0:00:01.134,0:00:03.524
So let me with start with Roy Amara.

0:00:04.350,0:00:08.561
Roy's argument is that most new[br]technologies tend to be overestimated

0:00:08.585,0:00:10.653
in their impact to begin with,

0:00:10.677,0:00:13.079
and then they get underestimated[br]in the long term

0:00:13.103,0:00:14.467
because we get used to them.

0:00:14.491,0:00:16.687
These really are days[br]of miracle and wonder.

0:00:17.433,0:00:19.814
You remember that wonderful[br]song by Paul Simon?

0:00:20.365,0:00:21.703
There were two lines in it.

0:00:21.727,0:00:25.414
So what was it that was considered[br]miraculous back then?

0:00:26.393,0:00:28.465
Slowing down things -- slow motion --

0:00:29.371,0:00:31.099
and the long-distance call.

0:00:31.941,0:00:34.800
Because, of course, you used[br]to get interrupted by operators

0:00:34.824,0:00:37.821
who'd tell you, "Long distance calling.[br]Do you want to hang up?"

0:00:37.845,0:00:40.547
And now we think nothing of calling[br]all over the world.

0:00:41.040,0:00:43.670
Well, something similar may be happening

0:00:43.694,0:00:45.766
with reading and programming life.

0:00:46.636,0:00:48.364
But before I unpack that,

0:00:49.069,0:00:51.753
let's just talk about telescopes.

0:00:52.798,0:00:57.109
Telescopes were overestimated[br]originally in their impact.

0:00:57.133,0:00:59.302
This is one of Galileo's early models.

0:01:00.090,0:01:03.449
People thought it was just[br]going to ruin all religion.

0:01:03.473,0:01:04.623
(Laughter)

0:01:06.862,0:01:09.576
So we're not paying that much[br]attention to telescopes.

0:01:10.628,0:01:14.710
But, of course, telescopes launched[br]10 years ago, as you just heard,

0:01:14.734,0:01:17.725
could take this Volkswagen,[br]fly it to the moon,

0:01:17.749,0:01:23.605
and you could see the lights[br]on that Volkswagen light up on the moon.

0:01:24.624,0:01:27.886
And that's the kind of resolution power[br]that allowed you to see

0:01:28.592,0:01:32.196
little specks of dust[br]floating around distant suns.

0:01:32.220,0:01:35.684
Imagine for a second that this[br]was a sun a billion light years away,

0:01:36.310,0:01:39.237
and you had a little speck of dust[br]that came in front of it.

0:01:39.566,0:01:42.067
That's what detecting[br]an exoplanet is like.

0:01:43.268,0:01:47.058
And the cool thing is, the telescopes[br]that are now being launched

0:01:48.138,0:01:51.143
would allow you to see[br]a single candle lit on the moon.

0:01:52.279,0:01:55.107
And if you separated it by one plate,

0:01:55.131,0:01:57.925
you could see two candles[br]separately at that distance.

0:01:59.124,0:02:01.937
And that's the kind[br]of resolution that you need

0:02:01.961,0:02:04.429
to begin to image[br]that little speck of dust

0:02:04.453,0:02:05.739
as it comes around the sun

0:02:05.763,0:02:07.812
and see if it has a blue-green signature.

0:02:09.120,0:02:11.191
And if it does have[br]a blue-green signature,

0:02:11.215,0:02:13.435
it means that life[br]is common in the universe.

0:02:13.459,0:02:17.655
The first time you ever see a blue-green[br]signature on a distant planet,

0:02:17.679,0:02:19.672
it means there's photosynthesis there,

0:02:19.696,0:02:20.977
there's water there,

0:02:21.001,0:02:24.873
and the chances that you saw[br]the only other planet with photosynthesis

0:02:24.897,0:02:26.260
are about zero.

0:02:27.108,0:02:29.004
And that's a calendar-changing event.

0:02:29.670,0:02:32.422
There's a before and after[br]we were alone in the universe:

0:02:32.446,0:02:34.916
forget about the discovery[br]of whatever continent.

