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So let me with start with Roy Amara.

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Roy's argument is that most new
technologies tend to be overestimated

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in their impact to begin with,

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and then they get underestimated
in the long term,

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because we get used to them.

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These really are days
of miracle and wonder.

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You remember that wonderful
song by Paul Simon?

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There were two lines in it.

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So what was it that was considered
miraculous back then?

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Slowing down things, slow motion

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and the long-distance call.

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Because, of course, you used
to get interrupted by operators

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who'd tell you, "Long distance calling.
Do you want to hang up?

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And now we think nothing of calling
all over the world.

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Well, something similar may be happening

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with reading and programming life.

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But before I unpack that,

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let's just talk about telescopes.

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Telescopes were overestimated
originally in their impact.

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This is one of Galileo's early models.

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People thought it was just
going to ruin all religion.

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(Laughter)

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So we're not paying that much
attention to telescopes.

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But, of course, telescopes launched
10 years ago, as you just heard,

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could take this Volkswagen,
fly it to the moon,

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and you could see the lights
on that Volkswagen light up on the moon.

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And that's the kind of resolution power
that allowed you to see

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little specks of dust
floating around distant suns.

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Imagine for a second that this
was a sun a billion light years away,

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and you had a little speck of dust
that came in front of it.

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That's what detecting
an exoplanet is like.

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And the cool thing is, the telescopes
that are now being launched

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would allow you to see
a single candle lit on the moon.

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And if you separated it by one plate,

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you could see two candles
separately at that distance.

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And that's the kind
of resolution that you need

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to begin to image
that little speck of dust

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as it comes around the sun

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and see if it has a blue-green signature.

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And if it does have
a blue-green signature,

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it means that life
is common in the universe.

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The first time you ever see a blue-green
signature on a distant planet,

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it means there's photosynthesis there,

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there's water there,

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and the chances that you saw
the only other planet with photosynthesis

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are about zero.

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And that's a calendar-changing event.

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There's a before and after
we were alone in the universe,

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forget about the discovery
of whatever continent.

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So as you're thinking about this,

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we're now beginning
to be able to image most of the universe.

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And that is a time of miracle and wonder.

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And we kind of take that for granted.

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Something similar is happening in life.

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So we're hearing about life
in these little bits and pieces.

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We hear about CRISPR,
and we hear about this technology,

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and we hear about this technology.

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But the bottom line on life
is that life turns out to be code.

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And life as code is a really
important concept because it means,

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just in the same way
as you can write a sentence

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in English or in French or Chinese,

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just in the same way
as you can copy a sentence,

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just in the same way
as you can edit a sentence,

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just in the same way
as you can print a sentence,

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you're beginning to be able
to do that with life.

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It means that we're beginning
to learn how to read this language.

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And this, of course, is the language
that is used by this orange.

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So how does this orange execute code?

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It doesn't do it in ones and zeroes
like a computer does.

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It sits on a tree, and one day it does:

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plop!

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And that means: execute.

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AACTAAG: make me a little root.

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TCGACC: make me a little stem.

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GAC: make me some leaves.
AGC: make me some flowers.

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And then GCAA: make me some more oranges.

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If I edit a sentence in English
on a word processor,

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then what happens is you can go
from this word to that word.

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If I edit something in this orange

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and put in GCAAC, using CRISPR
or something else that you've heard of,

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then this orange becomes a lemon,

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or it becomes a grapefruit,

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or it becomes a tangerine.

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And if I edit one in a thousand letters,

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you become the person
sitting next to you today.

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Be more careful where you sit.

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(Laughter)

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What's happening on this stuff
is it was really expensive to begin with.

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It was like long-distance calls.

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But the cost of this is dropping
50 percent faster than Moore's law.

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The first $200 full genome
was announced yesterday by Veritas.

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And so as you're looking at these systems,

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it doesn't matter, it doesn't matter,
it doesn't matter, and then it does.

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So let me just give you
the map view of this stuff.

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This is a big discovery.

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There's 23 chromosomes.

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Cool.

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Let's now start using a telescope version,
but instead of using a telescope,

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let's use a microscope to zoom in

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on the inferior of those chromosomes,

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which is the Y chromosome.

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It's a third the size of the X.
It's recessive and mutant.

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But hey,

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just a male.

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And as you're looking at this stuff,

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here's kind of a country view

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at a 400 base pair resolution level,

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and then you zoom in to 550,
and then you zoom in to 850,

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and you can begin to identify
more and more genes as you zoom in.

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Then you zoom in to the state level,

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and you can begin to tell
who's got leukemia,

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how did they get leukemia,
what kind of leukemia do they have,

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what shifted from what place
to what place.

