0:00:01.078,0:00:04.627
The world is filled with [br]incredible objects

0:00:04.627,0:00:07.483
and rich cultural heritage.

0:00:07.483,0:00:09.643
And when we get access to them,

0:00:09.643,0:00:12.659
we are blown away, we fall in love.

0:00:12.659,0:00:14.473
But most of the time,

0:00:14.473,0:00:20.233
the world's population is living[br]without real access to arts and culture.

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What might the connections be

0:00:22.429,0:00:25.523
when we start exploring our heritage,

0:00:25.523,0:00:29.710
the beautiful locations[br]and the art in this world.

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Before we get started [br]in this presentation,

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I just want to take care[br]of a few housekeeping points.

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First, I am no expert in art or culture.

0:00:39.223,0:00:42.556
I fell into this by mistake,[br]but I'm loving it.

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Secondly, all of what I'm going[br]to show you

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belongs to the amazing museums,[br]archives and foundations

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that we partner with.

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None of this belongs to Google.

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And finally, what you see[br]behind me

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is available right now[br]on your mobile phones,

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on your laptops.

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This is our current platform [br]where you can explore

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thousands of museums[br]and objects at your finger tips

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in extremely high-definition detail.

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The diversity of the content is what's[br]is what's amazing.

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If we just had European paintings,

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if we just had modern art,

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I think it gets a bit boring.

0:01:18.458,0:01:22.404
For example, we, this month, [br]launched the Black History channel

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with 82 curated exhibitions,

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which talk about arts and culture[br]in that community.

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We also have some amazing objects[br]from Japan

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around craftsmanship in Japan[br]called "Made in Japan".

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And one of my favorite exhibitions,[br]

0:01:39.322,0:01:41.827
which actually is the idea [br]of my talk,

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is I didn't expect to become[br]a fan of Japanese dolls.

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But, I am.

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And thanks to this exhibition[br]that has really taught me

0:01:50.561,0:01:54.635
what is the craftsmanship [br]behind the soul of a Japanese doll.

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Trust me, it's very exciting.

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Take my word for it.

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So, moving on swiftly,

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one quick thing I wanted to showcase[br]in this platform,

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which you can share with [br]your kids and your friends right now,

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is you can travel to all these[br]amazing institutions virtually as well.

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So one of our recent ideas was with[br]The Guggenheim Museum in New York

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where you can actually get a taste[br]of what it might feel like

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to actually be there.

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You can actually go to the ground floor[br]

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and obviously, most of you, I assume,[br]have been there.

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And you can see the architectural[br]masterpiece that it is.

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But imagine this accesibility[br]for a kid in Bombay

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who's studying architecture,

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who hasn't had a chance[br]to go to The Guggenheim as yet.

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You can obviously look at objects[br]in the Guggenheim Museum,

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you can obviously get in to them[br]and so on and so forth.

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There's a lot of information here.

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But this is not the purpose[br]of my talk today.

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This exists right now.

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What we now have are [br]the building blocks

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to a very exciting future[br]

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when it comes to arts and culture

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and accessibility to arts and culture.

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So I am joined today on stage[br]by my good friend and artist in residence

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at our office in Paris, ?

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who is the professor of interactive design

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at Ecal University in [br]Lausanne, Switzerland.

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What ? and our team of engineers[br]have been doing[br]

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is trying to find these connections[br]and visualize a few of these.

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So I'm going to go quite quick now.

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Just clarification:

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Always, seeing the real thing[br]is better.

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In case people try to think [br]I'm replicating the real thing.

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So moving on,

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this object you see behind me

0:03:27.270,0:03:28.895
is the Venus of Berekhat Ram.

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It's one of the oldest objects[br]in the world,

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around 233,000 years ago

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found in the Golan Heights

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and currently residing in [br]the Israel Museum in Jerusalem.

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It is also one of the oldest objects[br]on our platform.

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So let's zoom.

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We start from this one object.

0:03:44.186,0:03:46.746
And what if we zoomed out[br]

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and actually tried to experience[br]our own cultural big bang.

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What might that look like?

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This is what we deal with[br]on a daily basis

0:03:56.460,0:03:57.418
at The Cultural Institute.

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Over 6 million cultural artifacts[br]curated and given to us by institutions

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to actually make these connections.

0:04:04.311,0:04:05.734
You can travel through time,

0:04:05.734,0:04:09.107
you can understand more [br]about our society through these.

