Juan Enriquez: The life-code that will reshape the future

87,621 views ใƒป 2007-05-16

TED


ืื ื ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ืœืžื˜ื” ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ.

ืžืชืจื’ื: Yubal Masalker ืžื‘ืงืจ: Shahar Kaiser
00:26
I'm supposed to scare you, because it's about fear, right?
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ืื ื™ ืืžื•ืจ ืœื”ืคื—ื™ื“ ืืชื›ื, ื›ื™ ื”ืจื™ ืžื“ื•ื‘ืจ ื‘ืคื—ื“, ืœื?
00:30
And you should be really afraid,
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ื•ืืชื ื‘ืืžืช ืฆืจื™ื›ื™ื ืœืคื—ื“,
00:32
but not for the reasons why you think you should be.
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ืื‘ืœ ืœื ื‘ื’ืœืœ ื”ืกื™ื‘ื•ืช ืฉืืชื ื—ื•ืฉื‘ื™ื.
00:35
You should be really afraid that --
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ืืชื ื‘ืืžืช ืฆืจื™ื›ื™ื ืœื—ืฉื•ืฉ ืฉ --
00:37
if we stick up the first slide on this thing -- there we go -- that you're missing out.
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ืื ืจืง ืืฆืœื™ื— ืœื”ืฉื—ื™ืœ ืืช ื”ืฉืงื•ืคื™ืช ื”ืจืืฉื•ื ื” -- ื”ื ื” -- ืฉืืชื ืžืคืกืคืกื™ื.
00:43
Because if you spend this week thinking about Iraq and
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ืžื›ื™ื•ื•ืŸ ืฉืื ืืชื ืžืขื‘ื™ืจื™ื ืฉื‘ื•ืข ื–ื” ื‘ืžื—ืฉื‘ื•ืช ืขืœ ืขื™ืจืง
00:47
thinking about Bush and thinking about the stock market,
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ื•ืขืœ ื‘ื•ืฉ ื•ืขืœ ื”ื‘ื•ืจืกื”, ืืชื ืชืคืกืคืกื• ืื—ืช ืžื”ื”ืจืคืชืงืื•ืช ื”ื’ื“ื•ืœื•ืช ื‘ื™ื•ืชืจ
00:51
you're going to miss one of the greatest adventures that we've ever been on.
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ืฉื”ื™ื™ื ื• ืขื“ื™ื ืœื” ืื™-ืคืขื.
00:54
And this is what this adventure's really about.
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ื•ื”ื”ืจืคืชืงืื” ื”ื™ื ื‘ื ื•ืฉื ื–ื”.
00:56
This is crystallized DNA.
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ื–ื” DNA ืฉื”ืชื’ื‘ืฉ.
01:00
Every life form on this planet -- every insect, every bacteria, every plant,
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ื›ืœ ืฆื•ืจืช ื—ื™ื™ื ืขืœ ื›ื“ื•ืจ-ื”ืืจืฅ -- ื›ืœ ื—ืจืง, ื›ืœ ื—ื™ื™ื“ืง, ื›ืœ ืฆืžื—,
01:03
every animal, every human, every politician -- (Laughter)
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ื›ืœ ื‘ืขืœ-ื—ื™ื™ื, ื›ืœ ืื“ื, ื›ืœ ืคื•ืœื˜ื™ืงืื™ -- (ืฆื—ื•ืง)
01:08
is coded in that stuff.
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ืžื•ืฆืคืŸ ื‘ื—ื•ืžืจ ื–ื”.
01:10
And if you want to take a single crystal of DNA, it looks like that.
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ื•ืื ืชืงื—ื• ื’ื‘ื™ืฉ ื™ื—ื™ื“ ืฉืœ DNA, ื”ื•ื ื™ื™ืจืื” ื›ืš.
01:14
And we're just beginning to understand this stuff.
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ื•ืื ื—ื ื• ืจืง ืžืชื—ื™ืœื™ื ืœื”ื‘ื™ืŸ ืืช ื”ื ื•ืฉื.
01:17
And this is the single most exciting adventure that we have ever been on.
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ื•ื–ื•ื”ื™ ื”ื”ืจืคืชืงืื” ื”ืžืจื’ืฉืช ื‘ื™ื•ืชืจ ืฉื—ื•ื•ื™ื ื• ืื™-ืคืขื.
01:21
It's the single greatest mapping project we've ever been on.
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ื–ื”ื• ืžื™ื–ื ื”ืžื™ืคื•ื™ ื”ื’ื“ื•ืœ ื‘ื™ื•ืชืจ ืฉื—ื•ื•ื™ื ื• ืื™-ืคืขื.
01:24
If you think that the mapping of America's made a difference,
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ืื ืืชื ืกื‘ื•ืจื™ื ืฉืžื™ืคื•ื™ ืืžืจื™ืงื” ืขืฉื” ืืช ื”ื”ื‘ื“ืœ,
01:26
or landing on the moon, or this other stuff,
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ืื• ื”ื ื—ื™ืชื” ืขืœ ื™ืจื—, ืื• ืžืฉื”ื• ืื—ืจ,
01:29
it's the map of ourselves and the map of every plant
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ืื– ื–ื” ื”ืžื™ืคื•ื™ ืฉืœ ืขืฆืžื ื• ื•ื”ืžื™ืคื•ื™ ืฉืœ ื›ืœ ืฆืžื—
01:32
and every insect and every bacteria that really makes a difference.
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ื•ืฉืœ ื›ืœ ื—ืจืง ื•ืฉืœ ื›ืœ ื—ื™ื™ื“ืง ืฉืขื•ืฉื” ืืช ื”ื”ื‘ื“ืœ ื”ืืžื™ืชื™.
01:35
And it's beginning to tell us a lot about evolution.
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ื•ื–ื” ืžืชื—ื™ืœ ืœื•ืžืจ ืœื ื• ื”ืžื•ืŸ ืขืœ ื”ืื‘ื•ืœื•ืฆื™ื”.
01:40
(Laughter)
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(ืฆื—ื•ืง)
01:44
It turns out that what this stuff is --
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ืžืกืชื‘ืจ ืฉื”ื“ื‘ืจ ื”ื–ื” --
01:46
and Richard Dawkins has written about this --
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ื•ืจื™ืฆ'ืจื“ ื“ื•ืงื™ื ืก ื›ืชื‘ ืขืœ ื–ื” --
01:48
is, this is really a river out of Eden.
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ื”ื•ื ืžืžืฉ ื ื”ืจ ืฉืžืงื•ืจื• ื‘ื’ืŸ-ืขื“ืŸ.
01:50
So, the 3.2 billion base pairs inside each of your cells
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3.2 ืžื™ืœื™ืืจื“ ื”ื–ื•ื’ื•ืช ื‘ื›ืœ ืื—ื“ ืžื”ืชืื™ื ืฉืœื›ื ืžื›ื™ืœื™ื ืืช ื›ืœ ื”ื”ื™ืกื˜ื•ืจื™ื”
01:54
is really a history of where you've been for the past billion years.
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ืฉืœ ืžืงื•ื ื”ื™ืžืฆืื•ืชื›ื ื‘ืžื™ืœื™ืืจื“ ื”ืฉื ื™ื ื”ืื—ืจื•ื ื•ืช.
01:57
And we could start dating things,
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ื•ืื ื• ื™ื›ื•ืœื™ื ืœื”ืชื—ื™ืœ ืœืชืืจืš ื“ื‘ืจื™ื.
01:58
and we could start changing medicine and archeology.
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ื•ืื ื• ื™ื›ื•ืœื™ื ืœื”ืชื—ื™ืœ ืœืฉื ื•ืช ืชืจื•ืคื•ืช ื•ืืจื›ื™ืื•ืœื•ื’ื™ื”.
02:02
It turns out that if you take the human species about 700 years ago,
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ืžืชื‘ืจืจ ืฉืื ืžืกืชื›ืœื™ื ืขืœ ื”ืžื™ืŸ ื”ืื ื•ืฉื™ ืžืœืคื ื™ 700 ืฉื ื”,
02:05
white Europeans diverged from black Africans in a very significant way.
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ืืจื•ืคืื™ื ืœื‘ื ื™ื ื”ืชืคืฆืœื• ืžืืคืจื™ืงืื™ื ืฉื—ื•ืจื™ื ื‘ืื•ืคืŸ ืžืฉืžืขื•ืชื™.
02:08
White Europeans were subject to the plague.
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ืืจื•ืคืื™ื ืœื‘ื ื™ื ื”ื™ื• ืชื—ืช ื”ืฉืคืขืช ืžื—ืœืช ื”ื“ื‘ืจ.
02:14
And when they were subject to the plague, most people didn't survive,
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ื•ื›ืืฉืจ ื”ื ื”ื™ื• ื ืชื•ื ื™ื ืชื—ืช ื”ืฉืคืขืชื”, ืจื•ื‘ื ืœื ืฉืจื“ื•,
02:17
but those who survived had a mutation on the CCR5 receptor.
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ืื‘ืœ ืืœื” ืฉื›ืŸ, ื”ื™ื” ืืฆืœื ืฉื™ื ื•ื™ ื’ื ื˜ื™ ื‘ืงื•ืœื˜ืŸ CCR5.
02:21
And that mutation was passed on to their kids
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ื•ื”ืฉื™ื ื•ื™ ื”ื’ื ื˜ื™ ืขื‘ืจ ืœืฆืืฆืื™ื”ื
02:23
because they're the ones that survived,
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ืžืคื ื™ ืฉื”ื ืืœื” ืฉืฉืจื“ื•.
02:25
so there was a great deal of population pressure.
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ืœื›ืŸ ื ื•ืฆืจ ืœื—ืฅ ืื•ื›ืœื•ืกื™ืŸ.
02:27
In Africa, because you didn't have these cities,
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ื‘ืืคืจื™ืงื”, ื‘ื’ืœืœ ืฉืœื ื”ื™ื• ื›ืืœื” ืขืจื™ื,
02:29
you didn't have that CCR5 population pressure mutation.
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ืœื ื”ื™ื” ืฉื ืฉื™ื ื•ื™ ื’ื ื˜ื™ ื›ืชื•ืฆืื” ืžืœื—ืฅ ืื•ื›ืœื•ืกื™ื” ื‘ืขืœืช CCR5.
02:32
We can date it to 700 years ago.
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ืื ื• ื™ื›ื•ืœื™ื ืœืชืืจืš ื–ืืช ืžืœืคื ื™ 700 ืฉื ื”.
02:35
That is one of the reasons why AIDS is raging across Africa as fast as it is,
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ื–ื•ื”ื™ ืื—ืช ื”ืกื™ื‘ื•ืช ืžื“ื•ืข ืื™ื™ื“ืก ืžืชืคืฉื˜ ื‘ืืคืจื™ืงื” ื‘ืžื”ื™ืจื•ืช ื›ื–ื• ื’ื‘ื•ื”ื”,
02:39
and not as fast across Europe.
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ื•ืœื ื›ืœ-ื›ืš ืžื”ืจ ื‘ืื™ืจื•ืคื”.
02:43
And we're beginning to find these little things for malaria,
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ื•ืื ื• ืžืชื—ื™ืœื™ื ืœืžืฆื•ื ืืช ื”ื“ื‘ืจื™ื ื”ืงื˜ื ื™ื ื”ืœืœื• ืœื’ื‘ื™ ืžืœืจื™ื”,
02:46
for sickle cell, for cancers.
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ืœื’ื‘ื™ ืื ืžื™ื” ื—ืจืžืฉื™ืช, ืœื’ื‘ื™ ืกืจื˜ืŸ.
02:50
And in the measure that we map ourselves,
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ื•ื‘ืžื™ื“ื” ืฉื ืžืคื” ืืช ืขืฆืžื ื•,
02:52
this is the single greatest adventure that we'll ever be on.
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ื–ื•ื”ื™ ื”ื”ืจืคืชืงืื” ื”ื‘ื•ื“ื“ืช ื”ื’ื“ื•ืœื” ื‘ื™ื•ืชืจ ืฉื ื—ื•ื•ื” ืื™-ืคืขื.
02:54
And this Friday, I want you to pull out a really good bottle of wine,
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ื•ื‘ื™ื•ื ืฉื™ืฉื™ ื”ืงืจื•ื‘, ืื ื™ ืจื•ืฆื” ืฉืชื•ืฆื™ืื• ื‘ืงื‘ื•ืง ืฉืœ ื™ื™ืŸ ืžืฉื•ื‘ื—
02:58
and I want you to toast these two people.
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ื•ืชืฉืชื• ืœื—ื™ื™ ืฉื ื™ ืื ืฉื™ื ืืœื”.
03:01
Because this Friday, 50 years ago, Watson and Crick found the structure of DNA,
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ืžื›ื™ื•ื•ืŸ ืฉื‘ื™ื•ื ืฉื™ืฉื™ ื–ื” ืœืคื ื™ 50 ืฉื ื”, ื•ื•ื˜ืกื•ืŸ ื•ืงืจื™ืง ื’ื™ืœื• ืืช ืžื‘ื ื” ื”-DNA,
03:05
and that is almost as important a date
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ื•ืชืืจื™ืš ื–ื” ื—ืฉื•ื‘ ื›ืžืขื˜ ื›ืžื•
03:08
as the 12th of February when we first mapped ourselves,
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ื”-12 ื‘ืคื‘ืจื•ืืจ ื›ืืฉืจ ืžื™ืคื™ื ื• ืืช ืขืฆืžื ื• ืœืจืืฉื•ื ื”,
03:11
but anyway, we'll get to that.
