0:00:00.835,0:00:03.148
How many of you are creatives?

0:00:03.148,0:00:06.796
Designers, engineers,[br]entrepreneurs, artists,

0:00:06.796,0:00:09.207
or maybe you just have[br]a really big imagination.

0:00:09.207,0:00:10.207
Show of hands?

0:00:10.207,0:00:11.207
(Applause)

0:00:11.207,0:00:12.813
That's most of you.

0:00:13.434,0:00:15.728
I have some news for us creatives.

0:00:16.934,0:00:21.571
Over the course of the next 20 years ...

0:00:21.571,0:00:25.570
more will change around[br]the way we do our work

0:00:25.570,0:00:28.254
than has happened in the last 2,000.

0:00:28.611,0:00:33.239
In fact, I think we're at the dawn[br]of a new age in human history.

0:00:33.841,0:00:38.602
Now, there have been four major historical[br]eras defined by the way we work.

0:00:39.504,0:00:42.779
The Hunter-Gatherer Age[br]lasted several million years.

0:00:43.263,0:00:46.839
And then the Agricultural Age[br]lasted several thousand years.

0:00:47.295,0:00:50.809
The Industrial Age lasted[br]a couple of centuries,

0:00:50.809,0:00:54.843
and now the Information Age[br]has lasted just a few decades.

0:00:55.120,0:00:56.756
And now today,

0:00:56.756,0:01:00.340
we're on the cusp of our next[br]great era as a species.

0:01:01.496,0:01:03.969
Welcome to the Augemented Age.

0:01:04.199,0:01:05.351
In this new era,

0:01:05.351,0:01:09.199
your natural human capabilities are going[br]to be augmented by computational systems

0:01:09.199,0:01:11.009
that help you think,

0:01:11.009,0:01:13.175
robotic systems that help you make,

0:01:13.175,0:01:14.891
and [a] digital nervous system

0:01:14.891,0:01:19.214
that connects you to the world[br]fay beyond your natural senses.

0:01:19.530,0:01:21.467
Let's start with cognitive augmentation.

0:01:21.467,0:01:23.667
How many of you are augmented cyborgs?

0:01:24.333,0:01:25.329
(Laughter)

0:01:26.905,0:01:30.006
I would actually argue that we're[br]already augmented.

0:01:30.488,0:01:32.016
Imagine you're at a party,

0:01:32.016,0:01:35.491
and somebody asks you a question[br]that you don't know the answer to.

0:01:35.491,0:01:36.940
If you have one of these,

0:01:36.940,0:01:38.038
in a few seconds,

0:01:38.038,0:01:39.644
you can know the answer.

0:01:39.951,0:01:42.635
But this is just a primitive beginning.

0:01:42.938,0:01:46.436
Even Siri is just a passive tool.

0:01:46.860,0:01:50.186
In fact, for the last[br]three-and-a-half million years,

0:01:50.186,0:01:53.633
the tools that we've had[br]have been completely passive.

0:01:54.403,0:01:57.971
They do exactly what we tell them[br]and nothing more.

0:01:57.971,0:02:01.462
Our very first tool only cut[br]where we struck it.

0:02:02.022,0:02:05.284
The chisel only carves[br]where the artist points it.

0:02:05.543,0:02:10.898
And even our most advanced tools[br]do nothing without our explicit direction.

0:02:11.208,0:02:12.647
In fact, to date --

0:02:12.647,0:02:14.672
and this is something[br]that frustrates me --

0:02:14.672,0:02:15.933
we've always been limited

0:02:15.933,0:02:19.215
by this need to manually[br]push our wills into our tools --

0:02:19.215,0:02:20.230
like manual,

0:02:20.230,0:02:21.715
like literally using our hands,

0:02:21.715,0:02:23.277
even with computers.

0:02:24.272,0:02:26.759
But I'm more like Scotty in "Star Trek."

0:02:26.759,0:02:27.759
(Laughter)

0:02:28.584,0:02:30.803
I want to have a conversation[br]with a computer.

0:02:30.803,0:02:33.797
I want to say, "Computer,[br]let's design a car,"

0:02:33.797,0:02:35.360
and the computer shows me a car.

0:02:35.360,0:02:37.992
And I say, "No, more fast-looking,[br]and less German,"

0:02:37.992,0:02:40.156
and bang, the computer shows me an option.