0:04:09.107,0:04:13.806
You can obviously look at it[br]from the perspective of our planet

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and try to see how it might look[br]without borders

0:04:16.428,0:04:19.047
if we just organized art and culture.

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We can also, then, plot it by time,

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which obviously, for the data geek[br]in me is very fascinating.

0:04:25.403,0:04:28.813
And you can spend hours looking[br]at every decade

0:04:28.813,0:04:32.153
and the contributions[br]in that decade and in those years

0:04:32.153,0:04:34.510
for art history and cultures.

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We would love to spend hours[br]showing you each and every decade,

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but we don't have the time right now.

0:04:39.798,0:04:42.261
So you can go on your phone[br]and actually do it yourseld.

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(Applause)

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But if you don't mind,

0:04:48.230,0:04:49.769
and you can hold your applause[br]'till later,

0:04:49.769,0:04:50.986
I don't want to run out of time

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because I want to show you[br]a lot of really cool stuff.

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(Laughter)

0:04:53.726,0:04:54.670
So just very quickly,

0:04:54.670,0:04:56.126
you can move on from here

0:04:56.126,0:04:58.940
to another very interesting idea.

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Beyond the pretty picture,

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beyond the nice visualization,

0:05:02.570,0:05:04.920
what is the purpose, how is this useful?

0:05:04.920,0:05:09.400
This next idea comes from [br]discussions with curators

0:05:09.400,0:05:11.053
that we've been having with museums,

0:05:11.053,0:05:12.730
who, by the way, I've fallen in love with

0:05:12.730,0:05:16.256
because they get their whole life[br]to actually try to tell these stories.

0:05:16.256,0:05:17.825
And one of the curators told me,

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"Amit, what would it be like

0:05:19.553,0:05:22.056
if you could create [br]a virtual curator's table

0:05:22.056,0:05:24.383
where all these 6 million objects[br]

0:05:24.383,0:05:28.952
are displayed in a way for us[br]to look at the connections between them.

0:05:28.952,0:05:30.307
And let's start --

0:05:30.307,0:05:32.787
you can spend a lot of time,[br]trust me, looking at different objects

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and understanding where they come from,

0:05:34.736,0:05:37.066
it's a crazy matric experience.

0:05:37.066,0:05:39.340
Just moving on,

0:05:39.340,0:05:42.225
let's take the world-famous [br]Vincent Van Gogh

0:05:42.225,0:05:46.477
who is very well represented[br]on this platform.

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Thanks to the diversity[br]of the institutions we have,

0:05:50.420,0:05:54.791
we have over 211 high-definition,[br]amazing artworks by this artist

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now organized in one [br]beautiful view.

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And as it ? [br]

0:06:00.291,0:06:01.787
and as the seril goes deeper

0:06:01.787,0:06:03.882
you can see all the self-portraits,

0:06:03.882,0:06:05.607
you can see still life.

0:06:05.607,0:06:07.637
But I just wanted to highlight[br]one very quick example

0:06:07.637,0:06:09.887
which is very timely:

0:06:09.887,0:06:11.191
The Bedroom.

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This is an artwork where[br]three copies exist.

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One at the Van Gogh Museum[br]in Amsterdam,

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one at the d'Orsay in Paris,

0:06:17.629,0:06:19.445
and one at the Art Institute[br]in Chicago,

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which actually is currently hosting[br]a reunion

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of all three artworks physically,

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I think only for the second time ever.

0:06:26.141,0:06:30.860
But, it is united digitally and virtually[br]for anybody to look at

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in a very different way,

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and you won't get pushed[br]in the line in the crowd.

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So let's take you and let's travel[br]through the bedroom

0:06:39.635,0:06:41.894
very quickly so you can[br]experience

0:06:41.894,0:06:44.303
what we are doing for[br]every single object.

0:06:44.303,0:06:47.938
We want the image to speak[br]as much as it can

0:06:47.938,0:06:49.778
on a digital platform.

0:06:49.778,0:06:51.967
And all you need is[br]an internet connection and a computer[br]

0:06:51.967,0:06:57.139
(Applause)

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And Seril, if you can go deeper, quickly.

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I'm sorry, this is all live,

0:07:01.382,0:07:04.703
so you have to give Seril[br]a little bit of --

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and this is available for every object:

0:07:06.815,0:07:09.322
modern art, contemporary art,[br]renaissance -- you name it,

0:07:09.322,0:07:10.533
even sculpture.