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ืื‘ืœ ืขื•ื“ ื ื’ื™ืข ืœื–ื”.
03:13
I thought we'd talk about the new zoo.
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ื—ืฉื‘ืชื™ ืœื“ื‘ืจ ืขืœ ื’ืŸ-ื”ื—ื™ื•ืช ื”ื—ื“ืฉ.
03:15
So, all you guys have heard about DNA, all the stuff that DNA does,
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ื›ื•ืœื ื• ืฉืžืขื ื• ืขืœ DNA ื•ืขืœ ืžื” ืฉ-DNA ืขื•ืฉื”,
03:19
but some of the stuff we're discovering is kind of nifty
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ืื‘ืœ ื—ืœืง ืžื”ื“ื‘ืจื™ื ืฉืื ื• ืžื’ืœื™ื ื”ื ื‘ืืžืช ืžื™ื•ื—ื“ื™ื
03:22
because this turns out to be the single most abundant species on the planet.
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ืžื›ื™ื•ื•ืŸ ืฉืžืชื‘ืจืจ ืฉื–ื”ื• ื”ืžื™ืŸ ื”ื‘ื•ื“ื“ ื”ื ืคื•ืฅ ื‘ื™ื•ืชืจ ืขืœ ื›ื“ื•ืจ-ื”ืืจืฅ.
03:27
If you think you're successful or cockroaches are successful,
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ืื ืืชื ื—ื•ืฉื‘ื™ื ืฉืื ื—ื ื• ืื• ื”ืชื™ืงื ื™ื ื”ื ื”ืžื™ื ื™ื ื”ืžื•ืฆืœื—ื™ื ื‘ื™ื•ืชืจ,
03:30
it turns out that there's ten trillion trillion Pleurococcus sitting out there.
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ืžืกืชื‘ืจ ืฉื™ืฉื ื 10 ื˜ืจื™ืœื™ื•ื ื™ ื˜ืจื™ืœื™ื•ื ื™ื ืฉืœ ืื–ื•ื‘ื™ื.
03:33
And we didn't know that Pleurococcus was out there,
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ื•ืœื ื™ื“ืขื ื• ืฉืื–ื•ื‘ ืงื™ื™ื,
03:36
which is part of the reason
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ื•ื–ื• ืื—ืช ื”ืกื™ื‘ื•ืช
03:37
why this whole species-mapping project is so important.
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ืžื“ื•ืข ื›ืœ ื”ืžื™ื–ื ืฉืœ ืžื™ืคื•ื™ ื”ืžื™ื ื™ื ื”ื•ื ื›ื” ื—ืฉื•ื‘.
03:42
Because we're just beginning to learn
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ืžืคื ื™ ืฉืื ื• ืจืง ืžืชื—ื™ืœื™ื ืœืœืžื•ื“
03:44
where we came from and what we are.
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ืžื”ื™ื›ืŸ ื‘ืื ื• ื•ืžื” ืื ื—ื ื•.
03:46
And we're finding amoebas like this. This is the amoeba dubia.
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ื•ืื ื—ื ื• ืžื•ืฆืื™ื ืืžื‘ื•ืช ื›ืืœื”. ื–ื•ื”ื™ ืืžื‘ืช ื“ื•ื‘ื™ื”.
03:50
And the amoeba dubia doesn't look like much,
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ื•ืืžื‘ืช ื“ื•ื‘ื™ื” ืœื ื ืจืื™ืช ืžืฉื”ื• ืžื™ื•ื—ื“,
03:52
except that each of you has about 3.2 billion letters,
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ืžืœื‘ื“ ื”ืขื•ื‘ื“ื” ืฉืœื›ืœ ืื—ื“ ืžืื™ืชื ื• ื™ืฉ ื›-3.2 ืžื™ืœื™ืืจื“ ืื•ืชื™ื•ืช,
03:55
which is what makes you you,
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ืฉื–ื” ืžื” ืฉื”ื•ืคืš ืื•ืชื ื• ืœืžื” ืฉืื ื—ื ื•
03:57
as far as gene code inside each of your cells,
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ื›ื›ืœ ื”ื ื•ื’ืข ืœืฆื•ืคืŸ ื”ื’ื ื˜ื™ ืฉื‘ืชื•ืš ื‘ื›ืœ ืื—ื“ ืžืชืื™ื ื•,
04:00
and this little amoeba which, you know,
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ืื‘ืœ ื‘ืืžื‘ื” ืงื˜ื ื” ื–ื•, ืืฉืจ ื™ื•ืฉื‘ืช ื‘ืžื™ื
04:03
sits in water in hundreds and millions and billions,
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ืžืื•ืช ืžื™ืœื™ื•ื ื™ื ืื• ืžื™ืœื™ืืจื“ื™ ืฉื ื™ื,
04:06
turns out to have 620 billion base pairs of gene code inside.
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ืžืกืชื‘ืจ ืฉื™ืฉ ื‘ื” 620 ืžื™ืœื™ืืจื“ื™ ื–ื•ื’ื•ืช ื‘ืกื™ืกื™ื™ื ืฉืœ ืฆื•ืคืŸ ื’ื ื˜ื™.
04:12
So, this little thingamajig has a genome
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ืื– ืœื™ืฆื•ืจ ื”ืงื˜ืŸ ื”ื–ื” ื™ืฉ ื’ื ื•ื
04:15
that's 200 times the size of yours.
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ื”ื’ื“ื•ืœ ืคื™-200 ืžื–ื” ืฉืœื ื•.
04:18
And if you're thinking of efficient information storage mechanisms,
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ื•ืื ืชืจืฆื• ืœื“ืขืช ืžื”ื• ื”ืžื ื’ื ื•ืŸ ื”ื™ืขื™ืœ ืœืื—ืกื•ืŸ ืžื™ื“ืข,
04:22
it may not turn out to be chips.
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ืื•ืœื™ ื™ืชื‘ืจืจ ืฉื–ื” ืœื ื”ืฉื‘ื‘ื™ื.
04:25
It may turn out to be something that looks a little like that amoeba.
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ื™ื›ื•ืœ ืœื”ื™ื•ืช ืฉื™ืชื‘ืจืจ ืฉื–ื” ืžืฉื”ื• ืฉื ืจืื” ืงืฆืช ื›ืžื• ืืžื‘ื”.
04:29
And, again, we're learning from life and how life works.
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ื•ืฉื•ื‘, ืื ื• ืœื•ืžื“ื™ื ืžื”ื—ื™ื™ื ื•ืขืœ ื›ื™ืฆื“ ื”ื—ื™ื™ื ืคื•ืขืœื™ื.
04:33
This funky little thing: people didn't used to think
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ื”ื ื” ืžืงืจื” ืงื˜ืŸ ื•ืžืฉื•ื ื”: ืื ืฉื™ื ืœื ื—ืฉื‘ื•
04:37
that it was worth taking samples out of nuclear reactors
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ืฉืฉื•ื•ื” ืœืงื—ืช ื“ื•ื’ืžื™ื•ืช ืžื›ื•ืจื™ื ื’ืจืขื™ื ื™ื™ื
04:40
because it was dangerous and, of course, nothing lived there.
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ื›ื™ ื–ื” ืžืกื•ื›ืŸ, ื•ื›ืžื•ื‘ืŸ, ืฉืฉื•ื ื“ื‘ืจ ืœื ื—ื™ ืฉื.
04:43
And then finally somebody picked up a microscope
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ืขื“ ืฉืžื™ืฉื”ื• ืœืงื— ืžื™ืงืจื•ืกืงื•ืค
04:46
and looked at the water that was sitting next to the cores.
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ื•ืฆืคื” ื‘ืžื™ื ืฉื”ื™ื• ืœื™ื“ ื”ืœื™ื‘ื•ืช.
04:49
And sitting next to that water in the cores
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ื•ืœื™ื“ ืื•ืชื ืžื™ื ื‘ืœื™ื‘ื•ืช
04:51
was this little Deinococcus radiodurans, doing a backstroke,
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ื”ื™ื• Deinococcus radiodurans (ืžื™ืŸ ืฉืœ ื‘ืงื˜ืจื™ื•ืช ืขืžื™ื“ื•ืช ื‘ืงืจื™ื ื”), ืขื•ืฉื•ืช ืฉื—ื™ื™ืช-ื’ื‘,
04:54
having its chromosomes blown apart every day,
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ืฉื”ื›ืจื•ืžื•ื–ื•ืžื™ื ืฉืœื”ืŸ ืžืชืคืจืงื™ื ื›ืœ ื™ื•ื,
04:56
six, seven times, restitching them,
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ืฉืฉ, ืฉื‘ืข ืคืขืžื™ื, ืžืื—ื•ืช ืื•ืชื ื‘ื—ื–ืจื”,
04:59
living in about 200 times the radiation that would kill you.
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ื•ื›ืš ื—ื™ื•ืช ื‘ืงืจื™ื ื” ื”ื—ื–ืงื” ืคื™-200 ืžื–ื• ืฉื™ื›ื•ืœื” ืœื”ืจื•ื’ ืื•ืชื ื•.
05:02
And by now you should be getting a hint as to how diverse
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ื•ื‘ืฉืœื‘ ื–ื” ืืชื ื›ื‘ืจ ืžืชื—ื™ืœื™ื ืœื”ื‘ื™ืŸ ืขื“ ื›ืžื” ืžื’ื•ื•ืŸ
05:05
and how important and how interesting this journey into life is,
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ื•ื—ืฉื•ื‘ ื•ืžืขื ื™ื™ืŸ ื”ื•ื ืžืกืข ื–ื” ืืœ ืชื•ืš ื”ื—ื™ื™ื,
05:07
and how many different life forms there are,
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ื•ื›ืžื” ืฆื•ืจื•ืช ื—ื™ื™ื ืฉื•ื ื•ืช ื™ืฉ,
05:10
and how there can be different life forms living in
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ื•ื›ื™ืฆื“ ื™ื›ื•ืœื•ืช ืœื”ื™ื•ืช ืฆื•ืจื•ืช ื—ื™ื™ื ืฉื•ื ื•ืช ื”ืžืชืงื™ื™ืžื•ืช
05:13
very different places, maybe even outside of this planet.
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ื‘ืžืงื•ืžื•ืช ืฉื•ื ื™ื ืœื—ืœื•ื˜ื™ืŸ, ืื•ืœื™ ืืคื™ืœื• ืžื—ื•ืฅ ืœื›ื“ื•ืจ-ื”ืืจืฅ.
05:17
Because if you can live in radiation that looks like this,
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ืžืคื ื™ ืฉืื ื ื™ืชืŸ ืœื—ื™ื•ืช ื‘ืงืจื™ื ื” ื›ืžื• ื–ื•,
05:19
that brings up a whole series of interesting questions.
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ื–ื” ืžืขืœื” ืกื“ืจื” ืฉืœืžื” ืฉืœ ืฉืืœื•ืช ืžืขื ื™ื™ื ื•ืช.
05:23
This little thingamajig: we didn't know this thingamajig existed.
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ื”ื™ืฆื•ืจ ื”ืงื˜ืŸ ื”ื–ื”: ืœื ื™ื“ืขื ื• ืฉื”ื•ื ืงื™ื™ื.
05:27
We should have known that this existed
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ื”ื™ื™ื ื• ืฆืจื™ื›ื™ื ืœื“ืขืช ืฉื–ื” ืงื™ื™ื
05:29
because this is the only bacteria that you can see to the naked eye.
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ืžื›ื™ื•ื•ืŸ ืฉื–ื•ื”ื™ ื”ื‘ืงื˜ืจื™ื” ื”ื™ื—ื™ื“ื” ืฉื ื™ืชืŸ ืœืจืื•ืช ื‘ืขื™ืŸ ื’ืœื•ื™ื”.
05:32
So, this thing is 0.75 millimeters.
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ืื•ืจื›ื• 0.75 ืžื™ืœื™ืžื˜ืจ.
05:35
It lives in a deep trench off the coast of Namibia.
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ื”ื•ื ื—ื™ ื‘ืชืขืœื” ืขืžื•ืงื” ืœื™ื“ ื—ื•ืฃ ื‘ื ืžื™ื‘ื™ื”.
05:38
And what you're looking at with this namibiensis
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ื•ืžื” ืฉืืชื ืจื•ืื™ื ื›ืืŸ
05:40
is the biggest bacteria we've ever seen.
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ื”ื™ื ื”ื‘ืงื˜ืจื™ื” ื”ื’ื“ื•ืœื” ื‘ื™ื•ืชืจ ืฉืจืื™ื ื• ืื™-ืคืขื.
05:42
So, it's about the size of a little period on a sentence.
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ื’ื•ื“ืœื” ื›ื’ื•ื“ืœ ื”ื ืงื•ื“ื” ื‘ืกื•ืฃ ืžืฉืคื˜.
05:46
Again, we didn't know this thing was there three years ago.
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ืฉื•ื‘, ืœื ื™ื“ืขื ื• ืฉื“ื‘ืจ ื–ื” ืงื™ื™ื ืขื“ ืœืคื ื™ ืฉืœื•ืฉ ืฉื ื™ื.
05:50
We're just beginning this journey of life in the new zoo.
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ืื ื• ืจืง ืžืชื—ื™ืœื™ื ืืช ื”ืžืกืข ื‘ื’ืŸ-ื”ื—ื™ื•ืช ื”ื—ื“ืฉ.
05:54
This is a really odd one. This is Ferroplasma.