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And then you zoom in
to the Google street view level.

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So this is what happens
if you have colorectal cancer

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for a very specific patient
on the letter-by-letter resolution.

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So what we're doing in this stuff
is we're gathering information

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and just generating
enormous amounts of information.

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This is one of the largest
databases on the planet,

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and it's growing faster
than we can build computers to store it.

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You can create some incredible
maps with this stuff.

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You want to understand the plague
and why one plague is bubonic

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and the other one
is a different kind of plague

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and the other one
is a different kind of plague?

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Well, here's a map of the plague.

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Some are absolutely deadly to humans,

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some are not.

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And note, by the way,
as you go to the bottom of this,

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how does it compare to tuberculosis?

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So this is the difference between
tuberculosis and various kinds of plagues,

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and you can play detective
with this stuff,

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because you can take
a very specific kind of cholera

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that affected Haiti,

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and you can look at
which country it came from,

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which region it came from,

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and probably which soldier took that
from that African country to Haiti.

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Zoom out.

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It's not just zooming in.

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This is one of the coolest maps
ever done by human beings.

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What they've done is taken
all the genetic information they have

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about all the species,

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and they've put a tree of life
on a single page

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that you can zoom in and out of.

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So this is what came first,
how did it diversify, how did it branch,

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how large is that genome,

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on a single page.

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It's kind of the universe
of life on Earth,

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and it's being constantly
updated and completed.

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And so as you're looking at this stuff,

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the really important changes,
the old biology, used to be reactive.

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You used to have a lot of biologists
that had microscopes,

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and they had magnifying glasses,
and they were out observing animals.

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The new biology is proactive.

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You don't just observe stuff,
you make stuff.

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And that's a really big change,

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because it allows us
to do things like this.

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And I know you're really
excited by this picture.

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(Laughter)

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It only took us four years
and 40 million dollars

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to be able to take this picture.

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(Laughter)

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And what we did

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is we took the full gene code
out of a cell --

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not a gene, not two genes,
the full gene code out of a cell --

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built a completely new gene code,

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inserted it into the cell,

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figured out a way to have the cell
execute that code

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and built a completely new species.

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So this is the world's first
synthetic life form.

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And so what do you do with this stuff?

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Well, this stuff is going
to change the world.

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Let me give you three short-term trends

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in terms of how it's going
to change the world.

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The first is we're going to see
a new industrial revolution.

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And I actually mean that literally.

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So in the same way as Switzerland
and Germany and Britain

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changed the world with machines
like the one you see in this lobby,

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created power,

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in the same way CERN
is changing the world,

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using new instruments
and our concept of the universe,

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programmable life forms
are also going to change the world,

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because once you can program cells

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in the same way as you
program your computer chip,

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then you can make almost anything.

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So your computer chip
can produce photographs,

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can produce music, can produce film,

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can produce love letters,
can produce spreadsheets.

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It's just ones and zeroes
flying through there.

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If you can flow ATCGs through cells,

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then this software makes its own hardware,

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which means it scales very quickly.

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No matter what happens,

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if you leave your cell phone
by your bedside,

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you will not have a billion
cell phones in the morning.

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But if you do that with living organisms,

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you can make this stuff
at a very large scale.

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One of the things you can do
is you can start producing

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close to carbon-neutral fuels

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on a commercial scale by 2025,

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which we're doing with Exxon.

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But you can also substitute
for agricultural lands.

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Instead of having 100 hectares
to make oils or to make proteins,

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you can make it in these vats

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at 10 or 100 times
the productivity per hectare.

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Or you can store information,
or you can make all the world's vaccines

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in those three vats.

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Or you can store most of the information
that's held at CERN in those three vats.

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DNA is a really powerful
information storage device.

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Second turn:

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you're beginning to see the rise
of theoretical biology.

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So, medical school departments are one
of the most conservative places on earth.

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The way they teach anatomy is similar
to the way they taught anatomy

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100 years ago.

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00:10:51,113 --> 00:10:53,137
"Welcome, student. Here's your cadaver."

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One of the things medical schools are
not good at is creating new departments,

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which is why this is so unusual.

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00:11:00,351 --> 00:11:06,849
Isaac Kohane has now created a department
based on informatics, data, knowledge,

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00:11:06,873 --> 00:11:08,384
at Harvard Medical School.

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And in a sense,
what's beginning to happen is,

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biology is beginning to get enough data

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that it can begin to follow
the steps of physics,

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which used to be observational physics

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and experimental physicists

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and then started creating
theoretical biology.

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Well, that's what you're beginning to see

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because you have so many medical records,

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because you have
so much data about people:

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you've got their genomes,
you've got their viromes,

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you've got their microbiomes.