0:02:40.156,0:02:41.159
(Laughter)

0:02:42.408,0:02:44.738
That conversation might be[br]a little ways off,

0:02:44.738,0:02:47.290
it's actually probably less[br]than any of us think,

0:02:47.290,0:02:49.300
but right now,

0:02:49.300,0:02:50.307
we're working on it.

0:02:50.307,0:02:54.340
Tools are making this leap from being[br]passive to being generative.

0:02:55.031,0:02:58.363
Generative design tools[br]use a computer and algorithms

0:02:58.363,0:03:00.995
to synthesize geometry

0:03:00.995,0:03:03.749
to come up with new designs[br]all by themselves.

0:03:04.196,0:03:06.968
All it needs are your goals[br]and your constraints.

0:03:06.968,0:03:08.400
I'll give you an example.

0:03:08.400,0:03:11.212
In the case of this aerial drone chassis,

0:03:11.212,0:03:13.593
all you would need to do[br]is tell it something like,

0:03:13.593,0:03:15.083
it has four propellers,

0:03:15.083,0:03:17.186
you want it to be[br]as lightweight as possible,

0:03:17.186,0:03:19.421
and you need it to be[br]aerodynamically efficient.

0:03:19.421,0:03:21.550
And then what the computer does

0:03:21.550,0:03:24.546
is it explores the entire solution space:

0:03:24.546,0:03:28.497
every single possibility that solves[br]and meets your criteria --

0:03:28.497,0:03:29.844
millions of them.

0:03:29.844,0:03:31.797
It takes big computers to do this,

0:03:31.797,0:03:33.854
but it comes back to us with designs

0:03:33.854,0:03:36.997
that we by ourselves[br]never could've imagined.

0:03:37.380,0:03:40.143
And the computer's coming up[br]with this stuff all by itself,

0:03:40.143,0:03:42.153
no one ever drew anything,

0:03:42.153,0:03:44.532
and it started completely from scratch.

0:03:45.115,0:03:46.135
And by the way,

0:03:46.135,0:03:47.649
it's no accident

0:03:47.649,0:03:51.130
that the drone body looks just like[br]the pelvis of a flying squirrel.

0:03:51.487,0:03:52.612
(Laughter)

0:03:54.162,0:03:58.314
It's because the algorithms are designed[br]to work the same way that evolution does.

0:03:58.915,0:04:02.685
What's exciting is we're starting to see[br]this technology out in the real world.

0:04:02.685,0:04:05.159
We've been working with Airbus[br]for a couple of years

0:04:05.159,0:04:07.085
on this concept plane for the future.

0:04:07.085,0:04:09.285
It's aways out still,

0:04:09.285,0:04:13.018
but just recently we used[br]a generative design AI

0:04:13.018,0:04:15.390
to come up with this.

0:04:15.809,0:04:20.891
This is a 3D printed cabin partition[br]that's been designed by a computer.

0:04:20.891,0:04:23.834
It's stronger than the original[br]yet half the weight,

0:04:23.834,0:04:26.980
and it will be flying[br]in the Airbus A320 later this year.

0:04:27.498,0:04:29.188
So, computers can now generate.

0:04:29.188,0:04:33.694
They can come up with their own solutions[br]to our well-defined problems.

0:04:34.815,0:04:36.211
But they're not inutitive.

0:04:36.211,0:04:39.321
They still have to start from scratch[br]every single time,

0:04:39.321,0:04:42.568
and that's because they never learn ...

0:04:42.568,0:04:44.358
unlike Maggie.

0:04:44.358,0:04:45.364
(Laughter)

0:04:45.764,0:04:49.118
Maggie's actually smarter than our[br]most advanced design tools.

0:04:49.522,0:04:50.985
What do I mean by that?

0:04:50.985,0:04:52.578
If her owner picks up that leash,

0:04:52.578,0:04:54.624
Maggie knows with a fair[br]degree of certainty

0:04:54.624,0:04:56.048
that it's time to for a walk.

0:04:56.265,0:04:57.475
And how did she learn?

0:04:57.475,0:04:59.703
Well, every time the owner[br]picked up the leash,

0:04:59.703,0:05:00.715
they went for a walk.

0:05:00.715,0:05:02.724
And Maggie did three things:

0:05:02.724,0:05:04.617
she had to pay attention,

0:05:04.617,0:05:06.723
she had to remember what happened

0:05:06.723,0:05:11.157
and she had to retain and create[br]a pattern in her mind.