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ื–ื” ืื—ื“ ื‘ืืžืช ืžื•ื–ืจ. ื–ื”ื• ืคืจื•-ืคืœืกืžื”.
05:58
The reason why Ferroplasma is interesting is because it eats iron,
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ื”ืกื™ื‘ื” ืฉืคืจื•-ืคืœืกืžื” ืžืขื ื™ื™ืŸ ื”ื™ื ื‘ื’ืœืœ ืฉื”ื•ื ืื•ื›ืœ ื‘ืจื–ืœ,
06:02
lives inside the equivalent of battery acid,
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ื—ื™ ื‘ืชื•ืš ืžื” ืฉื“ื•ืžื” ืœื—ื•ืžืฆืช ืกื•ืœืœื”,
06:06
and excretes sulfuric acid.
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ื•ืžืคืจื™ืฉ ื—ื•ืžืฆื” ื’ืคืจืชื™ืช.
06:10
So, when you think of odd life forms,
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ืœื›ืŸ, ื›ืืฉืจ ื—ื•ืฉื‘ื™ื ืขืœ ืฆื•ืจื•ืช ื—ื™ื™ื ืžื•ื–ืจื•ืช,
06:12
when you think of what it takes to live,
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ื›ืืฉืจ ื—ื•ืฉื‘ื™ื ืขืœ ืžื” ืฉื“ืจื•ืฉ ื›ื“ื™ ืœื—ื™ื•ืช,
06:16
it turns out this is a very efficient life form,
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ืžืชื‘ืจืจ ืฉื–ื•ื”ื™ ืฆื•ืจืช ื—ื™ื™ื ืžืื•ื“ ื™ืขื™ืœื”,
06:18
and they call it an archaea. Archaea means "the ancient ones."
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ื•ืงื•ืจืื™ื ืœื” ืืจื›ื™ืื”. ืืจื›ื™ืื” ืคื™ืจื•ืฉื• ื”ืงื“ืžื•ื ื™ื.
06:22
And the reason why they're ancient is because this thing came up
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ื•ื”ืกื™ื‘ื” ืœื›ืš ืฉื”ื ืงื“ืžื•ื ื™ื, ื”ื™ื ืฉื”ื ื ื•ืฆืจื• ื›ืืฉืจ ื›ื“ื•ืจ-ื”ืืจืฅ
06:26
when this planet was covered
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ื”ื™ื” ืžื›ื•ืกื” ื‘ื—ื•ืžืจื™ื ื›ืžื•
06:28
by things like sulfuric acid in batteries,
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ื—ื•ืžืฆื” ื’ืคืจืชื™ืช ืฉื‘ืกื•ืœืœื•ืช,
06:29
and it was eating iron when the earth was part of a melted core.
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ื•ื”ื ื ื™ื–ื•ื ื• ืžื‘ืจื–ืœ ื›ืืฉืจ ื›ื“ื•ืจ-ื”ืืจืฅ ื”ื™ื” ื—ืœืง ืžืœื™ื‘ื” ืžื•ืชื›ืช.
06:34
So, it's not just dogs and cats and whales and dolphins
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ืื– ื–ื” ืœื ืจืง ื›ืœื‘ื™ื ื•ื—ืชื•ืœื™ื ื•ืœื•ื•ื™ื™ืชื ื™ื ื•ื“ื•ืœืคื™ื ื™ื
06:38
that you should be aware of and interested in on this little journey.
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ืฉืื ื• ืฆืจื™ื›ื™ื ืœื”ื™ื•ืช ืžื•ื“ืขื™ื ืืœื™ื”ื ื‘ืžืกืขื ื• ื–ื”.
06:42
Your fear should be that you are not,
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ืขืœื™ื ื• ืœื—ืฉื•ืฉ ืฉืื ื• ืœื --
06:45
that you're paying attention to stuff which is temporal.
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ืฉืื ื• ืฉืžื™ื ืœื‘ ืœื“ื‘ืจื™ื ืฉื”ื ื–ืžื ื™ื™ื.
06:48
I mean, George Bush -- he's going to be gone, alright? Life isn't.
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ืื ื™ ืžืชื›ื•ื•ืŸ, ื’'ื•ืจื’' ื‘ื•ืฉ -- ื”ื•ื ื™ื™ืœืš ืžืชื™ ืฉื”ื•ื, ื ื›ื•ืŸ? ืื‘ืœ ื”ื—ื™ื™ื ืœื.
06:54
Whether the humans survive or don't survive,
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ื‘ื™ืŸ ืื ื‘ื ื™-ืื“ื ืฉื•ืจื“ื™ื ื•ื‘ื™ืŸ ืื ืœืื•,
06:57
these things are going to be living on this planet or other planets.
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ื”ื“ื‘ืจื™ื ื”ืืœื” ื”ื•ืœื›ื™ื ืœื—ื™ื•ืช ืขืœ ื›ื“ื•ืจ-ื”ืืจืฅ ืื• ืขืœ ื›ื•ื›ื‘ื™-ืœื›ืช ืื—ืจื™ื.
07:00
And it's just beginning to understand this code of DNA
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ื•ื”ื”ืชื—ืœื” ื”ื–ื• ืฉืœื ื• ื‘ื”ื‘ื ืช ื”ืฆื•ืคืŸ ืฉืœ DNA
07:04
that's really the most exciting intellectual adventure
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ื”ื™ื ื‘ืืžืช ื”ื”ืจืคืชืงืื” ื”ืื™ื ื˜ืœืงื˜ื•ืืœื™ืช
07:07
that we've ever been on.
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ื”ืžืจื’ืฉืช ื‘ื™ื•ืชืจ ืฉื—ื•ื•ื™ื ื• ืื™-ืคืขื.
07:10
And you can do strange things with this stuff. This is a baby gaur.
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ื•ืืคืฉืจ ืœื‘ืฆืข ื“ื‘ืจื™ื ืžื•ื–ืจื™ื ืขื ื”ื—ื•ืžืจ ื”ื–ื”. ื–ื”ื• ื’ืื•ืจ (ืฉื•ืจ ื‘ืจ ืืกื™ืืชื™) ื‘ืŸ ื™ื•ืžื•.
07:14
Conservation group gets together,
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ืงื‘ื•ืฆื” ืœืฉื™ืžื•ืจ ื”ื˜ื‘ืข ืžืชื›ื ืกืช,
07:16
tries to figure out how to breed an animal that's almost extinct.
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ืžื ืกื” ืœืžืฆื•ื ื“ืจืš ืœื’ื“ืœ ื‘ืขืœ-ื—ื™ื™ื ืฉื›ืžืขื˜ ื ื›ื—ื“.
07:21
They can't do it naturally, so what they do with this thing is
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ื”ื ืœื ื™ื›ื•ืœื™ื ืœืขืฉื•ืช ื–ืืช ื‘ื“ืจืš ื”ื˜ื‘ืขื™ืช, ืื– ืžื” ืฉื”ื ืขื•ืฉื™ื
07:24
they take a spoon, take some cells out of an adult gaur's mouth, code,
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ื–ื” ืœืงื—ืช ื›ืคื™ืช, ืœื™ื˜ื•ืœ ื›ืžื” ืชืื™ื ืžืคื™ื• ืฉืœ ื’ืื•ืจ ื‘ื•ื’ืจ, ืฆื•ืคืŸ,
07:30
take the cells from that and insert it into a fertilized cow's egg,
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ืœื•ืงื—ื™ื ืืช ื”ืชืื™ื ื•ืžื›ื ื™ืกื™ื ืื•ืชื ืืœ ืชื•ืš ื‘ื™ืฆื™ืช ืžื•ืคืจื™ืช ืฉืœ ืคืจื”,
07:35
reprogram cow's egg -- different gene code.
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ืžืงื•ื“ื“ื™ื ืžื—ื“ืฉ ืืช ื‘ื™ืฆื™ืช ื”ืคืจื” -- ืฆื•ืคืŸ ื’ื ื˜ื™ ืฉื•ื ื”.
07:39
When you do that, the cow gives birth to a gaur.
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ื›ืืฉืจ ืขื•ืฉื™ื ื–ืืช, ื”ืคืจื” ืžื•ืœื™ื“ื” ื’ืื•ืจ.
07:44
We are now experimenting with bongos, pandas, elands, Sumatran tigers,
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ื›ืขืช ืื ื• ืขื•ืจื›ื™ื ื ื™ืกื•ื™ื™ื ืขื ืชืื• ืืคืจื™ืงื ื™, ืคื ื“ื•ืช, ื ืžืจื™ื ืกื•ืžืื˜ืจื™ื™ื,
07:50
and the Australians -- bless their hearts --
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ื•ื”ืื•ืกื˜ืจืœื™ื -- ืฉื™ื”ื™ื• ื‘ืจื™ืื™ื --
07:53
are playing with these things.
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ืžื ืกื™ื ื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื.
07:54
Now, the last of these things died in September 1936.
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ื”ืคืจื˜ ื”ืื—ืจื•ืŸ ืžืืœื” ืžืช ื‘ืกืคื˜ืžื‘ืจ 1936.
07:58
These are Tasmanian tigers. The last known one died at the Hobart Zoo.
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ืืœื” ื”ื ื ืžืจื™ื ื˜ืืกืžื ื™ื™ื. ื”ืื—ืจื•ืŸ ืžื‘ื™ื ื™ื”ื ืžืช ื‘ื’ืŸ-ื—ื™ื•ืช ื”ื•ื‘ืืจื“.
08:02
But it turns out that as we learn more about gene code
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ืื‘ืœ ืžืกืชื‘ืจ ืฉื›ื›ืœ ืฉืื ื• ืœื•ืžื“ื™ื ื™ื•ืชืจ ืขืœ ื”ืฆื•ืคืŸ ื”ื’ื ื˜ื™
08:05
and how to reprogram species,
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ื•ื›ื™ืฆื“ ืœืงื•ื“ื“ ืžื™ื ื™ื ืžื—ื“ืฉ,
08:07
we may be able to close the gene gaps in deteriorate DNA.
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ื™ื™ืชื›ืŸ ื•ื ื•ื›ืœ ืœืกื’ื•ืจ ืืช ื”ืคืขืจื™ื ื‘ื’ื ื™ื ื‘-DNA ืคื’ื•ื.
08:12
And when we learn how to close the gene gaps,
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ื•ื›ืืฉืจ ื ืœืžื“ ื›ื™ืฆื“ ืœืกื’ื•ืจ ืืช ื”ืคืขืจื™ื ื‘ื’ื ื™ื,
08:15
then we can put a full string of DNA together.
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ืื– ื ื•ื›ืœ ืœื”ื ื™ื— ืฉืจืฉืจืช ืฉืœืžื” ืฉืœ DNA ื‘ื™ื—ื“.
08:18
And if we do that, and insert this into a fertilized wolf's egg,
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ื•ืื ื ืขืฉื” ื–ืืช ื•ื ืฉืชื•ืœ ืืช ื–ื” ื‘ื‘ื™ืฆื™ืช ืžื•ืคืจื™ืช ืฉืœ ื–ืื‘ื”,
08:23
we may give birth to an animal
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ืื ื• ืขืฉื•ื™ื™ื ืœื’ืจื•ื ืœื”ื•ืœื“ืช ื‘ืขืœ-ื—ื™ื™ื
08:25
that hasn't walked the earth since 1936.
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ืฉืœื ื”ืชื”ืœืš ืขืœ ื”ืื“ืžื” ืžืื– 1936.
08:28
And then you can start going back further,
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ื•ืื– ื ืชื—ื™ืœ ืœืœื›ืช ืขื•ื“ ื™ื•ืชืจ ืื—ื•ืจื”,
08:30
and you can start thinking about dodos,
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ื•ื ื•ื›ืœ ืœื”ืชื—ื™ืœ ืœื—ืฉื•ื‘ ืขืœ ื“ื•ื“ื• (ืกื•ื’ ืขื•ืฃ ื ื›ื—ื“),
08:33
and you can think about other species.
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ื•ื ื™ืชืŸ ืœื—ืฉื•ื‘ ืขืœ ืžื™ื ื™ื ืื—ืจื™ื.
08:35
And in other places, like Maryland, they're trying to figure out
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ื•ื‘ืžืงื•ืžื•ืช ืื—ืจื™ื, ื›ืžื• ืžืจื™ืœื ื“, ื”ื ืžื ืกื™ื ืœื’ืœื•ืช
08:38
what the primordial ancestor is.
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ืžื™ื”ื• ื”ืื‘ ื”ืงื“ืžื•ืŸ.
08:40
Because each of us contains our entire gene code
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ืžื›ื™ื•ื•ืŸ ืฉื›ืœ ืื—ื“ ืžืื™ืชื ื• ืžื›ื™ืœ ืืช ื”ืฆื•ืคืŸ ื”ื’ื ื˜ื™ ื”ืฉืœื
08:43
of where we've been for the past billion years,
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ืฉืœ ื”ื™ื›ืŸ ืฉื”ื™ื™ื ื• ื‘ืžืฉืš ืžื™ืœื™ืืจื“ ื”ืฉื ื™ื ื”ืื—ืจื•ื ื•ืช,
08:46
because we've evolved from that stuff,
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ืžืื—ืจ ื•ื”ืชืคืชื—ื ื• ืžืื•ืชื• ื—ื•ืžืจ,
08:48
you can take that tree of life and collapse it back,
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ื ื™ืชืŸ ืœืงื—ืช ืืช ืื™ืœืŸ ื”ื™ื•ื—ืกื™ืŸ ื•ืœื”ืคืขื™ืœื• ื‘ืจื•ื•ืจืก,
08:50
and in the measure that you learn to reprogram,
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ื•ื‘ืžื™ื“ื” ื•ื ืœืžื“ ืœืงื•ื“ื“ ืžื—ื“ืฉ,
08:53
maybe we'll give birth to something
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ืื•ืœื™ ื ื•ืœื™ื“ ืžืฉื”ื•
08:55
that is very close to the first primordial ooze.
