1 00:00:00,878 --> 00:00:04,403 The world is filled with incredible objects 2 00:00:04,427 --> 00:00:06,355 and rich cultural heritage. 3 00:00:07,283 --> 00:00:09,419 And when we get access to them, 4 00:00:09,443 --> 00:00:11,827 we are blown away, we fall in love. 5 00:00:12,652 --> 00:00:14,249 But most of the time, 6 00:00:14,273 --> 00:00:19,065 the world's population is living without real access to arts and culture. 7 00:00:19,946 --> 00:00:25,299 What might the connections be when we start exploring our heritage, 8 00:00:25,323 --> 00:00:28,530 the beautiful locations and the art in this world? 9 00:00:29,427 --> 00:00:32,201 Before we get started in this presentation, 10 00:00:32,225 --> 00:00:35,200 I just want to take care of a few housekeeping points. 11 00:00:35,651 --> 00:00:38,999 First, I am no expert in art or culture. 12 00:00:39,023 --> 00:00:41,749 I fell into this by mistake, but I'm loving it. 13 00:00:42,356 --> 00:00:45,352 Secondly, all of what I'm going to show you 14 00:00:45,376 --> 00:00:49,341 belongs to the amazing museums, archives and foundations 15 00:00:49,365 --> 00:00:50,791 that we partner with. 16 00:00:50,815 --> 00:00:52,671 None of this belongs to Google. 17 00:00:53,235 --> 00:00:56,424 And finally, what you see behind me 18 00:00:56,448 --> 00:00:59,799 is available right now on your mobile phones, 19 00:00:59,823 --> 00:01:00,997 on your laptops. 20 00:01:01,021 --> 00:01:03,425 This is our current platform, where you can explore 21 00:01:03,449 --> 00:01:06,860 thousands of museums and objects at your fingertips, 22 00:01:06,884 --> 00:01:09,395 in extremely high-definition detail. 23 00:01:09,419 --> 00:01:12,312 The diversity of the content is what's amazing. 24 00:01:12,336 --> 00:01:14,505 If we just had European paintings, 25 00:01:14,529 --> 00:01:16,260 if we just had modern art, 26 00:01:16,284 --> 00:01:18,086 I think it gets a bit boring. 27 00:01:18,110 --> 00:01:21,969 For example, this month, we launched the "Black History" channel 28 00:01:21,993 --> 00:01:24,582 with 82 curated exhibitions, 29 00:01:24,606 --> 00:01:28,172 which talk about arts and culture in that community. 30 00:01:28,196 --> 00:01:31,819 We also have some amazing objects from Japan, 31 00:01:31,843 --> 00:01:35,947 centered around craftsmanship, called "Made in Japan." 32 00:01:35,971 --> 00:01:39,098 And one of my favorite exhibitions, 33 00:01:39,122 --> 00:01:41,527 which actually is the idea of my talk, 34 00:01:41,551 --> 00:01:45,414 is -- I didn't expect to become a fan of Japanese dolls. 35 00:01:45,438 --> 00:01:48,602 But I am, thanks to this exhibition, 36 00:01:48,626 --> 00:01:52,111 that has really taught me about the craftsmanship 37 00:01:52,135 --> 00:01:54,257 behind the soul of a Japanese doll. 38 00:01:54,281 --> 00:01:56,509 Trust me, it's very exciting. 39 00:01:56,533 --> 00:01:57,881 Take my word for it. 40 00:01:57,905 --> 00:01:59,914 So, moving on swiftly. 41 00:01:59,938 --> 00:02:02,770 One quick thing I wanted to showcase in this platform, 42 00:02:02,794 --> 00:02:05,729 which you can share with your kids and your friends right now, 43 00:02:05,753 --> 00:02:10,009 is you can travel to all these amazing institutions virtually, as well. 44 00:02:10,033 --> 00:02:13,619 One of our recent ideas was with The Guggenheim Museum in New York, 45 00:02:13,643 --> 00:02:17,001 where you can get a taste of what it might feel like 46 00:02:17,025 --> 00:02:18,176 to actually be there. 