0:05:11.544,0:05:12.634
Interestingly,

0:05:12.634,0:05:16.094
that's exactly computer scientists[br]have been trying to get AIs to do

0:05:16.094,0:05:18.056
for the last 60 or so years.

0:05:18.681,0:05:20.256
Back in 1952,

0:05:20.256,0:05:24.292
they built this computer[br]that could play Tic-Tac-Toe.

0:05:25.130,0:05:26.290
Big deal.

0:05:26.931,0:05:28.487
Then 45 years later,

0:05:28.487,0:05:30.253
in 1997,

0:05:30.253,0:05:33.332
Deep Blue beats Kasparov at Chess.

0:05:34.246,0:05:39.031
2011, Watson beats these two[br]humans at Jeopardy,

0:05:39.031,0:05:41.901
which is much harder for a computer[br]to play than Chess is.

0:05:42.190,0:05:46.026
In fact, rather than working[br]from predefined recipes,

0:05:46.026,0:05:49.349
Watson had to use reasoning[br]to overcome his human opponents.

0:05:50.438,0:05:53.056
And then a couple of weeks ago,

0:05:53.056,0:05:57.225
DeepMind's AlphaGo beats[br]the world's best human at Go,

0:05:57.225,0:05:59.382
which is the most difficult[br]game that we have.

0:05:59.382,0:06:00.379
In fact in Go,

0:06:00.379,0:06:04.706
there are more possible moves[br]than there are atoms in the universe.

0:06:06.315,0:06:08.260
So in order to win,

0:06:08.260,0:06:11.210
what AlphaGo had to do[br]was develop intuition,

0:06:11.210,0:06:12.273
and in fact,

0:06:12.273,0:06:13.273
at some points,

0:06:13.273,0:06:17.631
AlphaGo's programmers didn't understand[br]why AlphaGo was doing what it was doing.

0:06:19.527,0:06:21.168
And things are moving really fast.

0:06:21.168,0:06:22.286
I mean, consider --

0:06:22.286,0:06:24.586
in the space of a human lifetime,

0:06:24.586,0:06:28.120
computers have gone from a child's game

0:06:28.120,0:06:31.537
to what's recognized as the pinnacle[br]of strategic thought.

0:06:32.199,0:06:34.602
What's basically happening

0:06:34.602,0:06:37.974
is computers are going[br]from being like Spock

0:06:37.974,0:06:39.947
to being a lot more like Kirk.

0:06:39.947,0:06:41.895
(Laughter)

0:06:43.526,0:06:44.534
Right?

0:06:44.534,0:06:47.111
From pure logic to intuition.

0:06:48.298,0:06:50.373
Would you cross this bridge?

0:06:50.698,0:06:51.810
Most of you are saying,

0:06:51.810,0:06:53.156
"Oh, hell no."

0:06:53.156,0:06:54.159
(Laughter)

0:06:54.488,0:06:57.169
And you arrived at that decision[br]in a split second.

0:06:57.169,0:06:59.518
You just sort of knew[br]that that bridge was unsafe.

0:06:59.518,0:07:01.634
And that's exactly the kind of intuition

0:07:01.634,0:07:05.202
that our deep learning systems[br]are starting to develop right now.

0:07:05.607,0:07:06.607
Very soon,

0:07:06.607,0:07:09.191
you'll literally be able[br]to show something you've made,

0:07:09.191,0:07:10.194
you've designed,

0:07:10.194,0:07:11.193
to a computer,

0:07:11.193,0:07:12.670
and it will look at it and say,

0:07:12.670,0:07:14.540
"Mm, sorry homey, that will never work,

0:07:14.540,0:07:15.672
you have to try again."

0:07:16.078,0:07:19.973
Or you could ask it if people[br]are going to like your next song,

0:07:19.973,0:07:22.568
or your next flavor of ice cream.

0:07:23.607,0:07:26.395
Or, much more importantly,

0:07:26.395,0:07:30.290
you could work with a computer to solve[br]a problem that we've never faced before.

0:07:30.290,0:07:31.648
For instance climate change.

0:07:31.648,0:07:33.676
We're not doing a very[br]good job on our own,

0:07:33.676,0:07:35.877
we could certainly use[br]all the help we can get.