0:02:36.751,0:02:38.331
So as you're thinking about this,

0:02:38.355,0:02:41.257
we're now beginning[br]to be able to image most of the universe.

0:02:41.281,0:02:43.535
And that is a time of miracle and wonder.

0:02:43.559,0:02:45.911
And we kind of take that for granted.

0:02:47.562,0:02:49.477
Something similar is happening in life.

0:02:49.501,0:02:52.539
So we're hearing about life[br]in these little bits and pieces.

0:02:52.563,0:02:55.221
We hear about CRISPR,[br]and we hear about this technology,

0:02:55.245,0:02:56.911
and we hear about this technology.

0:02:56.935,0:03:00.323
But the bottom line on life[br]is that life turns out to be code.

0:03:01.900,0:03:05.850
And life as code is a really[br]important concept because it means,

0:03:05.874,0:03:09.084
just in the same way[br]as you can write a sentence

0:03:09.108,0:03:12.226
in English or in French or Chinese,

0:03:13.146,0:03:16.052
just in the same way[br]as you can copy a sentence,

0:03:16.076,0:03:18.602
just in the same way[br]as you can edit a sentence,

0:03:18.626,0:03:20.976
just in the same way[br]as you can print a sentence,

0:03:21.000,0:03:23.719
you're beginning to be able[br]to do that with life.

0:03:25.237,0:03:28.748
It means that we're beginning[br]to learn how to read this language.

0:03:28.772,0:03:32.008
And this, of course, is the language[br]that is used by this orange.

0:03:32.702,0:03:34.498
So how does this orange execute code?

0:03:34.522,0:03:37.230
It doesn't do it in ones and zeroes[br]like a computer does.

0:03:37.254,0:03:39.139
It sits on a tree, and one day it does:

0:03:39.163,0:03:40.313
plop!

0:03:40.819,0:03:42.624
And that means: execute.

0:03:43.149,0:03:46.421
AATCAAG: make me a little root.

0:03:47.057,0:03:49.559
TCGACC: make me a little stem.

0:03:49.583,0:03:53.021
GAC: make me some leaves.[br]AGC: make me some flowers.

0:03:53.045,0:03:55.902
And then GCAA: make me some more oranges.

0:03:56.984,0:04:01.057
If I edit a sentence in English[br]on a word processor,

0:04:03.153,0:04:06.594
then what happens is you can go[br]from this word to that word.

0:04:08.134,0:04:10.270
If I edit something in this orange

0:04:10.294,0:04:15.277
and put in GCAAC, using CRISPR[br]or something else that you've heard of,

0:04:16.261,0:04:18.058
then this orange becomes a lemon,

0:04:18.957,0:04:20.505
or it becomes a grapefruit,

0:04:20.529,0:04:22.186
or it becomes a tangerine.

0:04:23.102,0:04:25.120
And if I edit one in a thousand letters,

0:04:25.144,0:04:27.504
you become the person[br]sitting next to you today.

0:04:28.757,0:04:30.277
Be more careful where you sit.

0:04:30.301,0:04:31.490
(Laughter)

0:04:33.014,0:04:36.489
What's happening on this stuff[br]is it was really expensive to begin with.

0:04:36.513,0:04:38.208
It was like long-distance calls.

0:04:39.399,0:04:43.005
But the cost of this is dropping[br]50 percent faster than Moore's law.

0:04:43.909,0:04:47.741
The first $200 full genome[br]was announced yesterday by Veritas.

0:04:48.494,0:04:50.624
And so as you're looking at these systems,

0:04:50.648,0:04:54.450
it doesn't matter, it doesn't matter,[br]it doesn't matter, and then it does.

0:04:54.474,0:04:57.879
So let me just give you[br]the map view of this stuff.

0:04:58.973,0:05:01.532
This is a big discovery.

0:05:01.556,0:05:03.479
There's 23 chromosomes.

0:05:03.503,0:05:04.731
Cool.