47 00:02:18,200 --> 00:02:19,967 You can go to the ground floor 48 00:02:19,991 --> 00:02:22,680 and obviously, most of you, I assume, have been there. 49 00:02:22,704 --> 00:02:25,441 And you can see the architectural masterpiece that it is. 50 00:02:25,465 --> 00:02:28,559 But imagine this accessibility for a kid in Bombay 51 00:02:28,583 --> 00:02:30,303 who's studying architecture, 52 00:02:30,327 --> 00:02:33,382 who hasn't had a chance to go to The Guggenheim as yet. 53 00:02:33,406 --> 00:02:36,491 You can obviously look at objects in the Guggenheim Museum, 54 00:02:36,515 --> 00:02:39,233 you can obviously get into them and so on and so forth. 55 00:02:39,257 --> 00:02:41,132 There's a lot of information here. 56 00:02:41,156 --> 00:02:45,005 But this is not the purpose of my talk today. 57 00:02:45,543 --> 00:02:47,309 This exists right now. 58 00:02:47,333 --> 00:02:51,259 What we now have are the building blocks to a very exciting future, 59 00:02:51,283 --> 00:02:52,998 when it comes to arts and culture 60 00:02:53,022 --> 00:02:55,633 and accessibility to arts and culture. 61 00:02:55,657 --> 00:03:00,125 So I am joined today onstage by my good friend and artist in residence 62 00:03:00,149 --> 00:03:02,492 at our office in Paris, Cyril Diagne, 63 00:03:02,516 --> 00:03:04,645 who is the professor of interactive design 64 00:03:04,669 --> 00:03:07,306 at ECAL University in Lausanne, Switzerland. 65 00:03:07,330 --> 00:03:09,944 What Cyril and our team of engineers have been doing 66 00:03:09,968 --> 00:03:13,103 is trying to find these connections and visualize a few of these. 67 00:03:13,127 --> 00:03:14,940 So I'm going to go quite quick now. 68 00:03:14,964 --> 00:03:18,566 This object you see behind me -- oh, just clarification: 69 00:03:18,590 --> 00:03:20,541 Always, seeing the real thing is better. 70 00:03:20,565 --> 00:03:23,428 In case people think I'm trying to replicate the real thing. 71 00:03:23,452 --> 00:03:24,659 So, moving on. 72 00:03:25,155 --> 00:03:28,671 This object you see behind me is the Venus of Berekhat Ram. 73 00:03:28,695 --> 00:03:30,771 It's one of the oldest objects in the world, 74 00:03:30,795 --> 00:03:33,969 found in the Golan Heights around 233,000 years ago, 75 00:03:33,993 --> 00:03:37,122 and currently residing at the Israel Museum in Jerusalem. 76 00:03:37,146 --> 00:03:39,767 It is also one of the oldest objects on our platform. 77 00:03:40,322 --> 00:03:41,668 So let's zoom. 78 00:03:41,692 --> 00:03:43,457 We start from this one object. 79 00:03:43,986 --> 00:03:46,522 What if we zoomed out 80 00:03:46,546 --> 00:03:51,052 and actually tried to experience our own cultural big bang? 81 00:03:51,076 --> 00:03:52,654 What might that look like? 82 00:03:53,474 --> 00:03:57,131 This is what we deal with on a daily basis at the Cultural Institute -- 83 00:03:57,155 --> 00:04:02,117 over six million cultural artifacts curated and given to us by institutions, 84 00:04:02,141 --> 00:04:04,087 to actually make these connections. 85 00:04:04,111 --> 00:04:05,510 You can travel through time, 86 00:04:05,534 --> 00:04:09,045 you can understand more about our society through these. 87 00:04:09,069 --> 00:04:13,469 You can look at it from the perspective of our planet, 88 00:04:13,493 --> 00:04:16,128 and try to see how it might look without borders, 89 00:04:16,152 --> 00:04:18,823 if we just organized art and culture. 