So, this brings us to the course goals. The course is designed to help you to

So this is a NAND gate.

And from that you have new possibilities for computing.

It's very data intensive experimental science.

I'm a professor at the University of Illinois, Urbana, Champagne.

So, now we can compute that the output arranges material as well as information.

Free On Line Dictionary of Computing

So this quote wouldn't show up for the keyword David.

But today we have lots of different applications.

The whole industry is moving into heterogeneous computing from mobile to super computing.

We're writing programs to solve problems, but they're dealing with abstract representations of those problems.

It's not quite what he said, but close enough approximation. And when, I don't quite have the graph here.

What we're trying to do is build a virtual world.

Everything is transformed into machine instructions to manipulate these bits.

There's new programmability in these parts.

And computing looks very different.

But we still look at technology as top down mega projects.

The kde team welcomes you to user friendly UNIX computing.

Go through a whole series of things to change my research.

But there is a lot of computing in nature.

The KDE team welcomes you to user friendly UNIX computing.

We'll then go to the next paradigm.

like an immune system, and we're learning from gene regulation and biological development.

So Brielin, what does quantum physics have to do with computing?

Anybody in the world can use them.

I'm here with Brielin Brown, who works on quantum computing.

Illinois Coursera course of Heterogeneous Parallel Programming.

And that's when we got the Internet.

log plot is an exponential increase in performance.

So I have quite a few friends who do search engines and I asked one of them, Sergey Brin, who's co founder of Google

Geometry. We haven't used too much directly in this class.

So just to give you a bit of context, as June said, I'm an artist, a technologist and an educator.

We didn't get to this too much in this class, but this question about universality, questions about what can be computed and how fast it can be computed are really fundamental questions about science.

We'll start by summarizing the course, and I want to highlight the three main themes that I think are most important in computing.

And now of days we, of course, have transistors.

This is a student who made a machine that makes machines, and he made it by making Lego bricks that do the computing.

It's also related to universality.

If you don't believe me, I would encourage you to read this book by Douglas Hofstadter called Godel, Escher, Bach.

What we're going to do next is learn about the present of computing. We're going to visit SLAC National Accelerator Laboratory, and see how they're using computing to advance science today.

But it goes a step further, and it tries to have actual computation.

And we're learning from neural nets, genetic algorithms, evolutionary computing.

You cannot assume your computers don't die in the middle of calculations.

The hardest thing at this point is the social engineering and the organizational engineering, but it's here today.

Unit 7 will get you ready for the final exam and will give you some interesting examples of using Computing in Context.

Music, which is about number in time.