0:05:05.287,0:05:08.966
Let's now start using a telescope version,[br]but instead of using a telescope,

0:05:08.990,0:05:11.310
let's use a microscope to zoom in

0:05:11.334,0:05:13.406
on the inferior of those chromosomes,

0:05:13.430,0:05:15.051
which is the Y chromosome.

0:05:16.432,0:05:19.446
It's a third the size of the X.[br]It's recessive and mutant.

0:05:20.443,0:05:21.594
But hey,

0:05:22.262,0:05:23.481
just a male.

0:05:24.914,0:05:27.194
And as you're looking at this stuff,

0:05:27.218,0:05:30.668
here's kind of a country view

0:05:30.692,0:05:32.896
at a 400 base pair resolution level,

0:05:32.920,0:05:36.339
and then you zoom in to 550,[br]and then you zoom in to 850,

0:05:36.363,0:05:39.648
and you can begin to identify[br]more and more genes as you zoom in.

0:05:40.249,0:05:42.553
Then you zoom in to the state level,

0:05:43.473,0:05:46.277
and you can begin to tell[br]who's got leukemia,

0:05:47.543,0:05:50.567
how did they get leukemia,[br]what kind of leukemia do they have,

0:05:50.591,0:05:52.655
what shifted from what place[br]to what place.

0:05:53.330,0:05:56.188
And then you zoom in[br]to the Google street view level.

0:05:57.387,0:06:00.060
So this is what happens[br]if you have colorectal cancer

0:06:00.084,0:06:04.291
for a very specific patient[br]on the letter-by-letter resolution.

0:06:06.148,0:06:09.258
So what we're doing in this stuff[br]is we're gathering information

0:06:09.282,0:06:11.798
and just generating[br]enormous amounts of information.

0:06:11.822,0:06:14.696
This is one of the largest[br]databases on the planet

0:06:14.720,0:06:18.592
and it's growing faster[br]than we can build computers to store it.

0:06:20.063,0:06:22.529
You can create some incredible[br]maps with this stuff.

0:06:23.292,0:06:26.263
You want to understand the plague[br]and why one plague is bubonic

0:06:26.287,0:06:28.511
and the other one[br]is a different kind of plague

0:06:28.535,0:06:30.845
and the other one[br]is a different kind of plague?

0:06:30.869,0:06:32.599
Well, here's a map of the plague.

0:06:33.037,0:06:34.857
Some are absolutely deadly to humans,

0:06:34.881,0:06:36.066
some are not.

0:06:36.486,0:06:39.082
And note, by the way,[br]as you go to the bottom of this,

0:06:39.106,0:06:40.859
how does it compare to tuberculosis?

0:06:41.708,0:06:45.337
So this is the difference between[br]tuberculosis and various kinds of plagues,

0:06:45.361,0:06:47.696
and you can play detective[br]with this stuff,

0:06:47.720,0:06:50.195
because you can take[br]a very specific kind of cholera

0:06:50.219,0:06:51.409
that affected Haiti,

0:06:52.377,0:06:55.063
and you can look at[br]which country it came from,

0:06:55.087,0:06:56.813
which region it came from,

0:06:57.496,0:07:02.238
and probably which soldier took that[br]from that African country to Haiti.

0:07:05.133,0:07:06.645
Zoom out.

0:07:06.669,0:07:08.240
It's not just zooming in.

0:07:09.042,0:07:11.896
This is one of the coolest maps[br]ever done by human beings.

0:07:12.446,0:07:15.502
What they've done is taken[br]all the genetic information they have

0:07:15.526,0:07:17.007
about all the species,

0:07:17.031,0:07:20.461
and they've put a tree of life[br]on a single page

0:07:20.485,0:07:22.063
that you can zoom in and out of.

0:07:22.484,0:07:26.205
So this is what came first,[br]how did it diversify, how did it branch,

0:07:26.229,0:07:27.459
how large is that genome,

0:07:27.483,0:07:28.680
on a single page.

0:07:29.619,0:07:31.682
It's kind of the universe[br]of life on Earth,

0:07:31.706,0:07:34.155
and it's being constantly[br]updated and completed.