0:07:36.048,0:07:37.485
That's what I'm talking about:

0:07:37.485,0:07:40.200
technology amplifying[br]our cognitive abilities

0:07:40.200,0:07:41.866
so we can imagine and design things

0:07:41.866,0:07:46.633
that were simply out of our reach[br]as plain old unaugmented humans.

0:07:48.137,0:07:51.006
So, what about making[br]all of this crazy new stuff

0:07:51.006,0:07:53.754
that we're going to invent and design?

0:07:54.152,0:07:58.269
I think the era of human augmentation[br]is as much about the physical world

0:07:58.269,0:08:01.743
as it is about the virtual,[br]intellectual realm.

0:08:02.033,0:08:04.574
So how will technology augment us?

0:08:04.574,0:08:05.768
In the physcial world,

0:08:05.768,0:08:07.098
robotic systems.

0:08:07.820,0:08:11.793
OK, there's certainly a fear that robots[br]are going to take jobs away from humans,

0:08:11.793,0:08:14.029
and that is true in certain sectors.

0:08:14.306,0:08:17.352
But I'm much more interested in this idea

0:08:17.352,0:08:22.310
that humans and robots working together[br]are going to augment each other,

0:08:22.310,0:08:24.392
and start to inhabit a new space.

0:08:24.392,0:08:26.778
This is our applied[br]research lab in San Francisco,

0:08:26.778,0:08:29.944
where one of our areas of focus[br]is advanced robotics,

0:08:29.944,0:08:32.608
specifically human-robot collaboration.

0:08:33.234,0:08:34.644
And this is Bishop,

0:08:34.644,0:08:36.017
one of our robots.

0:08:36.017,0:08:37.340
As an experiment,

0:08:37.340,0:08:41.243
we set it up to help a person working[br]in construction doing repetitive tasks.

0:08:42.098,0:08:46.377
Tasks like cutting out holes for outlets[br]or light switches in dry wall.

0:08:46.704,0:08:47.948
(Laughter)

0:08:50.077,0:08:53.212
So, Bishop's human partner[br]can tell what to do in plain English

0:08:53.212,0:08:54.541
and with simple gestures,

0:08:54.541,0:08:56.012
kind of like talking to a dog,

0:08:56.012,0:08:58.178
and then Bishop executes[br]on those instructions

0:08:58.178,0:08:59.767
with perfect precision.

0:09:00.047,0:09:02.546
We're using the human for what[br]the human is good at,

0:09:02.546,0:09:03.552
right?

0:09:03.552,0:09:05.583
Awareness, perception and desicion making.

0:09:05.583,0:09:07.826
And we're using the robot[br]for what it's good at:

0:09:07.826,0:09:09.848
precision and repetitiveness.

0:09:10.256,0:09:12.682
Here's another cool project[br]that Bishop worked on.

0:09:12.682,0:09:14.181
The goal of this project,

0:09:14.181,0:09:15.942
which we called the HIVE,

0:09:15.942,0:09:19.817
was to prototype the experience[br]of humans, computers and robots

0:09:19.817,0:09:23.398
all working together to solve[br]a highly complex design problem.

0:09:23.831,0:09:25.365
The humans acted as labor.

0:09:25.365,0:09:27.383
They cruised around the construction site,

0:09:27.383,0:09:28.735
they manipulated the bamboo,

0:09:28.735,0:09:29.743
which by the way,

0:09:29.743,0:09:31.659
because it's a [nonisomorphic] material,

0:09:31.659,0:09:33.504
is super hard for robots to deal with.

0:09:33.504,0:09:35.598
But then the robots[br]did this fiber winding,

0:09:35.598,0:09:37.940
which was almost impossible[br]for a human to do.

0:09:37.940,0:09:41.702
And then we had an AI[br]that was controlling everything.

0:09:41.702,0:09:43.466
It was telling the humans what to do,

0:09:43.466,0:09:45.265
it was telling the robots what to do,

0:09:45.265,0:09:47.993
and keeping track of thousands[br]of individual components.

0:09:47.993,0:09:52.431
What's interesting is building[br]this pavilion was simply not possible

0:09:52.431,0:09:57.306
without human, robot and AI[br]augmenting each other.

0:09:57.868,0:09:59.391
OK, I'll share one more project.

0:09:59.391,0:10:01.363
This one's a little bit crazy.