90 00:04:18,847 --> 00:04:21,075 We can also then plot it by time, 91 00:04:21,099 --> 00:04:25,179 which obviously, for the data geek in me, is very fascinating. 92 00:04:25,203 --> 00:04:28,589 You can spend hours looking at every decade 93 00:04:28,613 --> 00:04:31,929 and the contributions in that decade and in those years 94 00:04:31,953 --> 00:04:34,286 for art, history and cultures. 95 00:04:34,310 --> 00:04:37,689 We would love to spend hours showing you each and every decade, 96 00:04:37,713 --> 00:04:39,574 but we don't have the time right now. 97 00:04:39,598 --> 00:04:42,857 So you can go on your phone and actually do it yourself. 98 00:04:42,881 --> 00:04:46,343 (Applause) 99 00:04:46,367 --> 00:04:49,469 But if you don't mind and can hold your applause till later, 100 00:04:49,493 --> 00:04:51,041 I don't want to run out of time, 101 00:04:51,065 --> 00:04:53,264 because I want to show you a lot of cool stuff. 102 00:04:53,288 --> 00:04:54,788 So, just very quickly: 103 00:04:54,812 --> 00:04:58,798 you can move on from here to another very interesting idea. 104 00:04:58,822 --> 00:05:00,533 Beyond the pretty picture, 105 00:05:00,557 --> 00:05:02,346 beyond the nice visualization, 106 00:05:02,370 --> 00:05:04,697 what is the purpose, how is this useful? 107 00:05:04,721 --> 00:05:09,450 This next idea comes from discussions with curators 108 00:05:09,474 --> 00:05:11,109 that we've been having at museums, 109 00:05:11,133 --> 00:05:13,156 who, by the way, I've fallen in love with, 110 00:05:13,180 --> 00:05:16,374 because they dedicate their whole life to try to tell these stories. 111 00:05:16,398 --> 00:05:19,329 One of the curators told me, "Amit, what would it be like 112 00:05:19,353 --> 00:05:21,832 if you could create a virtual curator's table 113 00:05:21,856 --> 00:05:24,159 where all these six million objects 114 00:05:24,183 --> 00:05:28,586 are displayed in a way for us to look at the connections between them?" 115 00:05:28,610 --> 00:05:32,639 You can spend a lot of time, trust me, looking at different objects 116 00:05:32,663 --> 00:05:34,616 and understanding where they come from. 117 00:05:34,640 --> 00:05:36,848 It's a crazy Matrix experience. 118 00:05:36,872 --> 00:05:37,886 (Laughter) 119 00:05:37,910 --> 00:05:39,196 Just moving on, 120 00:05:39,220 --> 00:05:42,391 let's take the world-famous Vincent Van Gogh, 121 00:05:42,415 --> 00:05:46,130 who is very well-represented on this platform. 122 00:05:46,154 --> 00:05:48,930 Thanks to the diversity of the institutions we have, 123 00:05:48,954 --> 00:05:54,658 we have over 211 high-definition, amazing artworks by this artist, 124 00:05:54,682 --> 00:05:58,429 now organized in one beautiful view. 125 00:05:58,453 --> 00:06:01,426 And as it resolves, and as Cyril goes deeper, 126 00:06:01,450 --> 00:06:03,659 you can see all the self-portraits, 127 00:06:03,683 --> 00:06:05,108 you can see still life. 128 00:06:05,132 --> 00:06:07,735 But I just wanted to highlight one very quick example, 129 00:06:07,759 --> 00:06:09,447 which is very timely: 130 00:06:09,471 --> 00:06:10,782 "The Bedroom." 