0:00:00.835,0:00:03.148
How many of your 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,

0:08:11.966,0:08:14.202
and that is true in certain sectors.

0:08:14.456,0:08:17.392
But I'm much more interested in this idea

0:08:17.537,0:08:22.325
that humans and robots working together[br]are going to augment each other,

0:08:22.431,0:08:24.343
and start to inhabit a new space.

0:08:24.549,0:08:26.735
This is our applied[br]research lab in San Francisco,

0:08:26.920,0:08:29.926
where one of our areas of focus[br]is advanced robotics,

0:08:30.073,0:08:32.827
specifically human-robot collaboration.

9:59:59.000,9:59:59.000
And this is Bishop,

9:59:59.000,9:59:59.000
one of our robots.

9:59:59.000,9:59:59.000
As an experiment,

9:59:59.000,9:59:59.000
we set it up to help a person working[br]in construction doing repetitive tasks.

9:59:59.000,9:59:59.000
Tasks like cutting out holes for outlets[br]or light switches in dry wall.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
So Bishop's human partner can tell[br]what to do in plain English

9:59:59.000,9:59:59.000
and simple gestures,

9:59:59.000,9:59:59.000
kind of like talking to a dog.

9:59:59.000,9:59:59.000
And then Bishop executes[br]on those instructions

9:59:59.000,9:59:59.000
with perfect precision.

9:59:59.000,9:59:59.000
We're using the human for what[br]the human is good at,

9:59:59.000,9:59:59.000
right?

9:59:59.000,9:59:59.000
Awareness, perception and desicion making.

9:59:59.000,9:59:59.000
And we're using the robot[br]for what it's good at:

9:59:59.000,9:59:59.000
precision and repetitiveness.

9:59:59.000,9:59:59.000
Here's another cool project[br]that Bishop worked on.

9:59:59.000,9:59:59.000
The goal of this project,

9:59:59.000,9:59:59.000
which we called, "The Hive,"

9:59:59.000,9:59:59.000
was the prototype the experience[br]of humans, computers and robots

9:59:59.000,9:59:59.000
all working together to solve[br]a highly complex design problem.

9:59:59.000,9:59:59.000
The humans acted as labor.

9:59:59.000,9:59:59.000
They cruised around the construction site,

9:59:59.000,9:59:59.000
they manipulated the bamboo --

9:59:59.000,9:59:59.000
which by the way,

9:59:59.000,9:59:59.000
because it's a non-icomorphic material,

9:59:59.000,9:59:59.000
is super hard for robots to deal with.

9:59:59.000,9:59:59.000
But then the robots[br]did this fiber winding,

9:59:59.000,9:59:59.000
which was almost impossible[br]for a human to do.

9:59:59.000,9:59:59.000
And then we had an AI[br]that was controlling everything.

9:59:59.000,9:59:59.000
It was telling the humans what to do,

9:59:59.000,9:59:59.000
it was tell the robots what to do,

9:59:59.000,9:59:59.000
and keeping track of thousands[br]of individual components.

9:59:59.000,9:59:59.000
What's interesting is building[br]this pavillion was simply not possible

9:59:59.000,9:59:59.000
without human, robot and AI[br]augmenting each other.

9:59:59.000,9:59:59.000
OK, I'll share one more project.

9:59:59.000,9:59:59.000
This one's a little bit crazy.

9:59:59.000,9:59:59.000
We're working with Amsterdam-based artist,[br][Youris Marvin and his team at MX3D]

9:59:59.000,9:59:59.000
to generatively design[br]and robotically print

9:59:59.000,9:59:59.000
the world's first autonomously[br]manufactured bridge.

9:59:59.000,9:59:59.000
So, Youris and an AI are designing[br]this thing right now, as we speak,

9:59:59.000,9:59:59.000
in Amsterdam.