0:10:01.363,0:10:05.926
We're working with Amsterdam-based artist,[br]Joris Laarman and his team at MX3D

0:10:05.926,0:10:08.828
to generatively design[br]and robotically print

0:10:08.828,0:10:11.823
the world's first autonomously[br]manufactured bridge.

0:10:12.566,0:10:16.224
So, Joris and an AI are designing[br]this thing right now, as we speak,

0:10:16.224,0:10:17.260
in Amsterdam.

0:10:17.260,0:10:18.341
And when they're done,

0:10:18.341,0:10:19.842
we're going to hit "go,"

0:10:19.842,0:10:23.176
and robots will start 3D printing[br]in stainless steel,

0:10:23.176,0:10:26.482
and then they're going to keep printing[br]without human intervention

0:10:26.482,0:10:28.341
until the bridge is finished.

0:10:29.250,0:10:32.251
So, as computers are going[br]to augment our ability

0:10:32.251,0:10:34.453
to imagine and design new stuff,

0:10:34.453,0:10:36.179
robotic systems are going to help us

0:10:36.179,0:10:39.883
build and make things that we've[br]never been able to make before.

0:10:40.440,0:10:44.378
But what about our ability[br]to sense and control these things?

0:10:44.624,0:10:48.529
What about a nervous system[br]for the things that we make?

0:10:48.787,0:10:50.230
Our nervous system --

0:10:50.230,0:10:51.542
the human nervous system --

0:10:51.542,0:10:54.093
tells us everything that's[br]going on around us.

0:10:54.363,0:10:57.750
But the nervous system of the things[br]we make is rudimentary at best.

0:10:58.119,0:10:59.131
For instance,

0:10:59.131,0:11:01.681
a car doesn't tell the city's[br]Public Works department

0:11:01.681,0:11:04.835
that it just hit a pothole at the corner[br]of Broadway and Morrison;

0:11:04.835,0:11:06.891
A building doesn't tell its designers

0:11:06.891,0:11:09.683
whether or not the people[br]inside like being there,

0:11:09.683,0:11:14.570
and the toy manufacturer doesn't know[br]if a toy is actually being played with --

0:11:14.570,0:11:17.461
how and where and whether[br]or not it's any fun.

0:11:17.820,0:11:21.569
Look, I'm sure that the designers[br]imagined this lifestyle for Barbie

0:11:21.569,0:11:23.591
when they designed her --

0:11:23.591,0:11:24.589
right?

0:11:24.589,0:11:27.489
But what if it turns out that Barbie's[br]actually really lonely?

0:11:27.489,0:11:29.068
(Laughter)

0:11:31.263,0:11:34.549
If the designers had known what was[br]really happening in the real world

0:11:34.549,0:11:35.551
with their designs --

0:11:35.551,0:11:37.275
the road, the building and Barbie --

0:11:37.275,0:11:38.863
they could've used that knowledge

0:11:38.863,0:11:41.337
to create an experience[br]that was better for the user.

0:11:41.337,0:11:43.473
What's missing is a nervous system

0:11:43.473,0:11:47.182
connecting us to all of the things[br]that we design, make and use.

0:11:48.115,0:11:51.694
What if all of you had that kind[br]of information flowing to you

0:11:51.694,0:11:54.005
from the things you create[br]in the real world?

0:11:55.507,0:11:56.951
With all of the stuff we make,

0:11:56.951,0:11:59.349
we spend a tremendous amount[br]of money and energy --

0:11:59.349,0:12:01.575
in fact last year about[br]two trillion dollars --

0:12:01.575,0:12:04.298
convincing people to buy[br]the things that we've made.

0:12:04.666,0:12:07.992
But if you had this connection[br]to the things that you design and create

0:12:07.992,0:12:09.744
after they're out in the real world,

0:12:09.744,0:12:13.725
after they've been sold,[br]or launched or whatever,

0:12:13.725,0:12:15.368
we could actually change that,

0:12:15.368,0:12:18.360
and go from making people want our stuff,

0:12:18.360,0:12:21.617
to just making stuff that people[br]want in the first place.

0:12:21.818,0:12:24.629
The good news is we're working[br]on digital nervous systems

0:12:24.629,0:12:27.430
that connect us to the things we design.