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Sometimes, you don't know[br]what can attract you

0:07:15.234,0:07:21.325
to an artwork or to a museum[br]or to a cultural discovery.[br]

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So for me personally,

0:07:22.725,0:07:23.861
it was quite a challenge

0:07:23.861,0:07:26.965
because when I to make this [br]my full-time job at Google,

0:07:26.965,0:07:29.631
my mother was not very supportive.

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I love my mother,

0:07:30.783,0:07:34.420
but she thought I was wasting my life[br]with this museum stuff.

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And for her, a museum is what[br]you do when you go on vacation

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and you tick-mark and it's over, right?

0:07:39.133,0:07:41.640
And so, it took about 4 and a half years

0:07:41.640,0:07:43.963
for me to convince my lovely[br]Indian mother

0:07:43.963,0:07:45.363
that actually, this is worthwhile.

0:07:45.363,0:07:46.460
And the way I did it

0:07:46.460,0:07:49.155
was I realized one day that she[br]loves gold,

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and so I started showing her objects

0:07:51.900,0:07:54.914
that have the material gold in them

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and the first thing my mom [br]asks me is,

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"How can we buy these?"

0:07:59.887,0:08:01.714
(Laughter)

0:08:01.714,0:08:04.802
And obviously, my salary is not that high

0:08:04.802,0:08:07.290
so I was like, "We can't actually [br]do that, mom.

0:08:07.290,0:08:09.633
But you can explore them virtually."

0:08:09.633,0:08:10.935
And so now my mom --

0:08:10.935,0:08:13.866
every time I meet she's like,[br]"Any more gold,

0:08:13.866,0:08:15.326
any more silver in your project?

0:08:15.326,0:08:16.383
Can you show me?"

0:08:16.383,0:08:18.002
And that's the idea I'm trying[br]to illustrate.

0:08:18.002,0:08:20.632
It does not matter how you get in,

0:08:20.632,0:08:22.086
as long as you get in.

0:08:22.086,0:08:23.652
Once you get in, you're hooked.

0:08:23.652,0:08:26.025
Moving on from here very quickly,

0:08:26.025,0:08:29.040
there is kind of a playful idea,[br]actually,

0:08:29.040,0:08:30.471
to illustrate the point of access,

0:08:30.471,0:08:32.382
and I'm going to go quite quickly[br]on this one.

0:08:32.382,0:08:38.592
We all know that seeing the artwork[br]in-person is amazing.

0:08:38.592,0:08:41.041
But we also know that most of us[br]can't do it,

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and the ones that can afford to do it,

0:08:43.055,0:08:44.137
it's complicated.

0:08:44.137,0:08:47.062
So Seril, can we just load up[br]our art trip,

0:08:47.062,0:08:47.856
what do we call it?

0:08:47.856,0:08:49.184
We don't have a good name for this.

0:08:49.184,0:08:52.062
But essentially, let's. --

0:08:52.062,0:08:55.135
so we have around 1,000[br]amazing institutions, 60 countries.

0:08:55.135,0:08:57.637
But let's start with Rembrandt,

0:08:57.637,0:08:59.671
we might have time for only[br]one example.

0:08:59.671,0:09:01.536
But thanks to the diversity,

0:09:01.536,0:09:05.797
we have around 500 amazing[br]Rembrandt object artworks

0:09:05.797,0:09:08.090
from 46 institutions[br]and 17 countries.

0:09:08.090,0:09:10.666
And let's say you on your next vacation

0:09:10.666,0:09:12.740
want to go see every single one of them.

0:09:12.740,0:09:14.176
That is your itinerary,

0:09:14.176,0:09:18.151
you will probably travel[br]53,000 kilometers,

0:09:18.151,0:09:20.724
visit around, I think, [br]46 institutions,

0:09:20.724,0:09:29.092
and just FYI, you might release[br]10 tons of CO2 emissions.

0:09:29.092,0:09:30.109
(Laughter)

0:09:30.109,0:09:30.774
But remember, it's art,

0:09:30.774,0:09:31.783
so you can justify it, perhaps,[br]in some way.

0:09:31.783,0:09:33.104
Moving on swiftly from here

0:09:33.104,0:09:35.668
is something a little bit more[br]technical and more interesting.