131 00:06:10,806 --> 00:06:13,107 This is an artwork where three copies exist -- 132 00:06:13,131 --> 00:06:15,461 one at the Van Gogh Museum in Amsterdam, 133 00:06:15,485 --> 00:06:17,472 one at the Orsay in Paris 134 00:06:17,496 --> 00:06:19,430 and one at the Art Institute of Chicago, 135 00:06:19,454 --> 00:06:21,957 which, actually, currently is hosting a reunion 136 00:06:21,981 --> 00:06:23,756 of all three artworks physically, 137 00:06:23,780 --> 00:06:25,917 I think only for the second time ever. 138 00:06:25,941 --> 00:06:30,860 But, it is united digitally and virtually for anybody to look at 139 00:06:30,884 --> 00:06:32,805 in a very different way, 140 00:06:32,829 --> 00:06:35,862 and you won't get pushed in the line in the crowd. 141 00:06:35,886 --> 00:06:40,628 So let's take you and let's travel through "The Bedroom" very quickly, 142 00:06:40,652 --> 00:06:44,239 so you can experience what we are doing for every single object. 143 00:06:44,263 --> 00:06:47,714 We want the image to speak as much as it can 144 00:06:47,738 --> 00:06:49,382 on a digital platform. 145 00:06:49,406 --> 00:06:52,553 And all you need is an internet connection and a computer 146 00:06:52,577 --> 00:06:56,915 (Applause) 147 00:06:56,939 --> 00:06:59,497 And, Cyril, if you can go deeper, quickly. 148 00:06:59,521 --> 00:07:01,005 I'm sorry, this is all live, 149 00:07:01,029 --> 00:07:03,464 so you have to give Cyril a little bit of -- 150 00:07:04,401 --> 00:07:06,461 and this is available for every object: 151 00:07:06,485 --> 00:07:09,200 modern art, contemporary art, Renaissance -- you name it, 152 00:07:09,224 --> 00:07:10,411 even sculpture. 153 00:07:11,802 --> 00:07:15,397 Sometimes, you don't know what can attract you 154 00:07:15,421 --> 00:07:20,649 to an artwork or to a museum or to a cultural discovery. 155 00:07:20,673 --> 00:07:23,415 So for me, personally, it was quite a challenge 156 00:07:23,439 --> 00:07:26,661 because when I decided to make this my full-time job at Google, 157 00:07:26,685 --> 00:07:29,288 my mother was not very supportive. 158 00:07:29,312 --> 00:07:30,559 I love my mother, 159 00:07:30,583 --> 00:07:33,582 but she thought I was wasting my life with this museum stuff. 160 00:07:33,606 --> 00:07:36,918 And for her, a museum is what you do when you go on vacation 161 00:07:36,942 --> 00:07:38,909 and you tick-mark and it's over, right? 162 00:07:38,933 --> 00:07:41,464 And it took around four and a half years 163 00:07:41,488 --> 00:07:43,702 for me to convince my lovely Indian mother 164 00:07:43,726 --> 00:07:45,379 that actually, this is worthwhile. 165 00:07:45,403 --> 00:07:48,844 And the way I did it was, I realized one day that she loves gold. 166 00:07:48,868 --> 00:07:54,443 So I started showing her all objects that have the material gold in them. 167 00:07:54,467 --> 00:07:57,118 And the first thing my mom asks me is, 168 00:07:57,142 --> 00:07:59,570 "How can we buy these?" 169 00:07:59,594 --> 00:08:01,412 (Laughter) 170 00:08:01,436 --> 00:08:04,578 And obviously, my salary is not that high, 171 00:08:04,602 --> 00:08:06,980 so I was like, "We can't actually do that, mom. 172 00:08:07,004 --> 00:08:09,115 But you can explore them virtually." 173 00:08:09,139 --> 00:08:12,558 And so now my mom -- every time I meet her, she asks me, 174 00:08:12,582 --> 00:08:16,048 "Any more gold, any more silver in your project? Can you show me?" 175 00:08:16,072 --> 00:08:18,246 And that's the idea I'm trying to illustrate. 176 00:08:18,270 --> 00:08:20,408 It does not matter how you get in, 177 00:08:20,432 --> 00:08:21,794 as long as you get in. 178 00:08:21,818 --> 00:08:23,428 Once you get in, you're hooked. 