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So I have a feature on my website where every week
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people submit hypothetical questions
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for me to answer,
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and I try to answer them using math, science,
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and comics.
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So for example, one person asked,
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what would happen if you tried to hit a baseball
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pitched at 90% of the speed of light?
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So I did some calculations.
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Now, normally, when an object flies through the air,
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the air will flow around the object,
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but in this case, the ball would be going so fast
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that the air molecules wouldn't have time
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to move out the way.
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The ball would smash right into and through them,
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and the collisions with these air molecules
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would knock away the nitrogen,
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carbon, and hydrogen from the ball,
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fragmenting it off into tiny particles,
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and also triggering waves of thermonuclear fusion
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in the air around it.
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This would result in a flood of x-rays
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that would spread out in a bubble
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along with exotic particles,
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plasma inside, centered on the pitcher's mound,
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and that would move away from the pitcher's mound
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slightly faster than the ball.
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Now at this point, about 30 nanoseconds in,
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the home plate is far enough away
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that light hasn't had time to reach it,
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which means the batter
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still sees the pitcher about to throw
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and has no idea that anything is wrong.
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(Laughter)
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Now, after 70 nanoseconds,
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the ball will reach home plate,
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or at least the cloud of expanding plasma
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that used to be the ball,
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and it will engulf the bat and the batter
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and the plate and the catcher and the umpire
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and start disintegrating them all
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as it also starts to carry them backward
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through the backstop, which
also starts to disintegrate.
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So if you were watching this whole thing
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from a hill,
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you know, ideally, far away,
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what you'd see is a bright flash of light
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that would fade over a few seconds,
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followed by a blast wave spreading out,
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shredding trees and houses
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as it moves away from the stadium,
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and then eventually a mushroom cloud
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rising up over the ruined city. (Laughter)
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So the Major League Baseball rules
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are a little bit hazy,
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but — (Laughter) — under rule 6.02 and 5.09,
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I think that in this situation,
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the batter would be considered hit by pitch
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and would be eligible to take first base,
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if it still existed.
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So this is the kind of question I answer,
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and I get people writing in with
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a lot of other strange questions.
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I've had someone write and say,
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scientifically speaking, what is the best
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and fastest way to hide a body?
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Can you do this one soon?
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And I had someone write in,
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I've had people write in about, you know,
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can you prove whether or not you can find love again
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after your heart's broken?
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And I've had people send in
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what are clearly homework questions
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they're trying to get me to do for them.
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But one week, a couple months ago,
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I got a question that was actually about Google.
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If all digital data in the world
were stored on punch cards,
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how big would Google's data warehouse be?
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Now, Google's pretty secretive
about their operations,
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so no one really knows how much data Google has,
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and in fact, no one really knows
how many data centers Google has,
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except, you know, people at Google itself.
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And I've tried, met them a few times,
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tried asking them, and they
aren't revealing anything.
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So I decided to try to figure this out myself.
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There are a few things that I looked at here.
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I started with money.
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Google has to reveal how much they spend,
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in general, and that lets you put some caps
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on how many data centers could they be building,
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because a big data center costs
a certain amount of money.
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And you can also, then, put a cap on
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how much of the world hard
drive market are they taking up,
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which turns out, it's pretty sizable.
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I read a calculation at one point,
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Google has a drive failure
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about every minute or two,
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and they just throw out the hard drive
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and swap in a new one.
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So they go through a huge number of them.
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And so by looking at money,
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you can get an idea of how
many of these centers they have.
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You can also look at power.
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You can look at how much electricity they need,
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because you need a certain amount
of money to run the servers,
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and Google is more efficient than most,
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but they still have some basic requirements,
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and that lets you put a limit
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on the number of servers that they have.
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You can also look at square footage and see
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of the data centers that you know,
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how big are they?
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How much room is that?
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How many server racks could you fit in there?
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And some for data centers,
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you might get two of these pieces of information.
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You know how much they spent,
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and they also, say, because they had the contract
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with the local government
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to get the power provided,
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you might know what they made a deal to buy,
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so you know how much power it takes.
