Ray Kurzweil: A university for the coming singularity

87,328 views ・ 2009-06-02

TED


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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)
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