9:59:59.000,9:59:59.000
And when we're done,

9:59:59.000,9:59:59.000
we're going to hit Go,

9:59:59.000,9:59:59.000
and robots will start 3D printing[br]in stainless steel,

9:59:59.000,9:59:59.000
and then they're going to keep printing[br]without human intervention

9:59:59.000,9:59:59.000
until the bridge is finished.

9:59:59.000,9:59:59.000
So as computers are going[br]to augment our ability

9:59:59.000,9:59:59.000
to imagine and design new stuff,

9:59:59.000,9:59:59.000
robotic systems are going to help us

9:59:59.000,9:59:59.000
build and make things that we've[br]never been able to make before.

9:59:59.000,9:59:59.000
But what about our ability[br]to sense and control these things?

9:59:59.000,9:59:59.000
What about a nervous system[br]for the things that we make?

9:59:59.000,9:59:59.000
Our nervous system --

9:59:59.000,9:59:59.000
the human nervous system --

9:59:59.000,9:59:59.000
tells everything that's[br]going on around us.

9:59:59.000,9:59:59.000
But the nervous system of the things[br]we make is rudimentary at best.

9:59:59.000,9:59:59.000
For instance,

9:59:59.000,9:59:59.000
a car doesn't tell the city's[br]Public Works department

9:59:59.000,9:59:59.000
that it just hit a pothole at the corner[br]of Broadway and Morrison;

9:59:59.000,9:59:59.000
A building doesn't tell its designers

9:59:59.000,9:59:59.000
whether or not the people[br]inside like being there,

9:59:59.000,9:59:59.000
and the toy manufacturer doesn't know[br]if a toy is actually being played with --

9:59:59.000,9:59:59.000
how and where and whether[br]or not it's any fun.

9:59:59.000,9:59:59.000
Look, I'm sure that the designers[br]imagined this lifestyle for Barbie

9:59:59.000,9:59:59.000
when they designed her --

9:59:59.000,9:59:59.000
right?

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
But what if it turns out that Barbie's[br]actually really lonely?

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
If the designers had known what was[br]really happening in the real world

9:59:59.000,9:59:59.000
with their designs --

9:59:59.000,9:59:59.000
the road, the building, the Barbie --

9:59:59.000,9:59:59.000
they could've used that knowledge

9:59:59.000,9:59:59.000
to create an experience[br]that was better for the user.

9:59:59.000,9:59:59.000
What's missing is a nervous system

9:59:59.000,9:59:59.000
connecting us to all of the things[br]that we design, make and use.

9:59:59.000,9:59:59.000
What if all of you had that kind[br]of information flowing to you

9:59:59.000,9:59:59.000
from the things you create[br]in the real world?

9:59:59.000,9:59:59.000
With all of the stuff we make,

9:59:59.000,9:59:59.000
we spend a tremendous amount[br]of money and energy --

9:59:59.000,9:59:59.000
in fact last year about[br]two trillion dollars --

9:59:59.000,9:59:59.000
convincing people to buy[br]the things that we've made.

9:59:59.000,9:59:59.000
But if you had this connection[br]to the things that you design and create,

9:59:59.000,9:59:59.000
after they're out in the real world,

9:59:59.000,9:59:59.000
after they've been sold,[br]or launched or whatever,

9:59:59.000,9:59:59.000
we could actually change that,

9:59:59.000,9:59:59.000
and go from making people want our stuff,

9:59:59.000,9:59:59.000
to just making stuff that people want[br]in the first place.

9:59:59.000,9:59:59.000
The good news is we're working[br]on digital nervous systems

9:59:59.000,9:59:59.000
that connect us to the things we design.

9:59:59.000,9:59:59.000
We're working on one project[br]with a couple of guys down in Los Angeles

9:59:59.000,9:59:59.000
called the Bandito Brothers,

9:59:59.000,9:59:59.000
and their team,

9:59:59.000,9:59:59.000
and one of the things these guys do[br]is build insane cars

9:59:59.000,9:59:59.000
that do absolutely insane things.

9:59:59.000,9:59:59.000
These guys are crazy.

9:59:59.000,9:59:59.000
(Laughter)

9:59:59.000,9:59:59.000
In the best way.