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Then you can look at the ratios of those numbers,
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and figure out for a data center
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where you don't have that information,
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you can figure out,
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but maybe you only have one of those,
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you know the square footage,
then you could figure out
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well, maybe the power is proportional.
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And you can do this same thing
with a lot of different quantities,
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you know, with guesses about
the total amount of storage,
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the number of servers, the
number of drives per server,
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and in each case using what you know
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to come up with a model that narrows down
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your guesses for the things that you don't know.
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It's sort of circling around the
number you're trying to get.
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And this is a lot of fun.
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The math is not all that advanced,
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and really it's like nothing more than
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solving a sudoku puzzle.
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So what I did, I went through all of this information,
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spent a day or two researching,
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and there are some things I didn't look at.
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You could always look at the Google
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recruitment messages that they post.
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That gives you an idea of where they have people.
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Sometimes, when people visit a data center,
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they'll take a cell-cam photo and post it,
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and they aren't supposed to,
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but you can learn things about
their hardware that way.
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And in fact, you can just
look at pizza delivery drivers.
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Turns out, they know where all
the Google data centers are,
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at least the ones that have people in them.
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But I came up with my estimate,
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which I felt pretty good about,
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that was about 10 exabytes of data
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across all of Google's operations,
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and then another maybe five exabytes or so
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of offline storage in, like, tape drives,
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which it turns out Google is
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about the world's largest consumer of.
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So I came up with this estimate, and this is
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a staggering amount of data.
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It's quite a bit more than any other organization
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in the world has, as far as we know.
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There's a couple of other contenders,
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especially everyone always thinks of the NSA.
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But using some of these same methods,
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we can look at the NSA's data centers,
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and figure out, you know, we
don't know what's going on there,
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but it's pretty clear their operation
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is not the size of Google's.
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Adding all of this up, I came up with
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the other thing that we can answer, which is,
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how many punch cards would this take?
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And so a punch card can hold
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about 80 characters,
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and you can fit about 2,000 or so cards into a box,
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and you put them in, say,
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my home region of New England,
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it would cover the entire region
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up to a depth of a little less than five kilometers,
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which is about three times deeper
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than the glaciers during the last ice age
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about 20,000 years ago.
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So this is impractical, but I think
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that's about the best answer I could come up with.
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And I posted it on my website. I wrote it up.
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And I didn't expect to get an answer from Google,
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because of course they've been so secretive,
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they didn't answer of my questions,
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and so I just put it up and said,
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well, I guess we'll never know.
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But then a little while later
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I got a message, a couple weeks later, from Google,
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saying hey, someone here has an envelope for you.
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So I go and get it, open it up,
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and it's punch cards. (Laughter)
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Google-branded punch cards.
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And on these punch cards,
there are a bunch of holes,
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and I said, thank you, thank you,
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and I say, so what's on here?
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So I get some software and start reading it,
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and scan them, and it turns out
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it's a puzzle.
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There's a bunch of code,
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and I get some friends to help,
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and we crack the code, and then
inside that is another code,
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and then there are some equations,
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and then we solve those equations,
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and then finally out pops a message from Google
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which is their official answer to my article,
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and it said, "No comment."
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(Laughter) (Applause)
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And I love calculating these kinds of things,
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and it's not that I love doing the math.
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I do a lot of math,
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but I don't really like math for its own sake.
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What I love is that it lets you take
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some things that you know,
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and just by doing some symbols
around on a piece of paper,
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find out something that you didn't know
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that's very surprising.
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And I have a lot of stupid questions,
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and I love that math gives the power
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to answer them sometimes.
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And sometimes not.
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This is a question I got from a reader,
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an anonymous reader,
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and the subject line just said, "Urgent,"
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and this was the entire email.
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If people had wheels and could fly,
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how would we differentiate them from airplanes?
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Urgent. (Laughter)
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And I think there are some questions
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that math just cannot answer.
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Thank you.
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(Applause)