0:12:28.732,0:12:32.659
We're working on one project[br]with a couple of guys down in Los Angeles

0:12:32.659,0:12:33.993
called the Bandito Brothers,

0:12:33.993,0:12:35.447
and their team,

0:12:35.447,0:12:38.903
and one of the things these guys do[br]is build insane cars

0:12:38.903,0:12:42.104
that do absolutely insane things.

0:12:42.927,0:12:44.579
These guys are crazy --

0:12:44.579,0:12:45.583
(Laughter)

0:12:45.583,0:12:47.213
in the best way.

0:12:49.061,0:12:50.980
And what we're doing with them

0:12:50.980,0:12:53.444
is taking a traditional racecar chassis

0:12:53.444,0:12:55.053
and giving it a nervous system.

0:12:55.053,0:12:58.135
So, we instrumented it[br]with dozens of sensors,

0:12:58.135,0:13:00.675
and then we put a world-class[br]driver behind the wheel,

0:13:00.675,0:13:01.885
took it out to the desert

0:13:01.885,0:13:03.831
and drove the hell out of it for a week.

0:13:04.089,0:13:07.822
And the car's nervous system captured[br]everything that was happening to the car.

0:13:07.822,0:13:10.841
We captured four billion data points ...

0:13:10.841,0:13:13.038
all of the forces[br]that it was subjected to.

0:13:13.038,0:13:15.087
And then we did something crazy.

0:13:15.363,0:13:16.791
We took all of that data,

0:13:16.791,0:13:20.638
and plugged it into a generative[br]design AI that we call, Dreamcatcher.

0:13:21.470,0:13:25.458
So, what do get when you give[br]a design tool a nervous system,

0:13:25.458,0:13:28.400
and you ask it to build you[br]the ultimate car chassis?

0:13:28.923,0:13:31.263
You get this.

0:13:32.493,0:13:36.578
This is something that human[br]could never have designed.

0:13:36.907,0:13:38.819
Except a human did design this,

0:13:38.819,0:13:42.936
but it was a human that was augmented[br]by a generative design AI,

0:13:42.936,0:13:44.294
a digital nervous system,

0:13:44.294,0:13:47.496
and robots that can actually[br]fabricate something like this.

0:13:47.880,0:13:49.724
So, if this is the future,

0:13:49.724,0:13:51.499
the Augmented Age,

0:13:51.499,0:13:55.784
and we're going to be augmented[br]cognitively, physically and perceptually,

0:13:55.784,0:13:57.483
what will that look like?

0:13:57.895,0:14:01.121
What is this wonderland going to be like?

0:14:01.121,0:14:02.854
I think we're going to see a world

0:14:02.854,0:14:05.946
where we're moving from[br]things that are fabricated

0:14:05.946,0:14:07.608
to things that are farmed.

0:14:08.201,0:14:11.775
Where we're moving from things[br]that are constructed

0:14:11.775,0:14:13.797
to that which is grown.

0:14:14.187,0:14:16.573
We're going to move from being isolated

0:14:16.573,0:14:18.834
to being connected,

0:14:18.834,0:14:21.269
and we'll move away from extraction

0:14:21.269,0:14:23.605
to embrace aggregation.

0:14:24.247,0:14:27.958
I also think we'll shift from craving[br]obedience from our things

0:14:27.958,0:14:29.906
to valuing autonomy.

0:14:30.554,0:14:32.639
Thanks to our augmented capabilities,

0:14:32.639,0:14:35.253
our world is going to change dramatically.

0:14:35.776,0:14:38.048
We're going to have a world[br]with more variety,

0:14:38.048,0:14:39.046
more connectedness,

0:14:39.046,0:14:40.131
more dynamism,

0:14:40.131,0:14:41.357
more complexity,

0:14:41.357,0:14:42.401
more adaptability,

0:14:42.401,0:14:43.699
and of course,

0:14:43.699,0:14:45.058
more beauty.

0:14:45.373,0:14:47.019
The shape of things to come

0:14:47.019,0:14:49.333
will be unlike anything[br]we've ever seen before.

0:14:49.333,0:14:50.328
Why?

0:14:50.328,0:14:52.376
Because what will be shaping those things

0:14:52.376,0:14:57.812
is this new partnership between[br]technology, nature and humanity.

0:14:59.125,0:15:03.022
That to me, is a future[br]well worth looking forward to.

0:15:03.307,0:15:04.602
Thank you all so much.

0:15:04.602,0:15:06.318
(Applause)