0:09:35.668,0:09:37.820
So all that we've shown you so far[br]uses metadata to make the connections.

0:09:37.820,0:09:42.923
But obviously we have something[br]cool nowadays

0:09:42.923,0:09:45.990
that everyone likes to talk about[br]called machine-learning.[br]

0:09:45.990,0:09:47.008
And so what we thought is,

0:09:47.008,0:09:49.071
"Let's strip out all the metadata,

0:09:49.071,0:09:52.707
let's look at what machine-learning[br]can do

0:09:52.707,0:09:55.301
based on visual recognition of[br]this entire collection."

0:09:55.301,0:10:01.271
And what we ended up with[br]is this very interesting map,

0:10:01.271,0:10:05.526
these clusters that have [br]no reference point of information

0:10:05.526,0:10:09.631
but has just used visuals to[br]cluster things together.

0:10:09.631,0:10:13.322
Each cluster is an art?[br]to itself of discovery.

0:10:13.322,0:10:15.823
But one of the clusters we want[br]to show you very quickly

0:10:15.823,0:10:18.563
is this amazing cluster[br]of portraits

0:10:18.563,0:10:20.989
that we found from museums[br]around the world.

0:10:20.989,0:10:23.024
If you could zoom in[br]a little but more Seril,

0:10:23.024,0:10:27.179
just to show you, you can [br]just be traveling through portraits.

0:10:27.179,0:10:29.499
And essentially, you can do nature,[br]you can do horses,

0:10:29.499,0:10:31.630
and clusters galore.

0:10:31.630,0:10:34.401
When we say all these portraits,[br]we were like, [br]

0:10:34.401,0:10:38.002
"Hey, can we do something[br]fun for kids,

0:10:38.002,0:10:39.664
can we just do something playful

0:10:39.664,0:10:41.678
to get people interested in portraits?"

0:10:41.678,0:10:42.795
Because I haven't really seen[br]

0:10:42.795,0:10:47.462
young kids really excited [br]to go to a portrait gallery.

0:10:47.462,0:10:49.048
So I want to try to [br]figure something out.

0:10:49.048,0:10:51.464
So we created something[br]called the portrait matcher.

0:10:51.464,0:10:53.005
It's quite self-explnatory,

0:10:53.005,0:10:56.284
so i'm just going to let Seril[br]show his beautiful face.

0:10:56.284,0:10:58.122
And essentially what's happening

0:10:58.122,0:11:00.345
is with the movement of his head,

0:11:00.345,0:11:04.721
we are matching different portraits[br]around the world from museums.

0:11:04.721,0:11:07.609
(Applause)

0:11:07.609,0:11:18.535
And I don't know about you,

0:11:18.535,0:11:20.202
but I've shown it to my nephew

0:11:20.202,0:11:23.389
and the reaction is just phenominal.

0:11:23.389,0:11:27.957
All they ask me is when [br]can we go see this.

0:11:27.957,0:11:29.436
And by the way, if you're nice,

0:11:29.436,0:11:33.737
maybe Seril you can smile[br]and find a happy one.

0:11:33.737,0:11:34.826
Oh, perfect.

0:11:34.826,0:11:36.838
And by the way, this is not rehearsed.

0:11:36.838,0:11:39.911
Congrats, Seril.

0:11:39.911,0:11:43.234
Let's move on.

0:11:43.234,0:11:44.309
Otherwise, this will [br]take the whole time.

0:11:44.309,0:11:48.243
So, art and culture can be fun, also.

0:11:48.243,0:11:51.820
So for our last quick experiment --

0:11:51.820,0:11:53.468
we call all of these experiments --

0:11:53.468,0:11:56.480
our last quick experiment[br]comes bck to machine learning.

0:11:56.480,0:11:59.326
So we show you clusters,[br]visual clusters,

0:11:59.326,0:12:01.986
but what if we could ask[br]the machine

0:12:01.986,0:12:04.142
to also name these clusters?

0:12:04.142,0:12:06.779
What if it could automatically[br]tag them

0:12:06.779,0:12:08.869
using no actual metadata?

0:12:08.869,0:12:13.009
So what we have is this kind[br]of explorer

0:12:13.009,0:12:16.763
where we have managed to[br]match around 4,000 labels

0:12:16.763,0:12:19.972
and we haven't really[br]done anything special here,

0:12:19.972,0:12:21.819
just feed the collection,

0:12:21.819,0:12:23.553
and we found interesting categories.