0:07:34.982,0:07:36.841
And so as you're looking at this stuff,

0:07:36.865,0:07:40.216
the really important change is[br]the old biology used to be reactive.

0:07:40.240,0:07:42.960
You used to have a lot of biologists[br]that had microscopes,

0:07:42.984,0:07:46.283
and they had magnifying glasses[br]and they were out observing animals.

0:07:46.897,0:07:48.766
The new biology is proactive.

0:07:49.433,0:07:52.452
You don't just observe stuff,[br]you make stuff.

0:07:53.135,0:07:54.783
And that's a really big change

0:07:54.807,0:07:57.616
because it allows us[br]to do things like this.

0:07:58.559,0:08:01.026
And I know you're really[br]excited by this picture.

0:08:01.050,0:08:02.161
(Laughter)

0:08:02.185,0:08:04.559
It only took us four years[br]and 40 million dollars

0:08:04.583,0:08:06.185
to be able to take this picture.

0:08:06.209,0:08:07.439
(Laughter)

0:08:07.463,0:08:08.834
And what we did

0:08:09.586,0:08:12.861
is we took the full gene code[br]out of a cell --

0:08:12.885,0:08:16.796
not a gene, not two genes,[br]the full gene code out of a cell --

0:08:18.016,0:08:19.856
built a completely new gene code,

0:08:20.825,0:08:22.400
inserted it into the cell,

0:08:22.424,0:08:25.356
figured out a way to have the cell[br]execute that code

0:08:25.380,0:08:27.634
and built a completely new species.

0:08:28.884,0:08:31.369
So this is the world's first[br]synthetic life form.

0:08:33.810,0:08:35.705
And so what do you do with this stuff?

0:08:36.430,0:08:38.634
Well, this stuff is going[br]to change the world.

0:08:39.417,0:08:41.356
Let me give you three short-term trends

0:08:41.380,0:08:43.635
in terms of how it's going[br]to change the world.

0:08:44.269,0:08:47.190
The first is we're going to see[br]a new industrial revolution.

0:08:47.674,0:08:49.375
And I actually mean that literally.

0:08:49.992,0:08:54.483
So in the same way as Switzerland[br]and Germany and Britain

0:08:54.507,0:08:58.165
changed the world with machines[br]like the one you see in this lobby,

0:08:59.537,0:09:00.733
created power --

0:09:01.273,0:09:03.937
in the same way CERN[br]is changing the world,

0:09:03.961,0:09:07.308
using new instruments[br]and our concept of the universe --

0:09:08.060,0:09:10.954
programmable life forms[br]are also going to change the world

0:09:11.810,0:09:13.465
because once you can program cells

0:09:13.489,0:09:16.017
in the same way as you[br]program your computer chip,

0:09:17.736,0:09:19.429
then you can make almost anything.

0:09:20.369,0:09:23.148
So your computer chip[br]can produce photographs,

0:09:23.172,0:09:25.245
can produce music, can produce film,

0:09:25.269,0:09:27.682
can produce love letters,[br]can produce spreadsheets.

0:09:27.706,0:09:29.950
It's just ones and zeroes[br]flying through there.

0:09:30.604,0:09:33.209
If you can flow ATCGs through cells,

0:09:34.123,0:09:37.177
then this software makes its own hardware,

0:09:37.201,0:09:39.273
which means it scales very quickly.

0:09:40.487,0:09:42.138
No matter what happens,

0:09:42.162,0:09:44.320
if you leave your cell phone[br]by your bedside,

0:09:44.344,0:09:46.930
you will not have a billion[br]cell phones in the morning.

0:09:47.489,0:09:52.402
But if you do that with living organisms,

0:09:53.222,0:09:55.611
you can make this stuff[br]at a very large scale.

0:09:57.390,0:10:00.286
One of the things you can do[br]is you can start producing

0:10:00.310,0:10:02.533
close to carbon-neutral fuels

0:10:02.557,0:10:04.983
on a commercial scale by 2025,

0:10:06.054,0:10:07.815
which we're doing with Exxon.