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ืฉื”ื•ื ืงืจื•ื‘ ืžืื•ื“ ืœืขื™ืกื” ื”ืงื“ืžื•ื ื™ืช ื”ืจืืฉื•ื ื”.
08:57
And it's all coming out of things that look like this.
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ื•ื”ื›ืœ ื ื•ื‘ืข ืžืžืงื•ืžื•ืช ืฉื ืจืื™ื ื‘ืขืจืš ื›ืš.
08:59
These are companies that didn't exist five years ago.
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ืืœื• ื”ืŸ ื—ื‘ืจื•ืช ืฉืœื ื”ื™ื• ืงื™ื™ืžื•ืช ืœืคื ื™ 5 ืฉื ื™ื.
09:01
Huge gene sequencing facilities the size of football fields.
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ืžืชืงื ื™ื ื‘ื’ื•ื“ืœ ืžื’ืจืฉื™ ื›ื“ื•ืจื’ืœ ืœืกื™ื“ื•ืจ ืฉืœ ื’ื ื™ื.
09:05
Some are public. Some are private.
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ื—ืœืงื ืฆื™ื‘ื•ืจื™ื™ื. ื—ืœืงื ืคืจื˜ื™ื™ื.
09:07
It takes about 5 billion dollars to sequence a human being the first time.
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ื“ืจื•ืฉื™ื ื›-5 ืžื™ืœื™ืืจื“ื™ ื“ื•ืœืจื™ื ื›ื“ื™ ืœืขืจื•ืš ื‘ืŸ-ืื ื•ืฉ ื‘ืคืขื ื”ืจืืฉื•ื ื”.
09:11
Takes about 3 million dollars the second time.
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ื“ืจื•ืฉื™ื ื›-3 ืžื™ืœื™ื•ืŸ ื“ื•ืœืจ ื‘ืคืขื ื”ืฉื ื™ื”.
09:13
We will have a 1,000-dollar genome within the next five to eight years.
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ื™ื”ื™ื” ืœื ื• ื’ื ื•ื ื‘-1,000 ื“ื•ืœืจ ื‘ืชื•ืš 5-8 ื”ืฉื ื™ื ื”ื‘ืื•ืช.
09:17
That means each of you will contain on a CD your entire gene code.
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ื–ื” ืื•ืžืจ ืฉื›ืœ ืื—ื“ ืžืื™ืชื ื• ื™ื—ื–ื™ืง ืขืœ ืชืงืœื™ื˜ื•ืจ ืืช ื›ืœ ื”ืฆื•ืคืŸ ื”ื’ื ื˜ื™ ืฉืœื•.
09:22
And it will be really boring. It will read like this.
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ื•ื–ื” ื™ื”ื™ื” ืžืžืฉ ืžืฉืขืžื. ื”ื•ื ื™ื™ืจืื” ื›ืš.
09:25
(Laughter)
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(ืฆื—ื•ืง)
09:27
The really neat thing about this stuff is that's life.
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ื”ื“ื‘ืจ ื”ื›ื™ ื’ื“ื•ืœ ื”ืงืฉื•ืจ ื‘ื—ื•ืžืจ ื–ื” ืฉื”ื•ื ื”ื—ื™ื™ื ืขืฆืžื.
09:29
And Laurie's going to talk about this one a little bit.
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ื•ืœื•ืจื™ ืขื•ืžื“ืช ืœื“ื‘ืจ ืขืœ ื–ื” ืงืฆืช.
09:32
Because if you happen to find this one inside your body,
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ืžืื—ืจ ื•ืื ื ืžืฆื ืืช ื–ื” ื‘ืชื•ืš ื’ื•ืคื™ื ื•,
09:34
you're in big trouble, because that's the source code for Ebola.
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ื ื”ื™ื” ื‘ืฆืจื” ืฆืจื•ืจื” ืžื›ื™ื•ื•ืŸ ืฉื–ื”ื• ืฆื•ืคืŸ ื”ืžืงื•ืจ ืฉืœ ืื‘ื•ืœื”.
09:38
That's one of the deadliest diseases known to humans.
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ื–ื•ื”ื™ ืื—ืช ื”ืžื—ืœื•ืช ื”ืงื˜ืœื ื™ื•ืช ื‘ื™ื•ืชืจ ื”ื™ื“ื•ืขื” ืœืื“ื.
09:40
But plants work the same way and insects work the same way,
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ืื‘ืœ ืฆืžื—ื™ื ืคื•ืขืœื™ื ื‘ืื•ืชื• ืื•ืคืŸ ื•ื—ืจืงื™ื ืคื•ืขืœื™ื ื‘ืื•ืชื• ืื•ืคืŸ,
09:42
and this apple works the same way.
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ื•ืชืคื•ื— ื–ื” ืคื•ืขืœ ื‘ืื•ืชื• ืื•ืคืŸ.
09:44
This apple is the same thing as this floppy disk.
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ืชืคื•ื— ื–ื” ื”ื•ื ืื•ืชื• ื“ื‘ืจ ื›ืžื• ื“ื™ืกืงื˜ ื–ื”.
09:46
Because this thing codes ones and zeros,
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ืžืคื ื™ ืฉื“ื‘ืจ ื–ื” ืžืงื•ื“ื“ ื‘ืขื–ืจืช 1 ื•-0,
09:48
and this thing codes A, T, C, Gs, and it sits up there,
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ื•ื“ื‘ืจ ื–ื” ืžืงื•ื“ื“ ื‘ืขื–ืจืช A, T, C ื•-Gื™ื ื•ื”ื•ื ื™ื•ืฉื‘ ืฉื ืœืžืขืœื”,
09:50
absorbing energy on a tree, and one fine day
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ืงื•ืœื˜ ืื ืจื’ื™ื” ืขืœ ืขืฅ ื•ืื– ื™ื•ื ื‘ื”ื™ืจ ืื—ื“
09:53
it has enough energy to say, execute, and it goes [thump]. Right?
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ื™ืฉ ืœื• ืžืกืคื™ืง ืื ืจื’ื™ื”, ื ืืžืจ, ืœื”ื•ืฆื™ื ืœืคื•ืขืœ ืคืงื•ื“ื”, ื•ื‘ื•ื. ื ื›ื•ืŸ?
09:57
(Laughter)
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(ืฆื—ื•ืง)
10:00
And when it does that, pushes a .EXE, what it does is,
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ื•ื›ืืฉืจ ื”ื•ื ืขื•ืฉื” ื–ืืช, ื›ืืฉืจ ื”ื•ื ืœื•ื—ืฅ ืขืœ EXE, ืžื” ืฉื”ื•ื ืขื•ืฉื”,
10:04
it executes the first line of code, which reads just like that,
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ื”ื•ื ืžื•ืฆื™ื ืœืคื•ืขืœ ืฉื•ืจื” ืจืืฉื•ื ื” ืฉืœ ืฆื•ืคืŸ, ืืฉืจ ื ืจืื™ืช ืคืฉื•ื˜ ื›ืš,
10:07
AATCAGGGACCC, and that means: make a root.
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AATCAGGGACCC, ื•ืคื™ืจื•ืฉื”: ืชื™ืฆื•ืจ ืฉื•ืจืฉ.
10:10
Next line of code: make a stem.
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ืฉื•ืจื” ื”ื‘ืื” ื‘ืฆื•ืคืŸ: ืชื™ืฆื•ืจ ื’ื‘ืขื•ืœ.
10:12
Next line of code, TACGGGG: make a flower that's white,
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ืฉื•ืจื” ื”ื‘ืื” ื‘ืฆื•ืคืŸ, TACGGGG: ืชื™ืฆื•ืจ ืคืจื— ืฉื”ื•ื ืœื‘ืŸ,
10:15
that blooms in the spring, that smells like this.
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ืืฉืจ ืคื•ืจื— ื‘ืื‘ื™ื‘ ื•ืžืจื™ื— ื›ืš ื•ื›ืš.
10:18
In the measure that you have the code
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ื‘ืžื™ื“ื” ื•ื™ืฉ ืœื ื• ืืช ื”ืฆื•ืคืŸ
10:20
and the measure that you read it --
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ื•ื‘ืžื™ื“ื” ื•ืงื•ืจืื™ื ืื•ืชื• --
10:23
and, by the way, the first plant was read two years ago;
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ื•ื“ืจืš ืื’ื‘, ื”ืฆืžื— ื”ืจืืฉื•ืŸ ื ืงืจื ืœืคื ื™ ืฉื ืชื™ื™ื;
10:25
the first human was read two years ago;
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ื”ืื“ื ื”ืจืืฉื•ืŸ ื ืงืจื ืœืคื ื™ ืฉื ืชื™ื™ื;
10:27
the first insect was read two years ago.
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ื”ื—ืจืง ื”ืจืืฉื•ืŸ ื ืงืจื ืœืคื ื™ ืฉื ืชื™ื™ื.
10:29
The first thing that we ever read was in 1995:
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ื”ืคืขื ื”ืจืืฉื•ื ื” ืฉืงืจืื ื• ืžืฉื”ื• ื”ื™ืชื” ื‘-1995:
10:32
a little bacteria called Haemophilus influenzae.
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ื‘ืงื˜ืจื™ื” ืงื˜ื ื” ื”ืžื›ื•ื ื” "ื”ืžื•ืคื™ืœื•ืก ื”ืฉืคืขืช".
10:35
In the measure that you have the source code, as all of you know,
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ื‘ืชื ืื™ ืฉื™ืฉ ืœื ื• ืืช ืฆื•ืคืŸ ืžืงื•ืจ, ื›ืคื™ ืฉื›ื•ืœื ื• ืžื›ื™ืจื™ื,
10:38
you can change the source code, and you can reprogram life forms
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ื ื™ืชืŸ ืœืฉื ื•ืช ืืช ืฆื•ืคืŸ ื”ืžืงื•ืจ, ื•ื ื™ืชืŸ ืœืงื•ื“ื“ ืžื—ื“ืฉ ืฆื•ืจื•ืช ื—ื™ื™ื
10:40
so that this little thingy becomes a vaccine,
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ื›ืš ืฉื”ื™ืฆื•ืจ ื”ืงื˜ื ื˜ืŸ ื”ื–ื” ื™ื”ืคื•ืš ืœื—ื™ืกื•ืŸ,
10:42
or this little thingy starts producing biomaterials,
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ืื• ืฉื”ื™ืฆื•ืจ ื”ืงื˜ื ื˜ืŸ ื”ื–ื” ื™ืชื—ื™ืœ ืœื™ื™ืฆืจ ื—ื•ืžืจื™ื ื‘ื™ื•ืœื•ื’ื™ื™ื,
10:45
which is why DuPont is now growing a form of polyester
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ืฉื‘ืฉืœ ื›ืš ื“ื•'ืคื•ื ื˜ ืžื’ื“ืœืช ื‘ื™ืžื™ื ืืœื” ืฆื•ืจืช ืคื•ืœื™ืืกื˜ืจ
10:48
that feels like silk in corn.
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ืฉื ื•ืชืŸ ืชื—ื•ืฉื” ืฉืœ ืžืฉื™ ื‘ืชื™ืจืก.
10:51
This changes all rules. This is life, but we're reprogramming it.
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ื–ื” ืžืฉื ื” ืืช ื›ืœ ื”ื›ืœืœื™ื. ืืœื” ื”ื ื”ื—ื™ื™ื, ืื‘ืœ ืื ื—ื ื• ืžืงื•ื“ื“ื™ื ืื•ืชื ืžื—ื“ืฉ.
10:58
This is what you look like. This is one of your chromosomes.
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ื›ืš ืื ื• ื ืจืื™ื. ื–ื”ื• ืื—ื“ ื”ื›ืจื•ืžื•ื–ื•ืžื™ื ืฉืœื ื•.
11:02
And what you can do now is,
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ื•ืžื” ืฉื ื™ืชืŸ ืœืขืฉื•ืช ื›ืขืช ื”ื•ื:
11:04
you can outlay exactly what your chromosome is,
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ื ื™ืชืŸ ืœืชืืจ ื‘ืžื“ื•ื™ื™ืง ืžื” ื”ื›ืจื•ืžื•ื–ื•ื ืฉืœื ื•,
11:07
and what the gene code on that chromosome is right here,
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ื•ื”ืฆื•ืคืŸ ื”ื’ื ื˜ื™ ืฉืขืœ ืื•ืชื• ื›ืจื•ืžื•ื–ื•ื, ื”ื•ื ื›ืืŸ
11:10
and what those genes code for, and what animals they code against,
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ื•ืื™ื–ื” ืฆื•ืคืŸ ื”ื’ื ื™ื ื”ืœืœื• ืžื™ื™ืฆื’ื™ื, ื•ืขื‘ื•ืจ ืื™ื–ื• ื—ื™ื” ื”ื ืžืงื•ื“ื“ื™ื,
11:13
and then you can tie it to the literature.
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ื•ืื– ื ื™ืชืŸ ืœืงืฉืจ ื–ืืช ืœืกืคืจื•ืช ื”ืžืงืฆื•ืขื™ืช.