179 00:08:23,452 --> 00:08:25,801 Moving on from here very quickly, 180 00:08:25,825 --> 00:08:28,674 there is kind of a playful idea, actually, 181 00:08:28,698 --> 00:08:30,333 to illustrate the point of access, 182 00:08:30,357 --> 00:08:32,779 and I'm going to go quite quickly on this one. 183 00:08:32,803 --> 00:08:38,210 We all know that seeing the artwork in person is amazing. 184 00:08:38,234 --> 00:08:40,817 But we also know that most of us can't do it, 185 00:08:40,841 --> 00:08:43,599 and the ones that can afford to do it, it's complicated. 186 00:08:43,623 --> 00:08:47,430 So -- Cyril, can we load up our art trip, what do we call it? 187 00:08:47,454 --> 00:08:49,216 We don't have a good name for this. 188 00:08:49,240 --> 00:08:54,211 But essentially, we have around 1,000 amazing institutions, 189 00:08:54,235 --> 00:08:55,402 68 countries. 190 00:08:55,426 --> 00:08:57,126 But let's start with Rembrandt. 191 00:08:57,150 --> 00:08:59,392 We might have time for only one example. 192 00:08:59,416 --> 00:09:01,645 But thanks to the diversity, 193 00:09:01,669 --> 00:09:05,573 we've got around 500 amazing Rembrandt object artworks 194 00:09:05,597 --> 00:09:07,866 from 46 institutions and 17 countries. 195 00:09:07,890 --> 00:09:10,442 Let's say that on your next vacation, 196 00:09:10,466 --> 00:09:12,516 you want to go see every single one of them. 197 00:09:12,540 --> 00:09:13,874 That is your itinerary, 198 00:09:13,898 --> 00:09:17,552 you will probably travel 53,000 kilometers, 199 00:09:17,576 --> 00:09:20,163 visit around, I think, 46 institutions, 200 00:09:20,187 --> 00:09:24,378 and just FYI, you might release 10 tons of CO2 emissions. 201 00:09:24,402 --> 00:09:25,865 (Laughter) 202 00:09:25,889 --> 00:09:27,362 But remember, it's art, 203 00:09:27,386 --> 00:09:30,051 so you can justify it, perhaps, in some way. 204 00:09:30,837 --> 00:09:32,759 Moving on swiftly from here, 205 00:09:32,783 --> 00:09:35,718 is something a little bit more technical and more interesting. 206 00:09:35,742 --> 00:09:40,679 All that we've shown you so far uses metadata to make the connections. 207 00:09:40,703 --> 00:09:42,813 But obviously we have something cool nowadays 208 00:09:42,837 --> 00:09:45,749 that everyone likes to talk about, which is machine learning. 209 00:09:45,773 --> 00:09:48,847 So what we thought is, let's strip out all the metadata, 210 00:09:48,871 --> 00:09:52,483 let's look at what machine learning can do 211 00:09:52,507 --> 00:09:56,830 based purely on visual recognition of this entire collection. 212 00:09:56,854 --> 00:10:01,047 What we ended up with is this very interesting map, 213 00:10:01,071 --> 00:10:05,381 these clusters that have no reference point information, 214 00:10:05,405 --> 00:10:09,370 but has just used visuals to cluster things together. 215 00:10:09,394 --> 00:10:12,976 Each cluster is an art to us by itself of discovery. 216 00:10:13,000 --> 00:10:15,663 But one of the clusters we want to show you very quickly 217 00:10:15,687 --> 00:10:18,339 is this amazing cluster of portraits 218 00:10:18,363 --> 00:10:20,765 that we found from museums around the world. 219 00:10:20,789 --> 00:10:22,972 If you could zoom in a little bit more, Cyril. 220 00:10:22,996 --> 00:10:26,828 Just to show you, you can just travel through portraits. 221 00:10:26,852 --> 00:10:29,626 And essentially, you can do nature, you can do horses 222 00:10:29,650 --> 00:10:31,406 and clusters galore. 