0:12:23.553,0:12:26.173
We can start with horses,[br]very straightforward catgeory.

0:12:26.173,0:12:28.357
You would expect to see[br]that the machine

0:12:28.357,0:12:30.371
has put images of horses, right?

0:12:30.371,0:12:31.632
It has.

0:12:31.632,0:12:33.694
But you also notice right over there

0:12:33.694,0:12:35.883
that it has a very abstract image[br]

0:12:35.883,0:12:38.958
that it has still managed to recognize[br]and cluster as horses.

0:12:38.958,0:12:41.514
We also have an amazing head[br]in terms of a horse.

0:12:41.514,0:12:46.094
And each one has the tags[br]as to why it got categorized.

0:12:46.094,0:12:50.659
So let's move to another one [br]which I found very funny and interesting,

0:12:50.659,0:12:53.078
because I don't understand how[br]this category came up.

0:12:53.078,0:12:55.171
It's called Lady in Waiting.

0:12:55.171,0:12:57.935
If Seril, you do it very quickly,

0:12:57.935,0:13:01.410
you will see that we have [br]these amazing images

0:13:01.410,0:13:04.210
of ladies, I guess, in waiting[br]or posing,

0:13:04.210,0:13:05.535
I don't really understand it

0:13:05.535,0:13:06.565
(Laughter)

0:13:06.565,0:13:07.665
But I've been trying to ask[br]my museum contacts

0:13:07.665,0:13:09.899
what is this, what's going on here,

0:13:09.899,0:13:11.777
and it's fascinating.

0:13:11.777,0:13:14.079
Coming back to gold very quickly,

0:13:14.079,0:13:16.101
I wanted to search for gold

0:13:16.101,0:13:18.196
and see how the machine [br]tagged all the gold,

0:13:18.196,0:13:20.666
but actually, it doesn't tag it as gold.

0:13:20.666,0:13:22.048
We are living in popular times.

0:13:22.048,0:13:24.400
It tags it as "bling bling".

0:13:24.400,0:13:26.326
(Laughter)

0:13:26.326,0:13:30.702
I'm being hard on Seril [br]because I'm moving too fast.

0:13:30.702,0:13:33.079
Essentially, here you have[br]all the bling bling

0:13:33.079,0:13:36.311
of the world's museums[br]organized for you.

0:13:36.311,0:13:39.721
And finally to end this talk[br]and these experiments,

0:13:39.721,0:13:43.130
what I hope you feel after this talk[br]is happiness and emotion.

0:13:43.130,0:13:45.420
And what would we see[br]when we see happiness?

0:13:45.420,0:13:49.077
If we actually look at[br]all the objects

0:13:49.077,0:13:50.582
that have been tagged under happines,

0:13:50.582,0:13:53.825
you would expect happiness,[br]I guess.

0:13:53.825,0:13:55.655
But there was one that [br]came up

0:13:55.655,0:14:01.556
that was very fascinating[br]and interesting

0:14:01.556,0:14:04.438
which was this artwork[br]by Douglas Coupland,

0:14:04.438,0:14:06.618
our friend and artist in residence[br]as well

0:14:06.618,0:14:08.856
called "I Miss My Pre-Internet Brain".

0:14:08.856,0:14:10.345
I don't know why the machine[br]feels like

0:14:10.345,0:14:12.332
it misses it's pre-Internet brain,

0:14:12.332,0:14:13.718
it's been tagged here.

0:14:13.718,0:14:16.316
But you know, it's a very[br]interesting part.

0:14:16.316,0:14:17.778
I sometimes do miss[br]my pre-Internet brain,

0:14:17.778,0:14:20.872
but now when it comes[br]to exploring arts and culture online.

0:14:20.872,0:14:22.775
So take out your phones,[br]take out your computers,

0:14:22.775,0:14:23.687
go visit museums.

0:14:23.687,0:14:26.763
And just a quick call-out[br]to all the amazing archivists,

0:14:26.763,0:14:28.425
historians, curators,

0:14:28.425,0:14:31.420
who are sitting in museums[br]preserving all this culture.

0:14:31.420,0:14:34.153
And the least we can do is get[br]our daily dose of art and culture

0:14:34.153,0:14:35.918
for ourselves and our kids.

0:14:35.918,0:14:36.682
Thank you.

0:14:36.682,0:14:47.536
(Applause)