11:15
And in the measure that you can do that, you can go home today,
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ื•ื‘ืžื™ื“ื” ืฉื ื™ืชืŸ ืœืขืฉื•ืช ื–ืืช, ืืคืฉืจ ืœื—ื–ื•ืจ ื”ื™ื•ื ื”ื‘ื™ืชื”,
11:18
and get on the Internet, and access
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ืœื”ื™ื›ื ืก ืœืื™ื ื˜ืจื ื˜ ื•ืœื’ืฉืช
11:20
the world's biggest public library, which is a library of life.
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ืœืกืคืจื™ื” ื”ืฆื™ื‘ื•ืจื™ืช ื”ื›ื™ ื’ื“ื•ืœื” ื‘ืขื•ืœื,ืฉื”ื™ื ืกืคืจื™ื™ืช ื”ื—ื™ื™ื.
11:24
And you can do some pretty strange things
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ื•ื ื™ืชืŸ ืœื‘ืฆืข ื›ืžื” ื“ื‘ืจื™ื ื“ื™ ืžื•ื–ืจื™ื
11:26
because in the same way as you can reprogram this apple,
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ืžืื—ืจ ื•ื‘ืื•ืชื” ื“ืจืš ืฉื ื™ืชืŸ ืœืงื•ื“ื“ ื‘ื” ืชืคื•ื— ื–ื” ืžื—ื“ืฉ,
11:29
if you go to Cliff Tabin's lab at the Harvard Medical School,
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ืื ื”ื•ืœื›ื™ื ืœืžืขื‘ื“ืชื• ืฉืœ ืงืœื™ืฃ ื˜ืื‘ื™ืŸ ื‘ื‘ื™ืช-ืกืคืจ ืœืจืคื•ืื” ื‘ื”ืจื•ื•ืจื“,
11:32
he's reprogramming chicken embryos to grow more wings.
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ื”ื•ื ืžืงื•ื“ื“ ืžื—ื“ืฉ ืขื•ื‘ืจื™ ืขื•ืคื•ืช ื›ื“ื™ ืฉื™ื’ื“ืœื• ืœื”ื ื™ื•ืชืจ ื›ื ืคื™ื™ื.
11:38
Why would Cliff be doing that? He doesn't have a restaurant.
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ืžื“ื•ืข ืฉืงืœื™ืฃ ื™ืขืฉื” ื–ืืช? ื”ืจื™ ืื™ืŸ ืœื• ืžืกืขื“ื”.
11:41
(Laughter)
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(ืฆื—ื•ืง)
11:43
The reason why he's reprogramming that animal to have more wings
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ื”ืกื™ื‘ื” ืœื›ืš ืฉื”ื•ื ืžืงื•ื“ื“ ืžื—ื“ืฉ ื›ื“ื™ ืฉื™ื’ื“ืœื• ื™ื•ืชืจ ื›ื ืคื™ื™ื
11:46
is because when you used to play with lizards as a little child,
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ื”ื™ื ื‘ื’ืœืœ ืฉื›ืืฉืจ ื ื”ื’ืชื ืœืฉื—ืง ืขื ืœื˜ืื•ืช ื‘ืชื•ืจ ื™ืœื“ื™ื ืงื˜ื ื™ื,
11:49
and you picked up the lizard, sometimes the tail fell off, but it regrew.
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ื•ื”ืจืžืชื ืœื˜ืื”, ืœืคืขืžื™ื ื–ื ื‘ื” ื ืฉืจ, ืื‘ืœ ื”ื•ื ืฆืžื— ืžื—ื“ืฉ.
11:53
Not so in human beings:
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ืืฆืœ ื‘ื ื™-ืื“ื ื–ื” ืœื ื›ืš:
11:56
you cut off an arm, you cut off a leg -- it doesn't regrow.
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ื’ื•ื“ืขื™ื ื™ื“, ื’ื•ื“ืขื™ื ืจื’ืœ, ืื‘ืœ ื”ื ืื™ื ื ืฆื•ืžื—ื™ื ืžื—ื“ืฉ.
11:59
But because each of your cells contains your entire gene code,
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ืื‘ืœ ื‘ื’ืœืœ ืฉื›ืœ ืชื ืฉืœื ื• ืžื›ื™ืœ ืืช ื›ืœ ื”ืฆื•ืคืŸ ื”ื’ื ื˜ื™ ืฉืœื ื•,
12:04
each cell can be reprogrammed, if we don't stop stem cell research
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ื ื™ืชืŸ ืœืงื•ื“ื“ ืžื—ื“ืฉ ื›ืœ ืชื -- ืื ืœื ื ืขืฆื•ืจ ืืช ื—ืงืจ ืชืื™-ื”ื’ื–ืข
12:08
and if we don't stop genomic research,
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ื•ืื ืœื ื ืขืฆื•ืจ ืืช ื—ืงืจ ื”ื’ื ื•ื --
12:10
to express different body functions.
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ื›ืš ืฉื™ื‘ื˜ื ืคื•ื ืงืฆื™ื•ืช ื’ื•ืคื ื™ื•ืช ืฉื•ื ื•ืช.
12:14
And in the measure that we learn how chickens grow wings,
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ื•ื‘ืžื™ื“ื” ืฉื ืœืžื“ ื›ื™ืฆื“ ืขื•ืคื•ืช ืžืฆืžื™ื—ื™ื ื›ื ืคื™ื™ื,
12:17
and what the program is for those cells to differentiate,
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ื•ืžื”ื• ื”ืฆื•ืคืŸ ื”ืžื‘ื“ื™ืœ ืืช ืื•ืชื ื”ืชืื™ื,
12:19
one of the things we're going to be able to do
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ืื—ื“ ื”ื“ื‘ืจื™ื ืฉื ื”ื™ื” ืžืกื•ื’ืœื™ื ืœืขืฉื•ืช
12:22
is to stop undifferentiated cells, which you know as cancer,
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ื”ื•ื ืœืขืฆื•ืจ ืชืื™ื ื‘ืœืชื™ ืžื•ื‘ื“ืœื™ื, ืฉืื ื• ืžื›ื™ืจื™ื ืื•ืชื ื‘ืชื•ืจ ืกืจื˜ืŸ,
12:26
and one of the things we're going to learn how to do
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ื•ืื—ื“ ื”ื“ื‘ืจื™ื ืฉืื ื• ื”ื•ืœื›ื™ื ืœืœืžื•ื“ ื›ื™ืฆื“ ืœืขืฉื•ืช,
12:28
is how to reprogram cells like stem cells
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ื–ื” ื›ื™ืฆื“ ืœืงื•ื“ื“ ืžื—ื“ืฉ ืชืื™ื ื›ืžื• ืชืื™-ื’ื–ืข
12:31
in such a way that they express bone, stomach, skin, pancreas.
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ื‘ืื•ืคืŸ ื›ื–ื” ืฉื”ื ื™ื‘ื˜ืื• ืขืฆืžื•ืช, ืงื™ื‘ื”, ืขื•ืจ, ืœื‘ืœื‘.
12:38
And you are likely to be wandering around -- and your children --
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ื•ืจื•ื‘ ื”ืกื™ื›ื•ื™ื™ื ืฉืชืขืžื“ื• ื•ืชืชืคืœืื• - ื•ื’ื ื™ืœื“ื™ื›ื --
12:41
on regrown body parts in a reasonable period of time,
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ืขืœ ืื‘ืจื™ ื’ื•ืฃ ืฉืฆืžื—ื• ืžื—ื“ืฉ ื‘ืชื•ืš ืคืจืง ื–ืžืŸ ืกื‘ื™ืจ,
12:45
in some places in the world where they don't stop the research.
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ื‘ื›ืžื” ืžืงื•ืžื•ืช ื‘ืขื•ืœื ืฉื‘ื”ื ืœื ืขื•ืฆืจื™ื ืืช ื”ืžื—ืงืจ.
12:50
How's this stuff work? If each of you differs
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ืื™ืš ื›ืœ ื–ื” ืขื•ื‘ื“? ืื ื›ืœ ืื—ื“ ืžืื™ืชื ื• ื ื‘ื“ืœ
12:55
from the person next to you by one in a thousand, but only three percent codes,
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ืžื”ืื“ื ืฉืœื™ื“ื• ื‘ืื—ื“ ื—ืœืงื™ ืืœืฃ, ืื‘ืœ ืจืง ื‘-3 ืื—ื•ื–ื™ื ืžื”ืฆื•ืคืŸ,
12:58
which means it's only one in a thousand times three percent,
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ื–ื” ืื•ืžืจ ืจืง ืื—ื“ ื—ืœืงื™ ืืœืฃ ืคืขืžื™ื 3 ืื—ื•ื–,
13:00
very small differences in expression and punctuation
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ื”ื‘ื“ืœื™ื ืžืื•ื“ ืงื˜ื ื™ื ื‘ืคื™ืกื•ืง ื•ื ื™ืงื•ื“
13:03
can make a significant difference. Take a simple declarative sentence.
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ื™ื›ื•ืœื™ื ืœื™ืฆื•ืจ ื”ื‘ื“ืœื™ื ืžืฉืžืขื•ืชื™ื™ื. ื ื™ืงื— ืžืฉืคื˜ ื”ืฆื”ืจืชื™ ืคืฉื•ื˜.
13:08
(Laughter)
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(ืฆื—ื•ืง)
13:10
Right?
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ื ื›ื•ืŸ?
13:11
That's perfectly clear. So, men read that sentence,
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ื–ื” ื‘ืจื•ืจ ืœื’ืžืจื™. ืื–, ื’ื‘ืจื™ื ืงื•ืจืื™ื ืืช ื”ืžืฉืคื˜ ื”ื–ื”,
13:15
and they look at that sentence, and they read this.
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ื•ื”ื ืžืกืชื›ืœื™ื ืขืœ ืžืฉืคื˜ ื”ื–ื”, ื•ื”ื ืงื•ืจืื™ื ืืช ื–ื”.
13:23
Okay?
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ื‘ืกื“ืจ?
13:24
Now, women look at that sentence and they say, uh-uh, wrong.
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ื›ืขืช, ื ืฉื™ื ืžืกืชื›ืœื•ืช ืขืœ ื”ืžืฉืคื˜ ื•ื”ืŸ ืื•ืžืจื•ืช, ืœื ื•ืœื, ื–ื• ื˜ืขื•ืช.
13:28
This is the way it should be seen.
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ื›ืš ื”ื•ื ืฆืจื™ืš ืœื”ื™ื•ืช.
13:32
(Laughter)
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(ืฆื—ื•ืง)
13:40
That's what your genes are doing.
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ื–ื” ืžื” ืฉื”ื’ื ื™ื ืฉืœื ื• ืขื•ืฉื™ื.
13:41
That's why you differ from this person over here by one in a thousand.
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ื‘ื’ืœืœ ื–ื” ืืชื” ืฉื•ื ื” ืžื”ืื“ื ื”ื–ื” ื›ืืŸ ื‘ืื—ื“ ื—ืœืงื™ ืืœืฃ.
13:46
Right? But, you know, he's reasonably good looking, but...
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ืื‘ืœ, ืืชื ื™ื•ื“ืขื™ื, ื”ื•ื ื ืจืื” ื“ื™ ื˜ื•ื‘, ืื‘ืœ....
13:49
I won't go there.
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ื ืขื–ื•ื‘ ืืช ื–ื”.
13:52
You can do this stuff even without changing the punctuation.
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ื ื™ืชืŸ ืœื‘ืฆืข ื–ืืช ืืคื™ืœื• ืœืœื ืฉื™ื ื•ื™ ื‘ืคื™ืกื•ืง.
13:56
You can look at this, right?
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ืืชื ื™ื›ื•ืœื™ื ืœืจืื•ืช ืืช ื–ื”, ื ื›ื•ืŸ?
14:00
And they look at the world a little differently.
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ื”ื ืžื‘ื™ื˜ื™ื ืขืœ ืขื•ืœื ื‘ื”ื‘ื“ืœ ืงื˜ืŸ.
14:02
They look at the same world and they say...
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ื”ื ืžื‘ื™ื˜ื™ื ืขืœ ืื•ืชื• ืขื•ืœื ื•ืื•ืžืจื™ื...
14:04
(Laughter)
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(ืฆื—ื•ืง)
14:10
That's how the same gene code -- that's why you have 30,000 genes,
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ื›ืš ื’ื ืื•ืชื• ืฆื•ืคืŸ ื’ื ื˜ื™ -- ื–ื• ื”ืกื™ื‘ื” ืฉื™ืฉ ืœื ื• 30,000 ื’ื ื™ื,
14:14
mice have 30,000 genes, husbands have 30,000 genes.
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ืœืขื›ื‘ืจื™ื ื™ืฉ 30,000 ื’ื ื™ื, ืœื‘ืขืœื™ื ื™ืฉ 30,000 ื’ื ื™ื.
14:17
Mice and men are the same. Wives know that, but anyway.
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ืขื›ื‘ืจื™ื ื•ื’ื‘ืจื™ื ื”ื ืื•ืชื• ื“ื‘ืจ. ื ืฉื™ื ื™ื•ื“ืขื•ืช ืืช ื–ื”, ืื‘ืœ ืœื ืžืฉื ื”.
14:21
You can make very small changes in gene code
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ื ื™ืชืŸ ืœืขืฉื•ืช ืฉื™ื ื•ื™ื™ื ื–ืขื™ืจื™ื ื‘ืฆื•ืคืŸ ื’ื ื˜ื™
14:23
and get really different outcomes,
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ื•ืœืงื‘ืœ ืชื•ืฆืื•ืช ื‘ืืžืช ืฉื•ื ื•ืช,
14:27
even with the same string of letters.