0:10:08.870,0:10:11.279
But you can also substitute[br]for agricultural lands.

0:10:11.303,0:10:16.054
Instead of having 100 hectares[br]to make oils or to make proteins,

0:10:16.078,0:10:17.937
you can make it in these vats

0:10:17.961,0:10:20.829
at 10 or 100 times[br]the productivity per hectare.

0:10:21.488,0:10:24.870
Or you can store information,[br]or you can make all the world's vaccines

0:10:24.894,0:10:26.193
in those three vats.

0:10:27.276,0:10:31.225
Or you can store most of the information[br]that's held at CERN in those three vats.

0:10:32.350,0:10:35.559
DNA is a really powerful[br]information storage device.

0:10:36.806,0:10:38.394
Second turn:

0:10:38.418,0:10:41.202
you're beginning to see the rise[br]of theoretical biology.

0:10:42.256,0:10:46.458
So, medical school departments are one[br]of the most conservative places on earth.

0:10:46.482,0:10:49.899
The way they teach anatomy is similar[br]to the way they taught anatomy

0:10:49.923,0:10:51.089
100 years ago.

0:10:51.113,0:10:53.137
"Welcome, student. Here's your cadaver."

0:10:54.149,0:10:57.856
One of the things medical schools are[br]not good at is creating new departments,

0:10:57.880,0:10:59.629
which is why this is so unusual.

0:11:00.351,0:11:06.849
Isaac Kohane has now created a department[br]based on informatics, data, knowledge

0:11:06.873,0:11:08.384
at Harvard Medical School.

0:11:09.408,0:11:11.585
And in a sense,[br]what's beginning to happen is

0:11:11.609,0:11:14.091
biology is beginning to get enough data

0:11:14.115,0:11:16.881
that it can begin to follow[br]the steps of physics,

0:11:16.905,0:11:20.293
which used to be observational physics

0:11:20.317,0:11:22.288
and experimental physicists,

0:11:22.312,0:11:24.474
and then started creating[br]theoretical biology.

0:11:24.498,0:11:26.502
Well, that's what you're beginning to see

0:11:26.526,0:11:28.506
because you have so many medical records,

0:11:28.530,0:11:30.562
because you have[br]so much data about people:

0:11:30.586,0:11:32.996
you've got their genomes,[br]you've got their viromes,

0:11:33.020,0:11:34.514
you've got their microbiomes.

0:11:34.538,0:11:36.519
And as this information stacks,

0:11:36.543,0:11:38.606
you can begin to make predictions.

0:11:40.149,0:11:43.404
The third thing that's happening[br]is this is coming to the consumer.

0:11:44.629,0:11:48.785
So you, too, can get your genes sequenced.

0:11:49.698,0:11:52.426
And this is beginning to create[br]companies like 23andMe,

0:11:52.450,0:11:54.928
and companies like 23andMe[br]are going to be giving you

0:11:54.952,0:11:56.304
more and more and more data,

0:11:56.328,0:11:57.872
not just about your relatives,

0:11:58.562,0:11:59.922
but about you and your body,

0:11:59.946,0:12:01.477
and it's going to compare stuff,

0:12:01.501,0:12:03.594
and it's going[br]to compare stuff across time,

0:12:03.618,0:12:06.225
and these are going to become[br]very large databases.

0:12:06.249,0:12:09.211
But it's also beginning to affect[br]a series of other businesses

0:12:09.235,0:12:10.772
in unexpected ways.

0:12:11.802,0:12:15.553
Normally, when you advertise something,[br]you really don't want the consumer

0:12:15.577,0:12:20.144
to take your advertisement[br]into the bathroom to pee on.

0:12:21.993,0:12:24.048
Unless, of course, if you're IKEA.

0:12:25.381,0:12:28.287
Because when you rip this[br]out of a magazine and you pee on it,

0:12:28.311,0:12:30.380
it'll turn blue if you're pregnant.

0:12:30.404,0:12:31.617
(Laughter)

0:12:32.214,0:12:36.087
And they'll give you[br]a discount on your crib.

