Stephen Wolfram Injecting Computation Everywhere–A SXSW Update

Матеріал взято з blog.wolfram.com
Two weeks ago I spoke at SXSW Interactive in Austin, TX. Here’s a slightly edited transcript (it’s the “speaker’s cut”, including some demos I had to abandon during the talk):
Well, I’ve got a lot planned for this hour.

Basically, I want to tell you a story that’s been unfolding for me for about the last 40 years, and that’s just coming to fruition in a really exciting way. And by just coming to fruition, I mean pretty much today. Because I’m planning to show you today a whole lot of technology that’s the result of that 40-year story—that I’ve never shown before, and that I think is going to be pretty important.
I always like to do live demos. But today I’m going to be pretty extreme. Showing you a lot of stuff that’s very very fresh. And I hope at least a decent fraction of it is going to work.
OK, here’s the big theme: taking computation seriously. Really understanding the idea of computation. And then building technology that lets one inject it everywhere—and then seeing what that means.
I’ve pretty much been chasing this idea for 40 years. I’ve been kind of alternating between science and technology—and making these bigger and bigger building blocks. Kind of making this taller and taller stack. And every few years I’ve been able to see a bit farther. And I think making some interesting things. But in the last couple of years, something really exciting has happened. Some kind of grand unification—which is leading to a kind of Cambrian explosion of technology. Which is what I’m going to be showing you pieces of for the first time here today.
But just for context, let me tell you a bit of the backstory. Forty years ago, I was a 14-year-old kid who’d just started using a computer—which was then about the size of a desk. I was using it not so much for its own sake, but instead to try to figure out things about physics, which is what I was really interested in. 
And I actually figured out a few things—which even still get used today. But in retrospect, I think the most important thing I figured out was kind of a meta thing. That the better the tools one uses, the further one can get. Like I was never good at doing math by hand, which in those days was a problem if you wanted to be a physicist. But I realized one could do math by computer. And I started building tools for that. And pretty soon me with my tools were better than almost anyone at doing math for physics.
And back in 1981—somewhat shockingly in those days for a 21-year-old professor type—I turned that into my first product and my first company. And one important thing is that it made me realize that products can really drive intellectual thinking. 
I needed to figure out how to make a language for doing math by computer, and I ended up figuring out these fundamental things about computation to be able to do that. Well, after that I dived back into basic science again, using my computer tools.
And I ended up deciding that while math was fine, the whole idea of it really needed to be generalized. And I started looking at the whole universe of possible formal systems—in effect the whole computational universe of possible programs. I started doing little experiments. Kind of pointing my computational telescope into this computational universe, and seeing what was out there. And it was pretty amazing. Like here are a few simple programs.

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