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ืืคื™ืœื• ืขื ืื•ืชื” ืžื—ืจื•ื–ืช ืื•ืชื™ื•ืช.
14:31
That's what your genes are doing every day.
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ื–ื” ืžื” ืฉื”ื’ื ื™ื ืฉืœื ื• ืขื•ืฉื™ื ื‘ื›ืœ ื™ื•ื.
14:34
That's why sometimes a person's genes
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ื–ื• ื”ืกื™ื‘ื” ืžื“ื•ืข ืœืคืขืžื™ื ื”ื’ื ื™ื ืฉืœ ืื“ื ืžืกื•ื™ื™ื
14:36
don't have to change a lot to get cancer.
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ืœื ืฆืจื™ื›ื™ื ืœื”ืฉืชื ื•ืช ื‘ื”ืจื‘ื” ื›ื“ื™ ืœืงื‘ืœ ืกืจื˜ืŸ.
14:42
These little chippies, these things are the size of a credit card.
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ื”ืฉื‘ื‘ื™ื ื”ืงื˜ื ื™ื ื”ืืœื”, ื’ื•ื“ืœื ื›ื’ื•ื“ืœ ื›ืจื˜ื™ืก ืืฉืจืื™.
14:47
They will test any one of you for 60,000 genetic conditions.
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ื”ื ืžืกื•ื’ืœื™ื ืœื‘ื“ื•ืง ื›ืœ ืื—ื“ ืžืื™ืชื ื• ืœ-60,000 ืžืฆื‘ื™ื ื’ื ื˜ื™ื™ื ืฉื•ื ื™ื.
14:50
That brings up questions of privacy and insurability
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ื–ื” ืžืขืœื” ืืช ื”ืฉืืœื” ืฉืœ ืคืจื˜ื™ื•ืช ื•ืื‘ื˜ื—ื”
14:53
and all kinds of stuff, but it also allows us to start going after diseases,
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ื•ืขื•ื“ ื›ืœ ืžื™ื ื™ ื“ื‘ืจื™ื, ืื‘ืœ ื–ื” ื’ื ืžืืคืฉืจ ืœื ื• ืœื”ืชื—ื™ืœ ืœืขืงื•ื‘ ืื—ืจ ืžื—ืœื•ืช
14:56
because if you run a person who has leukemia through something like this,
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ืžืคื ื™ ืฉืื ืžืขื‘ื™ืจื™ื ืื“ื ืฉื™ืฉ ืœื• ืกืจื˜ืŸ ื“ื ื“ืจืš ืžืฉื”ื• ื›ื–ื”,
15:00
it turns out that three diseases with
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ืžืชื‘ืจืจ ืฉืฉืœื•ืฉ ืžื—ืœื•ืช ื‘ืขืœื•ืช
15:02
completely similar clinical syndromes
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ืชืกืžื™ื ื™ื ืงืœื™ื ื™ื™ื ื“ื•ืžื™ื ืœื’ืžืจื™
15:06
are completely different diseases.
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ื”ืŸ ืžื—ืœื•ืช ืฉื•ื ื•ืช ืœื’ืžืจื™.
15:08
Because in ALL leukemia, that set of genes over there over-expresses.
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ืžื›ื™ื•ื•ืŸ ืฉื‘ืกืจื˜ืŸ ื”ื“ื ALL, ืื•ืชื” ืงื‘ื•ืฆืช ื’ื ื™ื ืฉื ื‘ืื” ืœื™ื“ื™ ื‘ื™ื˜ื•ื™ ื™ืชืจ.
15:11
In MLL, it's the middle set of genes,
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ื‘-MLL, ื”ืงื‘ื•ืฆื” ื”ืืžืฆืขื™ืช ืฉืœ ื”ื’ื ื™ื.
15:13
and in AML, it's the bottom set of genes.
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ื•ื‘-AML, ื–ื• ื”ืงื‘ื•ืฆื” ื”ืชื—ืชื™ืช ืฉืœ ื’ื ื™ื.
15:15
And if one of those particular things is expressing in your body,
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ื•ืื ืื—ื“ ืžืื•ืชื ื”ื“ื‘ืจื™ื ื”ืžืกื•ื™ื™ืžื™ื ืžื•ืฆืื™ื ืืช ื‘ื™ื˜ื•ื™ื™ื ื‘ื’ื•ืคื ื•,
15:20
then you take Gleevec and you're cured.
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ืื– ืœื•ืงื—ื™ื ื’ืœื™ื•ื•ืง ื•ืžื‘ืจื™ืื™ื.
15:23
If it is not expressing in your body,
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ืื ื–ื” ืœื ื‘ื ืœื™ื“ื™ ื‘ื™ื˜ื•ื™ ื‘ื’ื•ืคื ื•,
15:25
if you don't have one of those types --
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ืื ืื™ืŸ ืœื ื• ืื—ื“ ืžื”ืกื•ื’ื™ื ื”ืœืœื• --
15:27
a particular one of those types -- don't take Gleevec.
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ืื—ื“ ืžืกื•ื™ื™ื ืžื”ืกื•ื’ื™ื ื”ืœืœื• -- ืื™ืŸ ืœื™ื˜ื•ืœ ื’ืœื™ื•ื•ืง.
15:30
It won't do anything for you.
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ื’ืœื™ื•ื•ืง ืœื ื™ืฉืคื™ืข.
15:32
Same thing with Receptin if you've got breast cancer.
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ืื•ืชื• ื”ื“ื‘ืจ ืขื ืจืกืคื˜ื™ืŸ ืื ื™ืฉ ืกืจื˜ืŸ ื”ืฉื“.
15:35
Don't have an HER-2 receptor? Don't take Receptin.
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ืื™ืŸ ืงื•ืœื˜ืŸ HER-2, ืื™ืŸ ืœื™ื˜ื•ืœ ืจืกืคื˜ื™ืŸ.
15:38
Changes the nature of medicine. Changes the predictions of medicine.
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ืžืฉื ื” ืืช ืื•ืคื™ ื”ืชืจื•ืคื”. ืžืฉื ื” ืืช ื”ื—ื–ื•ื™ ืžื”ืชืจื•ืคื”.
15:42
Changes the way medicine works.
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ืžืฉื ื” ืืช ื“ืจืš ืคืขื•ืœืช ื”ืชืจื•ืคื”.
15:44
The greatest repository of knowledge when most of us went to college
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ื”ืžืื’ืจ ื”ื’ื“ื•ืœ ื‘ื™ื•ืชืจ ืฉืœ ื™ื“ืข, ื›ืืฉืจ ืจื•ื‘ื ื• ื”ืœื›ื ื• ืœืื•ื ื™ื‘ืจืกื™ื˜ื”,
15:47
was this thing, and it turns out that
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ื”ื™ื” ื”ื“ื‘ืจ ื”ื–ื”, ื•ืžืชื‘ืจืจ
15:49
this is not so important any more.
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ืฉื”ื•ื ื›ื‘ืจ ืœื ื›ืœ-ื›ืš ื—ืฉื•ื‘.
15:51
The U.S. Library of Congress, in terms of its printed volume of data,
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ืกืคืจื™ื™ืช ื”ืงื•ื ื’ืจืก ื”ืืžืจื™ืงืื™, ื‘ืžื•ื ื—ื™ื ืฉืœ ื›ืžื•ืช ื”ืžื™ื“ืข ื”ืžื•ื“ืคืกืช,
15:55
contains less data than is coming out of a good genomics company
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ืžื›ื™ืœื” ืคื—ื•ืช ื ืชื•ื ื™ื ืžืืฉืจ ื‘ืžื™ื“ืข ื”ื™ื•ืฆื ืžื—ื‘ืจื” ื’ื ื•ืžื™ืช ื™ืขื™ืœื”
15:59
every month on a compound basis.
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ื‘ื›ืœ ื—ื•ื“ืฉ ืขืœ ื‘ืกื™ืก ืชืจื›ื•ื‘ืชื™.
16:02
Let me say that again: A single genomics company
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ืื—ื–ื•ืจ ืขืœ ืžื” ืฉืืžืจืชื™: ื—ื‘ืจื” ื’ื ื•ืžื™ืช ื‘ื•ื“ื“ืช
16:05
generates more data in a month, on a compound basis,
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ืžื™ื™ืฆืจืช ื™ื•ืชืจ ื ืชื•ื ื™ื ื‘ื—ื•ื“ืฉ, ืขืœ ื‘ืกื™ืก ืชืจื›ื•ื‘ืชื™,
16:08
than is in the printed collections of the Library of Congress.
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ืžืืฉืจ ื‘ืื•ืกืคื™ื ื”ืžื•ื“ืคืกื™ื ืฉืœ ืกืคืจื™ื™ืช ื”ืงื•ื ื’ืจืก.
16:12
This is what's been powering the U.S. economy. It's Moore's Law.
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ื–ื” ืžื” ืฉืžืžืจื™ืฅ ืืช ื›ืœื›ืœืช ืืจื”"ื‘. ื–ื”ื• ื—ื•ืง ืžื•ืจ.
16:16
So, all of you know that the price of computers halves every 18 months
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ื›ื•ืœื ื• ื™ื•ื“ืขื™ื ืฉืžื—ื™ืจ ื”ืžื—ืฉื‘ื™ื ื™ื•ืจื“ ื‘ื—ืฆื™ ื›ืœ 18 ื—ื•ื“ืฉื™ื
16:21
and the power doubles, right?
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ื•ืขื•ืฆืžืชื ืžื•ื›ืคืœืช.
16:23
Except that when you lay that side by side with the speed
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ืžืœื‘ื“ ื–ื”, ื›ืืฉืจ ืžืขืžื™ื“ื™ื ืืช ื–ื” ืœืฆื“ ื”ืžื”ื™ืจื•ืช
16:27
with which gene data's being deposited in GenBank,
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ื‘ื” ื ืชื•ื ื™ ื”ื’ื ื•ื ื ืืกืคื™ื ื‘-GenBank,
16:30
Moore's Law is right here: it's the blue line.
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ื—ื•ืง ืžื•ืจ ืžื•ื›ื— ื›ืืŸ ื›ื ื›ื•ืŸ: ื–ื”ื• ื”ืงื• ื”ื›ื—ื•ืœ.
16:35
This is on a log scale, and that's what superexponential growth means.
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ื–ื” ืขืœ ืฆื™ืจ ืœื•ื’ืจื™ืชืžื™, ื•ื–ื• ื”ืžืฉืžืขื•ืช ืฉืœ ื’ื™ื“ื•ืœ ืขืœ-ืžืขืจื™ื›ื™ (ืกื•ืคืจ-ืืงืกืคื•ื ื ืฆื™ืืœื™).
16:39
This is going to push computers to have to grow faster
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ื–ื” ื”ื•ืœืš ืœื“ื—ื•ืฃ ืืช ื”ืžื—ืฉื‘ื™ื ืืœ ืขื‘ืจ ื’ื™ื“ื•ืœ ื™ื•ืชืจ ืžื”ื™ืจ
16:43
than they've been growing, because so far,
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ืžืืฉืจ ืงืฆื‘ ื’ื™ื“ื•ืœื ื ื›ื•ืŸ ืœื”ื™ื•ื.
16:45
there haven't been applications that have been required
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ืœื ื”ื™ื• ื™ื™ืฉื•ืžื™ื ืฉื“ืจืฉื•
16:48
that need to go faster than Moore's Law. This stuff does.
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ืžื”ื™ืจื•ืช ื™ื•ืชืจ ื’ื‘ื•ื”ื” ืžืืฉืจ ื—ื•ืง ืžื•ืจ. ื”ื“ื‘ืจ ื”ื–ื” ื›ืŸ ื“ื•ืจืฉ.
16:51
And here's an interesting map.
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ื•ื”ื ื” ืžืคื” ืžืขื ื™ื™ื ืช.
16:53
This is a map which was finished at the Harvard Business School.
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ืžืคื” ื–ื• ื”ื•ื›ื ื” ื‘ื‘ื™ืช-ืกืคืจ ืœืขืกืงื™ื ื‘ื”ืจื•ื•ืจื“.
16:57
One of the really interesting questions is, if all this data's free,
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ืื—ืช ื”ืฉืืœื•ืช ื”ื™ื•ืชืจ ืžืขื ื™ื™ื ื•ืช ื”ื™ื, ืื ื›ืœ ื”ืžื™ื“ืข ื”ื–ื” ื—ื•ืคืฉื™,
17:00
who's using it? This is the greatest public library in the world.
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ืžื™ ืžืฉืชืžืฉ ื‘ื•? ื–ื•ื”ื™ ื”ืกืคืจื™ื” ื”ืฆื™ื‘ื•ืจื™ืช ื”ื’ื“ื•ืœื” ื‘ื™ื•ืชืจ ื‘ืขื•ืœื.
17:04
Well, it turns out that there's about 27 trillion bits
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ืื– ืžืกืชื‘ืจ ืฉื›-27 ื˜ืจื™ืœื™ื•ืŸ ื‘ื™ื˜ื™ื
17:07
moving inside from the United States to the United States;
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ื ืขื™ื ืืœ ืชื•ืš ืืจื”"ื‘ ื•ืžืืจื”"ื‘;
17:10
about 4.6 trillion is going over to those European countries;
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ื›-4.6 ื˜ืจื™ืœื™ื•ืŸ ืขื•ื‘ืจื™ื ืืœ ืžื“ื™ื ื•ืช ืื™ืจื•ืคื”;
17:14
about 5.5's going to Japan; there's almost no communication
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ื›-5.5 ืขื•ื‘ืจื™ื ืœื™ืคืŸ; ืื™ืŸ ื›ืžืขื˜ ืชืงืฉื•ืจืช
17:17
between Japan, and nobody else is literate in this stuff.