0:12:36.111,0:12:37.269
(Laughter)

0:12:37.293,0:12:39.308
Right? So when I say consumer empowerment,

0:12:39.332,0:12:42.071
and this is spreading beyond biotech,

0:12:42.095,0:12:43.914
I actually really mean that.

0:12:46.273,0:12:49.638
We're now beginning to produce,[br]at Synthetic Genomics,

0:12:50.540,0:12:52.011
desktop printers

0:12:53.228,0:12:56.758
that allow you to design a cell,

0:12:56.782,0:12:57.949
print a cell,

0:12:57.973,0:12:59.818
execute the program on the cell.

0:13:00.825,0:13:02.928
We can now print vaccines

0:13:02.952,0:13:05.199
real time as an airplane takes off

0:13:05.223,0:13:06.413
before it lands.

0:13:07.929,0:13:10.501
We're shipping 78[br]of these machines this year.

0:13:12.068,0:13:16.541
This is not theoretical biology.[br]This is printing biology.

0:13:18.182,0:13:20.378
Let me talk about two long-term trends

0:13:21.374,0:13:24.700
that are coming at you[br]over a longer time period.

0:13:25.658,0:13:28.314
The first one is, we're starting[br]to redesign species.

0:13:29.055,0:13:30.832
And you've heard about that, right?

0:13:30.856,0:13:33.537
We're redesigning trees.[br]We're redesigning flowers.

0:13:33.561,0:13:35.854
We're redesigning yogurt,

0:13:36.513,0:13:38.543
cheese, whatever else you want.

0:13:39.678,0:13:42.328
And that, of course,[br]brings up the interesting question:

0:13:42.884,0:13:45.220
How and when should we redesign humans?

0:13:47.566,0:13:51.123
And a lot of us think,[br]"Oh no, we never want to redesign humans."

0:13:52.147,0:13:54.862
Unless, of course, if your child[br]has a Huntington's gene

0:13:54.886,0:13:56.275
and is condemned to death.

0:13:57.172,0:14:00.535
Or, unless if you're passing on[br]a cystic fibrosis gene,

0:14:00.559,0:14:03.249
in which case, you don't just want[br]to redesign yourself,

0:14:03.273,0:14:05.812
you want to redesign your children[br]and their children.

0:14:06.723,0:14:10.368
And these are complicated debates[br]and they're going to happen in real time.

0:14:10.839,0:14:12.790
I'll give you one current example.

0:14:13.531,0:14:16.603
One of the debates going on[br]at the National Academies today

0:14:17.896,0:14:22.598
is you have the power to put[br]a gene drive into mosquitoes

0:14:22.622,0:14:25.606
so that you will kill[br]all the malaria-carrying mosquitoes.

0:14:27.547,0:14:30.107
Now, some people say,

0:14:30.964,0:14:34.429
"That's going to affect the environment[br]in an extreme way, don't do it."

0:14:35.326,0:14:36.481
Other people say,

0:14:36.505,0:14:39.732
"This is one of the things[br]that's killing millions of people yearly.

0:14:39.756,0:14:43.304
Who are you to tell me[br]that I can't save the kids in my country?"

0:14:45.183,0:14:47.036
And why is this debate so complicated?

0:14:47.060,0:14:49.941
Because as soon as you[br]let this loose in Brazil

0:14:49.965,0:14:51.388
or in Southern Florida --

0:14:51.412,0:14:52.953
mosquitoes don't respect walls.

0:14:52.977,0:14:55.278
You're making a decision for the world

0:14:55.302,0:14:57.209
when you put a gene drive into the air.

0:15:02.145,0:15:04.240
This wonderful man won a Nobel Prize,

0:15:05.103,0:15:06.743
and after winning the Nobel Prize

0:15:06.767,0:15:08.022
he's been worrying about

0:15:09.531,0:15:11.634
how did life get started on this planet

0:15:11.658,0:15:13.939
and how likely is it[br]that it's in other places?