9:59:59.000,9:59:59.000
And what we're doing with them

9:59:59.000,9:59:59.000
is taking a traditions racecar [Chassy],

9:59:59.000,9:59:59.000
and giving it a nervous system.

9:59:59.000,9:59:59.000
So we instrumented it[br]with dozens of censors,

9:59:59.000,9:59:59.000
and then we put a world-class driver[br]behind the wheel,

9:59:59.000,9:59:59.000
took it out to the desert

9:59:59.000,9:59:59.000
and drove the hell out of it for a week.

9:59:59.000,9:59:59.000
And the car's nervous system captured[br]everything that was happening to car.

9:59:59.000,9:59:59.000
We captured four billion data points.

9:59:59.000,9:59:59.000
All of the forces[br]that it was subjected to.

9:59:59.000,9:59:59.000
And then we did something crazy.

9:59:59.000,9:59:59.000
We took all of that data,

9:59:59.000,9:59:59.000
and plugged it into a generative[br]design AI that we call, "Dreamcatcher."

9:59:59.000,9:59:59.000
So what do get when you give[br]a design tool a nervous system,

9:59:59.000,9:59:59.000
and you ask it to build you[br]the ultimate car [chassy]?

9:59:59.000,9:59:59.000
You get this.

9:59:59.000,9:59:59.000
This is something that human[br]could never have designed.

9:59:59.000,9:59:59.000
Except a human did design this,

9:59:59.000,9:59:59.000
but it was a human that was augmented[br]by a generative design AI,

9:59:59.000,9:59:59.000
a digital nervous system,

9:59:59.000,9:59:59.000
and robots that can actually[br]fabricate something like this.

9:59:59.000,9:59:59.000
So if this is the future,

9:59:59.000,9:59:59.000
the Augmented Age,

9:59:59.000,9:59:59.000
and we're going to be augemented[br]cognitively, physically and perceptually,

9:59:59.000,9:59:59.000
what will that look like?

9:59:59.000,9:59:59.000
What is this wonderland going to be like?

9:59:59.000,9:59:59.000
I think we're going to see a world

9:59:59.000,9:59:59.000
where we're moving from[br]things that are fabricated

9:59:59.000,9:59:59.000
to things that are farmed.

9:59:59.000,9:59:59.000
Where we're moving from things[br]that are constructed

9:59:59.000,9:59:59.000
to that which is grown.

9:59:59.000,9:59:59.000
We're going to move from being isolated

9:59:59.000,9:59:59.000
to being connected,

9:59:59.000,9:59:59.000
and we'll move away from extraction

9:59:59.000,9:59:59.000
to embrace aggregation.

9:59:59.000,9:59:59.000
I also think we'll shift from craving[br]obedience from our things

9:59:59.000,9:59:59.000
to valuing autonomy.

9:59:59.000,9:59:59.000
Thanks to our augmented capabilities,

9:59:59.000,9:59:59.000
our world is going to change dramatically.

9:59:59.000,9:59:59.000
We're going to have a world[br]with more variety,

9:59:59.000,9:59:59.000
more connectedness,

9:59:59.000,9:59:59.000
more dynamism,

9:59:59.000,9:59:59.000
more complexity,

9:59:59.000,9:59:59.000
more adaptability,

9:59:59.000,9:59:59.000
and of course,

9:59:59.000,9:59:59.000
more beauty.

9:59:59.000,9:59:59.000
The shape of things to come

9:59:59.000,9:59:59.000
will be unlike anything[br]we've ever seen before.

9:59:59.000,9:59:59.000
Why?

9:59:59.000,9:59:59.000
Because what will be shaping those things

9:59:59.000,9:59:59.000
is this new partnership between[br]technology, nature and humanity.

9:59:59.000,9:59:59.000
That to me is a future[br]well worth looking forward to.

9:59:59.000,9:59:59.000
Thank you all so much.

9:59:59.000,9:59:59.000
(Applause)