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ื‘ืชื•ืš ื™ืคืŸ, ื•ืืฃ ืื—ื“ ืื—ืจ ืื™ื ื• ื™ื•ื“ืข ืœืงืจื•ื ื—ื•ืžืจ ื–ื”.
17:21
It's free. No one's reading it. They're focusing on the war;
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ื”ื•ื ื—ื™ื ื. ืื‘ืœ ืืฃ ืื—ื“ ืœื ืงื•ืจื ืื•ืชื•. ื”ื ืžืชืžืงื“ื™ื ื‘ืžืœื—ืžื”;
17:26
they're focusing on Bush; they're not interested in life.
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ื”ื ืžืชืžืงื“ื™ื ื‘ื‘ื•ืฉ; ื”ื ืœื ืžืชืขื ื™ื™ื ื™ื ื‘ื—ื™ื™ื.
17:29
So, this is what a new map of the world looks like.
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ืื– ื›ื›ื” ื ืจืื™ืช ื”ืžืคื” ื”ื—ื“ืฉื” ืฉืœ ื”ืขื•ืœื.
17:32
That is the genomically literate world. And that is a problem.
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ื–ื”ื• ื”ืขื•ืœื ืฉื™ื•ื“ืข ืœืงืจื•ื ืžื™ื“ืข ื’ื ื˜ื™. ื•ื–ื• ื‘ืขื™ื”.
17:38
In fact, it's not a genomically literate world.
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ืœืžืขืฉื”, ื–ื”ื• ืื™ื ื• ืขื•ืœื ืฉื™ื•ื“ืข ืœืงืจื•ื ืžื™ื“ืข ื’ื ื˜ื™.
17:40
You can break this out by states.
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ื ื™ืชืŸ ืœืคืจืง ืืช ื–ื” ืœืคื™ ืžื“ื™ื ื•ืช.
17:42
And you can watch states rise and fall depending on
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ื•ื ื™ืชืŸ ืœืจืื•ืช ืขืœื™ื™ืชืŸ ื•ื ืคื™ืœืชืŸ ืฉืœ ืžื“ื™ื ื•ืช ืœืคื™
17:44
their ability to speak a language of life,
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ื™ื›ื•ืœืชืŸ ืœื“ื‘ืจ ืืช ืฉืคืช ื”ื—ื™ื™ื,
17:46
and you can watch New York fall off a cliff,
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ื•ื ื™ืชืŸ ืœืจืื•ืช ืืช ื ื™ื•-ื™ื•ืจืง ื ื•ืคืœืช ืœืชื”ื•ื,
17:48
and you can watch New Jersey fall off a cliff,
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ื•ื ื™ืชืŸ ืœืจืื•ืช ืืช ื ื™ื•-ื’'ืจื–ื™ ื ื•ืคืœืช ืœืชื”ื•ื,
17:50
and you can watch the rise of the new empires of intelligence.
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ื•ื ื™ืชืŸ ืœืจืื•ืช ืขืœื™ื™ืชืŸ ืฉืœ ืื™ืžืคืจื™ื•ืช ืื™ื ื˜ืœื™ื’ื ืฆื™ื” ื—ื“ืฉื•ืช.
17:54
And you can break it out by counties, because it's specific counties.
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ื•ื ื™ืชืŸ ืœืคืจืง ืืช ื–ื” ืœืคื™ ืžื—ื•ื–ื•ืช, ื‘ื’ืœืœ ืฉืืœื• ืžื—ื•ื–ื•ืช ืžืกื•ื™ื™ืžื™ื.
17:57
And if you want to get more specific,
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ื•ืื ืจื•ืฆื™ื ืœื”ื™ื•ืช ื™ื•ืชืจ ืกืคืฆื™ืคื™ื™ื,
17:59
it's actually specific zip codes.
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ื–ื” ื‘ืขืฆื ืžืกืคืจื™ ืžื™ืงื•ื“ ืžืกื•ื™ื™ืžื™ื.
18:01
(Laughter)
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(ืฆื—ื•ืง)
18:03
So, you want to know where life is happening?
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ืื– ืื ื• ืจื•ืฆื™ื ืœื“ืขืช ื”ื™ื›ืŸ ื”ื—ื™ื™ื ืžืชืจื—ืฉื™ื?
18:06
Well, in Southern California it's happening in 92121. And that's it.
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ืื–, ื‘ืงืœื™ืคื•ืจื ื™ื” ื”ื“ืจื•ืžื™ืช ื–ื” ืžืชืจื—ืฉ ื‘-92121. ื•ื–ื” ื”ื›ืœ.
18:12
And that's the triangle between Salk, Scripps, UCSD,
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ื•ื–ื”ื• ื”ืžืฉื•ืœืฉ ื‘ื™ืŸ ืกืืœืง, ืกืงืจื™ืคืก, ื™ื•.ืกื™.ืืก.ื“ื™.,
18:17
and it's called Torrey Pines Road.
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ื•ื”ื•ื ื ืงืจื ืจื—ื•ื‘ ื˜ื•ืจื™ ืคื™ื™ื ืก.
18:19
That means you don't need to be a big nation to be successful;
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ื•ื–ื” ืื•ืžืจ ืฉืื™ืŸ ื”ื›ืจื— ืœื”ื™ื•ืช ืื•ืžื” ื’ื“ื•ืœื” ื›ื“ื™ ืœื”ืฆืœื™ื—;
18:22
it means you don't need a lot of people to be successful;
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ื–ื” ืื•ืžืจ ืฉืื™ืŸ ืฆื•ืจืš ื‘ื”ืจื‘ื” ืื ืฉื™ื ื›ื“ื™ ืœื”ืฆืœื™ื—;
18:24
and it means you can move most of the wealth of a country
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ื•ื–ื” ืื•ืžืจ ืฉื ื™ืชืŸ ืœืฉื ืข ืืช ืจื•ื‘ ื”ืขื•ืฉืจ ืฉืœ ืžื“ื™ื ื”
18:27
in about three or four carefully picked 747s.
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ื‘ื›ืฉืœื•ืฉื” ืื• ืืจื‘ืขื” ืžื˜ื•ืกื™ ื’'ืžื‘ื• 747 ืฉื ื‘ื—ืจื• ื‘ืงืคื™ื“ื”.
18:31
Same thing in Massachusetts. Looks more spread out but --
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ืื•ืชื• ื”ื“ื‘ืจ ื‘ืžืกืฆ'ื•ืกื˜ืก. ื ืจืื” ื™ื•ืชืจ ืžืคื•ื–ืจ ืื‘ืœ --
18:35
oh, by the way, the ones that are the same color are contiguous.
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ื•ื“ืจืš ืื’ื‘, ืืœื” ืขื ืื•ืชื• ืฆื‘ืข ื’ื•ื‘ืœื™ื ื–ื” ื‘ื–ื”.
18:39
What's the net effect of this?
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ืžื”ื™ ื”ื”ืฉืคืขื” ื”ืกื•ืคื™ืช ืฉืœ ื›ืœ ื–ื”?
18:41
In an agricultural society, the difference between
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ื‘ื—ื‘ืจื” ื—ืงืœืื™ืช, ื”ื”ื‘ื“ืœ ื‘ื™ืŸ
18:43
the richest and the poorest,
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ื”ืขืฉื™ืจื™ื ื‘ื™ื•ืชืจ ืœืขื ื™ื™ื ื‘ื™ื•ืชืจ,
18:45
the most productive and the least productive, was five to one. Why?
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ื”ื™ืฆืจื ื™ื™ื ื‘ื™ื•ืชืจ ืœื”ื›ื™ ืคื—ื•ืช ื™ืฆืจื ื™ื™ื, ื”ื™ื” 5 ืœ-1. ืžื“ื•ืข?
18:49
Because in agriculture, if you had 10 kids
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ืžื›ื™ื•ื•ืŸ ืฉื‘ื—ืงืœืื•ืช, ืื ื”ื™ื• ืœืš 10 ื™ืœื“ื™ื
18:51
and you grow up a little bit earlier and you work a little bit harder,
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ื•ืงืžืช ืงืฆืช ื™ื•ืชืจ ืžื•ืงื“ื ื•ืขื‘ื“ืช ืžืขื˜ ื™ื•ืชืจ ืงืฉื”,
18:54
you could produce about five times more wealth, on average,
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ื™ื›ืœืช ืœื™ื™ืฆืจ ืขื•ืฉืจ ื’ื“ื•ืœ ืคื™-5, ื‘ืžืžื•ืฆืข,
18:56
than your neighbor.
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ืœืขื•ืžืช ืฉื›ื ืš.
18:58
In a knowledge society, that number is now 427 to 1.
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ื‘ื—ื‘ืจืช ื”ื™ื“ืข, ื”ืžืกืคืจ ื”ื–ื” ื”ื•ื 427 ืœ-1.
19:02
It really matters if you're literate, not just in reading and writing
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ื–ื” ื‘ืืžืช ืžืฉื ื” ืื ืืชื” ื™ื•ื“ืข ืงืจื•ื ื•ื›ืชื•ื‘, ืœื ืจืง ืงืจื™ืื” ื•ื›ืชื™ื‘ื”
19:06
in English and French and German,
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ื‘ืื ื’ืœื™ืช ื•ืฆืจืคืชื™ืช ื•ื’ืจืžื ื™ืช,
19:08
but in Microsoft and Linux and Apple.
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ืื‘ืœ ื’ื ื‘ืžื™ืงืจื•ืกื•ืคื˜ ื•ืœื™ื ื•ืงืก ื•ืืคืœ.
19:11
And very soon it's going to matter if you're literate in life code.
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ื•ื‘ืงืจื•ื‘ ืžืื•ื“ ื–ื” ื™ื”ื™ื” ืงื•ื‘ืข ืื ืืชื” ื™ื•ื“ืข ืœืงืจื•ื ืืช ืฆื•ืคืŸ ื”ื—ื™ื™ื.
19:15
So, if there is something you should fear,
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ืœื›ืŸ, ืื ืขืœื™ื ื• ืœื—ืฉื•ืฉ ืžืžืฉื”ื•,
19:17
it's that you're not keeping your eye on the ball.
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ื–ื” ื–ื” ืฉืื ื—ื ื• ืœื ื ืชืขื“ื›ืŸ.
19:20
Because it really matters who speaks life.
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ืžืคื ื™ ืฉื–ื” ื‘ืืžืช ืงื•ื‘ืข ืžื™ ืžื“ื‘ืจ ื—ื™ื™ื.
19:23
That's why nations rise and fall.
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ื–ื• ื”ืกื™ื‘ื” ืžื“ื•ืข ืื•ืžื•ืช ืงืžื•ืช ื•ื ื•ืคืœื•ืช.
19:26
And it turns out that if you went back to the 1870s,
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ื•ืžืกืชื‘ืจ ืฉืื ื ื—ื–ื•ืจ ืœ-1870,
19:29
the most productive nation on earth was Australia, per person.
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ื”ืื•ืžื” ื”ืคื•ืจื™ื” ื‘ื™ื•ืชืจ ืขืœ ื›ื“ื•ืจ-ื”ืืจืฅ ื”ื™ืชื” ืื•ืกื˜ืจืœื™ื”, ืคืจ ืื“ื.
19:32
And New Zealand was way up there. And then the U.S. came in about 1950,
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ื•ื ื™ื•-ื–ื™ืœื ื“ ื”ื™ืชื” ื”ืจื—ืง ืฉื ืœืžืขืœื”. ื•ืื– ื”ื’ื™ืขื” ืืจื”"ื‘ ื‘ืขืจืš ื‘-1950,
19:35
and then Switzerland about 1973, and then the U.S. got back on top --
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ื•ืฉื•ื•ื™ืฅ ื‘ืขืจืš ื‘-1973, ื•ืื– ืืจื”"ื‘ ื—ื–ืจื” ืœืคืกื’ื” --
19:39
beat up their chocolates and cuckoo clocks.
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ื”ื™ื›ืชื” ืืช ื”ืฉื•ืงื•ืœื“ื™ื ื•ืฉืขื•ื ื™ ื”ืงื•ืงื™ื” ืฉืœื”ื.
19:43
And today, of course, you all know that the most productive nation
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ื•ื”ื™ื•ื, ื›ืžื•ื‘ืŸ, ื›ื•ืœื ื• ื™ื•ื“ืขื™ื ืฉื”ืžื“ื™ื ื” ื”ืคื•ืจื™ื” ื‘ื™ื•ืชืจ
19:46
on earth is Luxembourg, producing about one third more wealth
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ืขืœ ื›ื“ื•ืจ-ื”ืืจืฅ ื”ื™ื ืœื•ืงืกืžื‘ื•ืจื’, ื”ืžื™ื™ืฆืจืช ืขื•ืฉืจ ื™ื•ืชืจ ื’ื“ื•ืœ ื‘ืฉืœื™ืฉ
19:49
per person per year than America.
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ืžืืฉืจ ืืจื”"ื‘ ืžื™ื™ืฆืจืช, ืœื›ืœ ืื“ื ื‘ื›ืœ ืฉื ื”.
19:52
Tiny landlocked state. No oil. No diamonds. No natural resources.