0:15:15.097,0:15:18.299
So what he's been doing is going around[br]to this graduate students

0:15:18.323,0:15:20.041
and saying to his graduate students,

0:15:20.864,0:15:24.186
"Build me life but don't use[br]any modern chemicals or instruments.

0:15:24.210,0:15:26.875
Build me stuff that was here[br]three billion years ago.

0:15:26.899,0:15:30.055
You can't use lasers.[br]You can't use this. You can't use that."

0:15:32.330,0:15:35.575
He gave me a vial of what he's built[br]about three weeks ago.

0:15:36.639,0:15:37.818
What has he built?

0:15:37.842,0:15:41.867
He's built basically what looked like[br]soap bubbles that are made out of lipids.

0:15:41.891,0:15:44.457
He's built a precursor of RNA.

0:15:45.291,0:15:49.043
He's had the precursor of the RNA[br]be absorbed by the cell

0:15:50.194,0:15:52.077
and then he's had the cells divide.

0:15:54.031,0:15:55.988
We may not be that far --

0:15:57.687,0:16:00.804
call it a decade, maybe two decades --

0:16:00.828,0:16:02.798
from generating life from scratch

0:16:04.285,0:16:06.088
out of proto-communities.

0:16:07.512,0:16:09.158
Second long-term trend:

0:16:10.273,0:16:13.799
we've been living and are living[br]through the digital age --

0:16:13.823,0:16:16.342
we're starting to live through[br]the age of the genome

0:16:16.366,0:16:19.981
and biology and CRISPR[br]and synthetic biology --

0:16:20.870,0:16:23.777
and all of that is going to merge[br]into the age of the brain.

0:16:24.743,0:16:28.724
So we're getting to the point where[br]we can rebuild most of our body parts,

0:16:28.748,0:16:32.404
in the same way as if you break a bone[br]or burn your skin, it regrows.

0:16:32.428,0:16:35.096
We're beginning to learn[br]how to regrow our tracheas

0:16:35.120,0:16:36.984
or how to regrow our bladders.

0:16:37.008,0:16:39.314
Both of those have been[br]implanted in humans.

0:16:39.338,0:16:42.066
Tony Atala is working on[br]32 different organs.

0:16:43.487,0:16:45.377
But the core is going to be this,

0:16:45.401,0:16:48.455
because this is you[br]and the rest is just packaging.

0:16:50.011,0:16:53.558
Nobody's going to live beyond[br]120, 130, 140 years

0:16:53.582,0:16:55.317
unless if we fix this.

0:16:56.084,0:16:58.150
And that's the most interesting challenge.

0:16:58.174,0:17:00.285
That's the next frontier, along with:

0:17:00.309,0:17:02.656
"How common is life in the universe?"

0:17:02.680,0:17:04.486
"Where did we come from?"

0:17:04.510,0:17:06.144
and questions like that.

0:17:08.031,0:17:11.221
Let me end this with[br]an apocryphal quote from Einstein.

0:17:11.697,0:17:13.916
[You can live as if[br]everything is a miracle,

0:17:13.940,0:17:16.212
or you can live as if[br]nothing is a miracle.]

0:17:16.236,0:17:17.749
It's your choice.

0:17:18.555,0:17:21.034
You can focus on the bad,[br]you can focus on the scary,

0:17:21.058,0:17:23.474
and certainly there's[br]a lot of scary out there.

0:17:24.012,0:17:28.744
But use 10 percent of your brain[br]to focus on that, or maybe 20 percent,

0:17:28.768,0:17:30.594
or maybe 30 percent.

0:17:31.474,0:17:33.256
But just remember,

0:17:33.280,0:17:35.889
we really are living in an age[br]of miracle and wonder.

0:17:36.271,0:17:39.822
We're lucky to be alive today.[br]We're lucky to see this stuff.

0:17:39.846,0:17:42.687
We're lucky to be able to interact[br]with folks like the folks

0:17:42.711,0:17:44.821
who are building[br]all the stuff in this room.

0:17:45.487,0:17:48.462
So thank you to all of you,[br]for all you do.

0:17:49.066,0:17:52.762
(Applause)