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And as this information stacks,

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you can begin to make predictions.

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The third thing that's happening
is, this is coming to the consumer.

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00:11:44,629 --> 00:11:48,785
So you, too, can get your genes sequenced.

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And this is beginning to create
companies like 23andMe,

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00:11:52,450 --> 00:11:54,928
and companies like 23andMe
are going to be giving you

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more and more and more data,

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not just about your relatives

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00:11:58,562 --> 00:11:59,922
but about you and your body,

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and it's going to compare stuff,

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00:12:01,501 --> 00:12:03,594
and it's going
to compare stuff across time,

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00:12:03,618 --> 00:12:06,225
and these are going to become
very large databases.

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00:12:06,249 --> 00:12:09,211
But it's also beginning to affect
a series of other businesses

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00:12:09,235 --> 00:12:10,772
in unexpected ways.

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Normally, when you advertise something,
you really don't want the consumer

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00:12:15,577 --> 00:12:20,144
to take your advertisement
into the bathroom to pee on,

246
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unless, of course, if you're IKEA.

247
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Because when you rip this
out of a magazine and you pee on it,

248
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it'll turn blue if you're pregnant.

249
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(Laughter)

250
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And they'll give you
a discount on your crib.

251
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(Laughter)

252
00:12:37,293 --> 00:12:39,308
Right? So when I say consumer empowerment,

253
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and this is spreading beyond biotech,

254
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I actually really mean that.

255
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We're now beginning to produce,
at Synthetic Genomics,

256
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desktop printers

257
00:12:53,228 --> 00:12:56,758
that allow you to design a cell,

258
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print a cell,

259
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execute the program on the cell.

260
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We can now print vaccines

261
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real time as an airplane takes off

262
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before it lands.

263
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We're shipping 78
of these machines this year.

264
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This is not theoretical biology.
This is printing biology.

265
00:13:18,182 --> 00:13:20,378
Let me talk about two long-term trends

266
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that are coming at you
over a longer time period.

267
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The first one is, we're starting
to redesign species.

268
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And you've heard about that, right?

269
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We're redesigning trees.
We're redesigning flowers.

270
00:13:33,561 --> 00:13:35,854
We're redesigning yogurt,

271
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cheese, whatever else you want.

272
00:13:39,678 --> 00:13:42,328
And that, of course,
brings up the interesting question:

273
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How and when should we redesign humans?

274
00:13:47,566 --> 00:13:51,123
And a lot of us think,
"Oh no, we never want to redesign humans."

275
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Unless, of course, if your child
has a Huntington's gene

276
00:13:54,886 --> 00:13:56,275
and is condemned to death.

277
00:13:57,172 --> 00:14:00,535
Or, unless if you're passing on
a cystic fibrosis gene,

278
00:14:00,559 --> 00:14:03,249
in which case, you don't just want
to redesign yourself,

279
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you want to redesign your children
and their children.

280
00:14:06,723 --> 00:14:10,368
And these are complicated debates
and they're going to happen in real time.

281
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I'll give you one current example.

282
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One of the debates going on
at the National Academies today

283
00:14:17,896 --> 00:14:22,598
is you have the power to put
a gene drive into mosquitoes

284
00:14:22,622 --> 00:14:25,606
so that you will kill
all the malaria-carrying mosquitoes.

285
00:14:27,547 --> 00:14:30,107
Now, some people say,

286
00:14:30,964 --> 00:14:34,429
"That's going to affect the environment
in an extreme way, don't do it."

287
00:14:35,326 --> 00:14:36,481
Other people say,

288
00:14:36,505 --> 00:14:39,732
"This is one of the things
that's killing millions of people yearly.

289
00:14:39,756 --> 00:14:43,304
Who are you to tell me
that I can't save the kids in my country?"

290
00:14:45,183 --> 00:14:47,036
And why is this debate so complicated?

291
00:14:47,060 --> 00:14:49,941
Because as soon as you
let this loose in Brazil

292
00:14:49,965 --> 00:14:51,388
or in Southern Florida --

293
00:14:51,412 --> 00:14:52,953
mosquitoes don't respect walls.

294
00:14:52,977 --> 00:14:55,278
You're making a decision for the world

295
00:14:55,302 --> 00:14:57,209
when you put a gene drive into the air.

296
00:15:02,145 --> 00:15:04,240
This wonderful man won a Nobel Prize,

297
00:15:05,103 --> 00:15:06,743
and after winning the Nobel Prize,

298
00:15:06,767 --> 00:15:08,022
he's been worrying about

299
00:15:09,531 --> 00:15:11,634
how did life get started on this planet

300
00:15:11,658 --> 00:15:13,939
and how likely is it
that it's in other places?