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ืžื“ื™ื ื” ื–ืขื™ืจื” ื”ืกื’ื•ืจื” ืžื›ืœ ื”ื›ื™ื•ื•ื ื™ื ื‘ื™ื‘ืฉื”. ืื™ืŸ ื ืคื˜, ืื™ืŸ ื™ื”ืœื•ืžื™ื, ืื™ืŸ ืžืฉืื‘ื™ื ื˜ื‘ืขื™ื™ื.
19:56
Just smart people moving bits. Different rules.
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ืจืง ืื ืฉื™ื ืคื™ืงื—ื™ื ื”ืžืฉื ืขื™ื ื‘ื™ื˜ื™ื. ื›ืœืœื™ื ืื—ืจื™ื.
20:02
Here's differential productivity rates.
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ืœื”ืœืŸ ืงืฆื‘ื™ ืชืคื•ืงื” ื™ื—ืกื™ื™ื.
20:06
Here's how many people it takes to produce a single U.S. patent.
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ื›ืืŸ ื–ื” ื›ืžื” ืื ืฉื™ื ื“ืจื•ืฉื™ื ื›ื“ื™ ืœื™ืฆื•ืจ ืคื˜ื ื˜ ืืžืจื™ืงืื™ ืื—ื“.
20:09
So, about 3,000 Americans, 6,000 Koreans, 14,000 Brits,
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ื–ื” ื›-3,000 ืืžืจื™ืงืื™ื, 6,000 ืงื•ืจื™ืื ื™ื, 14,000 ื‘ืจื™ื˜ื™ื,
20:13
790,000 Argentines. You want to know why Argentina's crashing?
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790,000 ืืจื’ื ื˜ื™ื ืื™ื. ืืชื ืจื•ืฆื™ื ืœื“ืขืช ืžื“ื•ืข ืืจื’ื ื˜ื™ื ื” ืžืชืจืกืงืช?
20:16
It's got nothing to do with inflation.
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ืื™ืŸ ืœื–ื” ืฉื•ื ืงืฉืจ ืขื ืื™ื ืคืœืฆื™ื”.
20:18
It's got nothing to do with privatization.
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ืื™ืŸ ืœื–ื” ืฉื•ื ืงืฉืจ ืขื ื”ืคืจื˜ื”.
20:20
You can take a Harvard-educated Ivy League economist,
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ืืชื ื™ื›ื•ืœื™ื ืœืงื—ืช ื›ืœื›ืœืŸ ื‘ื•ื’ืจ ื”ืจื•ื•ืจื“ ืžืœื™ื’ืช ื”ืงื™ืกื•ืก,
20:24
stick him in charge of Argentina. He still crashes the country
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ืชืชืงืขื• ืื•ืชื• ืœื”ื™ื•ืช ืื—ืจืื™ ืขืœ ืืจื’ื ื˜ื™ื ื”. ื”ื•ื ืขื“ื™ื™ืŸ ื™ืจืกืง ืืช ื”ืžื“ื™ื ื”
20:27
because he doesn't understand how the rules have changed.
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ืžื›ื™ื•ื•ืŸ ืฉื”ื•ื ืœื ื™ื‘ื™ืŸ ืื™ืš ื”ื—ื•ืงื™ื ื”ืฉืชื ื•.
20:30
Oh, yeah, and it takes about 5.6 million Indians.
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ืื”, ื›ืŸ, ื•ื–ื” ื›-5.6 ืžื™ืœื™ื•ืŸ ื”ื•ื“ื™ื.
20:33
Well, watch what happens to India.
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ื•ื‘ื›ืŸ, ืชืฉื™ืžื• ืœื‘ ืžื” ืงืจื” ืขื ื”ื•ื“ื•.
20:35
India and China used to be 40 percent of the global economy
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ื”ื•ื“ื• ื•ืกื™ืŸ ื”ื™ื• ืคืขื 40 ืื—ื•ื– ืžื”ื›ืœื›ืœื” ื”ืขื•ืœืžื™ืช
20:38
just at the Industrial Revolution, and they are now about 4.8 percent.
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ืžืžืฉ ื‘ืชื—ื™ืœืช ื”ืžื”ืคื›ื” ื”ืชืขืฉื™ื™ืชื™ืช, ื•ื›ืขืช ื”ืŸ ื›-4.8 ืื—ื•ื–.
20:43
Two billion people. One third of the global population producing 5 percent of the wealth
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ืฉื ื™ ืžื™ืœื™ืืจื“ ืื ืฉื™ื. ืฉืœื™ืฉ ืžื”ืื•ื›ืœื•ืกื™ื” ื”ืขื•ืœืžื™ืช ื”ืžื™ื™ืฆืจื™ื 5 ืื—ื•ื– ืžื”ืขื•ืฉืจ
20:47
because they didn't get this change,
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ืžื›ื™ื•ื•ืŸ ืฉื”ื ืœื ืขื‘ืจื• ืืช ื”ืฉื™ื ื•ื™,
20:50
because they kept treating their people like serfs
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ืžื›ื™ื•ื•ืŸ ืฉื”ื ื”ืžืฉื™ื›ื• ืœื”ืชื™ื—ืก ืœืื ืฉื™ื ื›ืืœ ืฆืžื™ืชื™ื
20:52
instead of like shareholders of a common project.
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ื‘ืžืงื•ื ื›ืืœ ืžื—ื–ื™ืงื™ ืžื ื™ื•ืช ืฉืœ ืžืฉื™ืžื” ืžืฉื•ืชืคืช.
20:56
They didn't keep the people who were educated.
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ื”ื ืœื ืฉืžืจื• ืืฆืœื ืืช ื”ืื ืฉื™ื ื”ืžืฉื›ื™ืœื™ื.
20:59
They didn't foment the businesses. They didn't do the IPOs.
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ื”ื ืœื ื˜ื™ืคื—ื• ืืช ื”ืขืกืงื™ื, ืœื ืขืฉื• ื”ื ืคืงื•ืช ืœื‘ื•ืจืกื”.
21:02
Silicon Valley did. And that's why they say
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ืขืžืง ื”ืกื™ืœื™ืงื•ืŸ ืขืฉื”. ื•ืœื›ืŸ ื”ื ืื•ืžืจื™ื ืฉืขืžืง ื”ืกื™ืœื™ืงื•ืŸ ืฉื•ืื‘
21:06
that Silicon Valley has been powered by ICs.
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ืืช ื›ื•ื—ื• ืž-ICs (ืžืขื’ืœื™ื ืžืฉื•ืœื‘ื™ื).
21:09
Not integrated circuits: Indians and Chinese.
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ืœื, ืœื ืžืขื’ืœื™ื ืžืฉื•ืœื‘ื™ื, ืืœื ื”ื•ื“ื™ื ื•ืกื™ื ื™ื (Indians and Chinese).
21:12
(Laughter)
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(ืฆื—ื•ืง)
21:16
Here's what's happening in the world.
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ื”ื ื” ืžื” ืฉืงื•ืจื” ื‘ืขื•ืœื.
21:18
It turns out that if you'd gone to the U.N. in 1950,
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ืžืชื‘ืจืจ ืฉืื ื”ื™ื™ื ื• ื”ื•ืœื›ื™ื ืœืื•"ื ื‘-1950,
21:21
when it was founded, there were 50 countries in this world.
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ื›ืืฉืจ ื”ื•ื ื ื•ืกื“, ื”ื™ื• 50 ืžื“ื™ื ื•ืช ื‘ืขื•ืœื.
21:23
It turns out there's now about 192.
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ืžืชื‘ืจืจ ืฉื™ืฉ ื”ื™ื•ื ื›-192.
21:26
Country after country is splitting, seceding, succeeding, failing --
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ืžื“ื™ื ื” ืื—ืจ ืžื“ื™ื ื” ืžืชืคืฆืœืช, ืžืชื ืชืงืช, ืžืฆืœื™ื—ื”, ื ื›ืฉืœืช.
21:31
and it's all getting very fragmented. And this has not stopped.
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ื•ื”ื›ืœ ื ืขืฉื” ืจืกื™ืกื™ื, ืจืกื™ืกื™ื. ื•ื–ื” ืœื ืขื•ืฆืจ.
21:36
In the 1990s, these are sovereign states
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ื‘ืฉื ื•ืช ื”-90, ื”ื™ื• ืืœื” ืžื“ื™ื ื•ืช ืจื™ื‘ื•ื ื™ื•ืช
21:39
that did not exist before 1990.
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ืฉืœื ื”ื™ื• ืงื™ื™ืžื•ืช ืœืคื ื™ 1990.
21:41
And this doesn't include fusions or name changes or changes in flags.
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ื•ื–ื” ืœื ื›ื•ืœืœ ืื™ื—ื•ื“ื™ื ืื• ืฉื™ื ื•ื™ื™ ืฉืžื•ืช ืื• ื”ื—ืœืคืช ื“ื’ืœื™ื.
21:46
We're generating about 3.12 states per year.
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ืื ื• ืžื™ื™ืฆืจื™ื ื›-3.12 ืžื“ื™ื ื•ืช ื›ืœ ืฉื ื”.
21:49
People are taking control of their own states,
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ืื ืฉื™ื ื ื•ื˜ืœื™ื ืืช ื”ืฉืœื™ื˜ื” ืขืœ ืžื“ื™ื ื•ืชื™ื”ื,
21:52
sometimes for the better and sometimes for the worse.
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ืœืคืขืžื™ื ื–ื” ืœื˜ื•ื‘ื” ื•ืœืคืขืžื™ื ืœืจืขื”.
21:55
And the really interesting thing is,
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ื•ื”ื“ื‘ืจ ื”ื‘ืืžืช ืžืขื ื™ื™ืŸ ื”ื•ื
21:57
you and your kids are empowered to build great empires,
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ืฉืืชื ื•ื™ืœื“ื™ื›ื, ื‘ื™ื›ื•ืœืชื›ื ืœื‘ื ื•ืช ืžืขืฆืžื•ืช ื’ื“ื•ืœื•ืช,
21:59
and you don't need a lot to do it.
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ื•ืื™ื ื›ื ืฆืจื™ื›ื™ื ืœืขืฉื•ืช ื”ืจื‘ื” ืœืฉื ื›ืš.
22:01
(Music)
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(ืžื•ื–ื™ืงื”)
22:03
And, given that the music is over, I was going to talk
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ื•ืžืชื•ืš ื”ื ื—ื” ืฉื”ืžื•ื–ื™ืงื” ื”ืกืชื™ื™ืžื”, ืขืžื“ืชื™ ืœื“ื‘ืจ
22:06
about how you can use this to generate a lot of wealth,
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ืขืœ ื›ื™ืฆื“ ืืชื ื™ื›ื•ืœื™ื ืœื”ืฉืชืžืฉ ื‘ื–ื” ื›ื“ื™ ืœื™ื™ืฆืจ ืขื•ืฉืจ ื’ื“ื•ืœ,
22:09
and how code works.
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ื•ื›ื™ืฆื“ ื”ืฆื•ืคืŸ ืขื•ื‘ื“.
22:11
Moderator: Two minutes.
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(ืื—ืจืื™: ืฉืชื™ ื“ืงื•ืช.)
22:12
(Laughter)
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(ืฆื—ื•ืง)
22:14
Juan Enriquez: No, I'm going to stop there and we'll do it next year
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ืœื, ืื ื™ ืืคืกื™ืง ื›ืืŸ ื•ืืขืฉื” ื–ืืช ื‘ืฉื ื” ื”ื‘ืื”
22:18
because I don't want to take any of Laurie's time.
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ื›ื™ ืื™ื ื™ ืจื•ืฆื” ืœืงื—ืช ืžื–ืžื ื” ืฉืœ ืœื•ืจื™.
22:21
But thank you very much.
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ืื‘ืœ ืชื•ื“ื” ืจื‘ื” ืœื›ื.
ืขืœ ืืชืจ ื–ื”

ืืชืจ ื–ื” ื™ืฆื™ื’ ื‘ืคื ื™ื›ื ืกืจื˜ื•ื ื™ YouTube ื”ืžื•ืขื™ืœื™ื ืœืœื™ืžื•ื“ ืื ื’ืœื™ืช. ืชื•ื›ืœื• ืœืจืื•ืช ืฉื™ืขื•ืจื™ ืื ื’ืœื™ืช ื”ืžื•ืขื‘ืจื™ื ืขืœ ื™ื“ื™ ืžื•ืจื™ื ืžื”ืฉื•ืจื” ื”ืจืืฉื•ื ื” ืžืจื—ื‘ื™ ื”ืขื•ืœื. ืœื—ืฅ ืคืขืžื™ื™ื ืขืœ ื”ื›ืชื•ื‘ื™ื•ืช ื‘ืื ื’ืœื™ืช ื”ืžื•ืฆื’ื•ืช ื‘ื›ืœ ื“ืฃ ื•ื™ื“ืื• ื›ื“ื™ ืœื”ืคืขื™ืœ ืืช ื”ืกืจื˜ื•ืŸ ืžืฉื. ื”ื›ืชื•ื‘ื™ื•ืช ื’ื•ืœืœื•ืช ื‘ืกื ื›ืจื•ืŸ ืขื ื”ืคืขืœืช ื”ื•ื•ื™ื“ืื•. ืื ื™ืฉ ืœืš ื”ืขืจื•ืช ืื• ื‘ืงืฉื•ืช, ืื ื ืฆื•ืจ ืื™ืชื ื• ืงืฉืจ ื‘ืืžืฆืขื•ืช ื˜ื•ืคืก ื™ืฆื™ืจืช ืงืฉืจ ื–ื”.

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