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Annotated captions of Ray Kurzweil: A university for the coming singularity in English

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Information technology grows in an exponential manner.

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It's not linear. And our intuition is linear.

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When we walked through the savanna a thousand years ago

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we made linear predictions where that animal would be,

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and that worked fine. It's hardwired in our brains.

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But the pace of exponential growth

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is really what describes information technologies.

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And it's not just computation.

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There is a big difference between linear and exponential growth.

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If I take 30 steps linearly -- one, two, three, four, five --

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I get to 30.

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If I take 30 steps exponentially -- two, four, eight, 16 --

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I get to a billion.

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It makes a huge difference.

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And that really describes information technology.

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When I was a student at MIT,

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we all shared one computer that took up a whole building.

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The computer in your cellphone today is a million times cheaper,

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a million times smaller,

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a thousand times more powerful.

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That's a billion-fold increase in capability per dollar

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that we've actually experienced since I was a student.

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And we're going to do it again in the next 25 years.

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Information technology progresses

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through a series of S-curves

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where each one is a different paradigm.

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So people say, "What's going to happen when Moore's Law comes to an end?"

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Which will happen around 2020.

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We'll then go to the next paradigm.

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And Moore's Law was not the first paradigm

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to bring exponential growth to computing.

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The exponential growth of computing started

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decades before Gordon Moore was even born.

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And it doesn't just apply to computation.

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It's really any technology where we can measure

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the underlying information properties.

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Here we have 49 famous computers. I put them in a logarithmic graph.

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The logarithmic scale hides the scale of the increase,

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because this represents trillions-fold increase

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since the 1890 census.

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In 1950s they were shrinking vacuum tubes,

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making them smaller and smaller. They finally hit a wall;

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they couldn't shrink the vacuum tube any more and keep the vacuum.

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And that was the end of the shrinking of vacuum tubes,

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but it was not the end of the exponential growth of computing.

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We went to the fourth paradigm, transistors,

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and finally integrated circuits.

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When that comes to an end we'll go to the sixth paradigm;

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three-dimensional self-organizing molecular circuits.

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But what's even more amazing, really, than this

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fantastic scale of progress,

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is that -- look at how predictable this is.

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I mean this went through thick and thin,

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through war and peace, through boom times and recessions.

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The Great Depression made not a dent in this exponential progression.

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We'll see the same thing in the economic recession we're having now.

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At least the exponential growth of information technology capability

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will continue unabated.

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And I just updated these graphs.

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Because I had them through 2002 in my book, "The Singularity is Near."

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So we updated them,

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so I could present it here, to 2007.

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And I was asked, "Well aren't you nervous?

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Maybe it kind of didn't stay on this exponential progression."

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I was a little nervous

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because maybe the data wouldn't be right,

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but I've done this now for 30 years,

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and it has stayed on this exponential progression.

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Look at this graph here.You could buy one transistor for a dollar in 1968.

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You can buy half a billion today,

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and they are actually better, because they are faster.

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But look at how predictable this is.

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And I'd say this knowledge is over-fitting to past data.

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I've been making these forward-looking predictions for about 30 years.

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And the cost of a transistor cycle,

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which is a measure of the price performance of electronics,

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comes down about every year.

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That's a 50 percent deflation rate.

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And it's also true of other examples,

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like DNA data or brain data.

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But we more than make up for that.

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We actually ship more than twice as much

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of every form of information technology.

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We've had 18 percent growth in constant dollars

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in every form of information technology for the last half-century,

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despite the fact that you can get twice as much of it each year.

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This is a completely different example.

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This is not Moore's Law.

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The amount of DNA data

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we've sequenced has doubled every year.

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The cost has come down by half every year.

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And this has been a smooth progression

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since the beginning of the genome project.

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And halfway through the project, skeptics said,

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"Well, this is not working out. You're halfway through the genome project

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and you've finished one percent of the project."

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But that was really right on schedule.

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Because if you double one percent seven more times,

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which is exactly what happened,

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you get 100 percent. And the project was finished on time.

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Communication technologies:

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50 different ways to measure this,

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the number of bits being moved around, the size of the Internet.

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But this has progressed at an exponential pace.

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This is deeply democratizing.

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I wrote, over 20 years ago in "The Age of Intelligent Machines,"

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when the Soviet Union was going strong, that it would be swept away

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by this growth of decentralized communication.

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And we will have plenty of computation as we go through the 21st century

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to do things like simulate regions of the human brain.

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But where will we get the software?

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Some critics say, "Oh, well software is stuck in the mud."

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But we are learning more and more about the human brain.

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Spatial resolution of brain scanning is doubling every year.

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The amount of data we're getting about the brain is doubling every year.

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And we're showing that we can actually turn this data

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into working models and simulations of brain regions.

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There is about 20 regions of the brain that have been modeled,

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simulated and tested:

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the auditory cortex, regions of the visual cortex;

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cerebellum, where we do our skill formation;

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slices of the cerebral cortex, where we do our rational thinking.

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And all of this has fueled

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an increase, very smooth and predictable, of productivity.

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We've gone from 30 dollars to 130 dollars

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in constant dollars in the value of an average hour of human labor,

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fueled by this information technology.

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And we're all concerned about energy and the environment.

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Well this is a logarithmic graph.

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This represents a smooth doubling,

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every two years, of the amount of solar energy we're creating,

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particularly as we're now applying nanotechnology,

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a form of information technology, to solar panels.

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And we're only eight doublings away

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from it meeting 100 percent of our energy needs.

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And there is 10 thousand times more sunlight than we need.

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We ultimately will merge with this technology. It's already very close to us.

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When I was a student it was across campus, now it's in our pockets.

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What used to take up a building now fits in our pockets.

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What now fits in our pockets would fit in a blood cell in 25 years.

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And we will begin to actually deeply influence

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our health and our intelligence,

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as we get closer and closer to this technology.

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Based on that we are announcing, here at TED,

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in true TED tradition, Singularity University.

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It's a new university

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that's founded by Peter Diamandis, who is here in the audience,

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and myself.

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It's backed by NASA and Google,

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and other leaders in the high-tech and science community.

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And our goal was to assemble the leaders,

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both teachers and students,

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in these exponentially growing information technologies,

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and their application.

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But Larry Page made an impassioned speech

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at our organizing meeting,

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saying we should devote this study

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to actually addressing some of the major challenges facing humanity.

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And if we did that, then Google would back this.

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And so that's what we've done.

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The last third of the nine-week intensive summer session

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will be devoted to a group project to address

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some major challenge of humanity.

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Like for example, applying the Internet,

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which is now ubiquitous, in the rural areas of China or in Africa,

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to bringing health information

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to developing areas of the world.

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And these projects will continue past these sessions,

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using collaborative interactive communication.

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All the intellectual property that is created and taught

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will be online and available,

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and developed online in a collaborative fashion.

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Here is our founding meeting.

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But this is being announced today.

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It will be permanently headquartered in Silicon Valley,

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at the NASA Ames research center.

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There are different programs for graduate students,

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for executives at different companies.

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The first six tracks here -- artificial intelligence,

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advanced computing technologies, biotechnology, nanotechnology --

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are the different core areas of information technology.

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Then we are going to apply them to the other areas,

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like energy, ecology,

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policy law and ethics, entrepreneurship,

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so that people can bring these new technologies to the world.

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So we're very appreciative of the support we've gotten

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from both the intellectual leaders, the high-tech leaders,

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particularly Google and NASA.

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This is an exciting new venture.

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And we invite you to participate. Thank you very much.

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(Applause)