301
00:15:15,097 --> 00:15:18,299
So what he's been doing is going around
to this graduate students

302
00:15:18,323 --> 00:15:20,041
and saying to his graduate students,

303
00:15:20,864 --> 00:15:24,186
"Build me life but don't use
any modern chemicals or instruments.

304
00:15:24,210 --> 00:15:26,875
Build me stuff that was here
three billion years ago.

305
00:15:26,899 --> 00:15:30,055
You can't use lasers.
You can't use this. You can't use that."

306
00:15:32,330 --> 00:15:35,575
He gave me a vial of what he's built
about three weeks ago.

307
00:15:36,639 --> 00:15:37,818
What has he built?

308
00:15:37,842 --> 00:15:41,867
He's built basically what looked like
soap bubbles that are made out of lipids.

309
00:15:41,891 --> 00:15:44,457
He's built a precursor of RNA.

310
00:15:45,291 --> 00:15:49,043
He's had the precursor of the RNA
be absorbed by the cell,

311
00:15:50,194 --> 00:15:52,077
and then he's had the cells divide.

312
00:15:54,031 --> 00:15:55,988
We may not be that far --

313
00:15:57,687 --> 00:16:00,804
call it a decade, maybe two decades --

314
00:16:00,828 --> 00:16:02,798
from generating life from scratch

315
00:16:04,285 --> 00:16:06,088
out of proto-communities.

316
00:16:07,512 --> 00:16:09,158
Second long-term trend:

317
00:16:10,273 --> 00:16:13,799
we've been living and are living
through the digital age,

318
00:16:13,823 --> 00:16:16,342
we're starting to live through
the age of the genome,

319
00:16:16,366 --> 00:16:19,981
and biology and CRISPR
and synthetic biology

320
00:16:20,870 --> 00:16:23,777
and all of that is going to merge
into the age of the brain.

321
00:16:24,743 --> 00:16:28,724
So we're getting to the point where
we can rebuild most of our body parts

322
00:16:28,748 --> 00:16:32,404
in the same way as if you break a bone
or burn your skin, and it regrows.

323
00:16:32,428 --> 00:16:35,096
We're beginning to learn
how to regrow our tracheas

324
00:16:35,120 --> 00:16:36,984
or how to regrow our bladders.

325
00:16:37,008 --> 00:16:39,314
Both of those have been
implanted in humans.

326
00:16:39,338 --> 00:16:42,066
Tony Atala is working on
32 different organs.

327
00:16:43,487 --> 00:16:45,377
But the core is going to be this,

328
00:16:45,401 --> 00:16:48,455
because this is you,
and the rest is just packaging.

329
00:16:50,011 --> 00:16:53,558
Nobody's going to live beyond
120, 130, 140 years

330
00:16:53,582 --> 00:16:55,317
unless if we fix this.

331
00:16:56,084 --> 00:16:58,150
And that's the most interesting challenge.

332
00:16:58,174 --> 00:17:00,285
That's the next frontier, along with

333
00:17:00,309 --> 00:17:02,656
"How common is life in the universe?"

334
00:17:02,680 --> 00:17:04,486
"Where did we come from?"

335
00:17:04,510 --> 00:17:06,144
and questions like that.

336
00:17:08,031 --> 00:17:11,221
Let me end this with
an apocryphal quote from Einstein.

337
00:17:11,697 --> 00:17:13,916
[You can live as if
everything is a miracle,

338
00:17:13,940 --> 00:17:16,212
or you can live as if
nothing is a miracle.]

339
00:17:16,236 --> 00:17:17,749
It's your choice.

340
00:17:18,555 --> 00:17:21,034
You can focus on the bad,
you can focus on the scary,

341
00:17:21,058 --> 00:17:23,474
and certainly there's
a lot of scary out there.

342
00:17:24,012 --> 00:17:28,744
But use 10 percent of your brain
to focus on that, or maybe 20 percent,

343
00:17:28,768 --> 00:17:30,594
or maybe 30 percent.

344
00:17:31,474 --> 00:17:33,256
But just remember,

345
00:17:33,280 --> 00:17:35,889
we really are living in an age
of miracle and wonder.

346
00:17:36,271 --> 00:17:39,822
We're lucky to be alive today.
We're lucky to see this stuff.

347
00:17:39,846 --> 00:17:42,687
We're lucky to be able to interact
with folks like the folks

348
00:17:42,711 --> 00:17:44,821
who are building
all the stuff in this room.

349
00:17:45,487 --> 00:17:48,462
So thank you to all of you,
for all you do.

350
00:17:49,066 --> 00:17:52,762
(Applause)