how it relates to artificial intelligence, about the whole idea of computational knowledge, where it means to the future and so on.  Let me start off by more of a conceptional level.  I wanted to sort of talk about world views.

When I first saw this, I didn't actually believe it, I thought that there was some regularity some way to decode what I was seeing. In our usual intuition, we have the idea that to make something complex, we have to go to lots of effort. It can't just take some tiny little rule like that. But I suppose this was my own personal little Galileo moment, for me, of a new world view, with new and different intuition, formed by what I'd seen out there in the new computational universe. Stephen Wolfram


A lot of the ways that we tend to think about the world and about science and technology is sort of very Newtonian, very Galilean.  I mean it's a great tradition that's done amazing things over the past three hundred years, also rooted in physics with math as an aspiration for how to describe things.  In a sense it all got started with one surprising discovery that got made in 1608, when Galileo turned his telescope towards the sky and saw for the first time the moons of Jupiter, and began to realize that there could be kind of this universal physics that applies everywhere, from which we could ultimately build this whole edifice that is modern exact science and technology.  I myself happened to start out early in life as a physicist and are much steeped in this physics/math worldview.

But as I studied different kinds of things, particularly ones where there was sort of an obvious complexity in the behavior of a system, I kept on finding cases where I could not make too much progress with that.  I got to wondering whether there was something fundamental that had to change.  One of the big issues was this: when we look at some system in nature, how do we think about the mechanism of that system?  So the big innovation of Galileo and Newton and friends was to have the idea of using mathematics to describe this mechanism.  So that we get all these equations and math and calculus with systems we study in science or build in technology.

Here's the question, is that the only mechanism that nature can be using?  Well what I realized, its that it's certainly possible that there are other mechanisms, rules that are precise, but that aren't captured by our standard mathematics.  The nice thing is that in our times, we have a way to think about those more general rules.  They're like programs, well when we think of programs, we usually think of these big things that we build for very particular purposes.  But what about little tiny programs, maybe just one line of code long or something like that.  You might have thought, as I certainly did, that programs like that would always be trivial, they would never do anything interesting.  But one day, nearly thirty years ago now, I decided to actually test that idea and put my analog telescope, the computer, and pointed it not at the sky, but at the abstract computational universe of possible programs.  This is one of the things that I saw.

Each one of these pictures represents a program.  You can see there's all kinds of different things that happen, most of them quite trivial.  But if you look carefully, you'll see something quite remarkable.  The thirtieth one of these is the thing I call rule thirty.  Here's what it does:

Rule 30
click to enlarge

You start it from one black cell at the top, using the little rule at the bottom, looks like a trivial rule, but here, the result of running that rule is you get all this "stuff," complex, in some ways random, no sign that it came from that little simple rule at the bottom.  When I first saw this, I didn't actually believe it, I thought that there was some regularity some way to decode what I was seeing.  In our usual intuition, we have the idea that to make something complex, we have to go to lots of effort.  It can't just take some tiny little rule like that.  But I suppose this was my own personal little Galileo moment, for me, of a new world view, with new and different intuition, formed by what I'd seen out there in the new computational universe.

Well, over the years since I've discovered rule thirty, I've been understanding more and more about the world view that it implies.  I feel very slow because there are many layers to understand.  But it's been tremendously exciting and the more I understand the more important I think it is for understanding the world and building the future.  There are some pretty interesting spinoffs.  I'll explain, like Wolfram Alpha for example. [We include a short video which explains Wolfram Alpha's computational search engines.  If you cannot see the embedded video, here is the link: http://youtu.be/L7Nwav5TcWo.]

So, we have this new kind of science that's based on exploring the computational universe of possible programs, what does it mean?  There's a basic issue in science that's been around forever, wit this question: how is that nature manages to make all the complicated stuff that it does?  It's sort of embarrassing.  If you show someone two objects, one of them is an artifact, one of them is a natural system, it's a good heuristic, that the one that's looks simpler, is the artifact.  With all that we've achieved in our civilization, nature still has some secret that let's it sort of effortlessly create stuff that's more complex than we can build.

We will continue with the rest of the lecture in part 2 of this series.