223 00:10:32,309 --> 00:10:33,857 When we saw all these portraits, 224 00:10:33,881 --> 00:10:37,533 we were like, "Hey, can we do something fun for kids, 225 00:10:37,557 --> 00:10:39,239 or can we do something playful 226 00:10:39,263 --> 00:10:41,288 to get people interested in portraits?" 227 00:10:41,312 --> 00:10:43,492 Because I haven't really seen 228 00:10:43,516 --> 00:10:46,883 young kids really excited to go to a portrait gallery. 229 00:10:47,357 --> 00:10:49,289 I wanted to try to figure something out. 230 00:10:49,313 --> 00:10:51,780 So we created something called the portrait matcher. 231 00:10:51,804 --> 00:10:53,121 It's quite self-explnatory, 232 00:10:53,145 --> 00:10:55,883 so I'm just going to let Cyril show his beautiful face. 233 00:10:55,907 --> 00:11:00,039 And essentially what's happening is, with the movement of his head, 234 00:11:00,063 --> 00:11:04,230 we are matching different portraits around the world from museums. 235 00:11:04,254 --> 00:11:06,450 (Applause) 236 00:11:17,445 --> 00:11:19,151 And I don't know about you, 237 00:11:19,175 --> 00:11:21,191 but I've shown it to my nephew and sister, 238 00:11:21,215 --> 00:11:23,064 and the reaction is just phenomenal. 239 00:11:23,088 --> 00:11:25,794 All they ask me is, "When can we go see this?" 240 00:11:27,492 --> 00:11:29,065 And by the way, if we're nice, 241 00:11:29,089 --> 00:11:31,910 maybe, Cyril, you can smile and find a happy one? 242 00:11:32,696 --> 00:11:34,094 Oh, perfect. 243 00:11:34,118 --> 00:11:36,106 By the way, this is not rehearsed. 244 00:11:36,474 --> 00:11:39,054 Congrats, Cyril. Great stuff. Oh wow. 245 00:11:39,078 --> 00:11:42,554 OK, let's move on; otherwise, this will just take the whole time. 246 00:11:42,578 --> 00:11:44,296 (Applause) 247 00:11:44,320 --> 00:11:46,900 So, art and culture can be fun also, right? 248 00:11:47,900 --> 00:11:51,297 For our last quick experiment -- 249 00:11:51,321 --> 00:11:53,084 we call all of these "experiments" -- 250 00:11:53,108 --> 00:11:55,997 our last quick experiment comes back to machine learning. 251 00:11:56,021 --> 00:11:58,862 We show you clusters, visual clusters, 252 00:11:58,886 --> 00:12:03,787 but what if we could ask the machine to also name these clusters? 253 00:12:03,811 --> 00:12:08,564 What if it could automatically tag them, using no actual metadata? 254 00:12:08,588 --> 00:12:12,688 So what we have is this kind of explorer, 255 00:12:12,712 --> 00:12:16,323 where we have managed to match, I think, around 4,000 labels. 256 00:12:16,347 --> 00:12:19,511 And we haven't really done anything special here, 257 00:12:19,535 --> 00:12:21,193 just fed the collection. 258 00:12:21,217 --> 00:12:22,987 And we found interesting categories. 259 00:12:23,011 --> 00:12:25,916 We can start with horses, a very straightforward category. 260 00:12:25,940 --> 00:12:28,239 You would expect to see that the machine has put 261 00:12:28,263 --> 00:12:30,004 images of horses, right? 262 00:12:30,028 --> 00:12:33,470 And it has, but you also notice, right over there, 263 00:12:33,494 --> 00:12:35,573 that it has a very abstract image 264 00:12:35,597 --> 00:12:38,792 that it has still managed to recognize and cluster as horses. 265 00:12:38,816 --> 00:12:42,506 We also have an amazing head in terms of a horse. 266 00:12:42,530 --> 00:12:46,532 And each one has the tags as to why it got categorized in this. 267 00:12:46,556 --> 00:12:50,530 So let's move to another one which I found very funny and interesting, 268 00:12:50,554 --> 00:12:53,045 because I don't understand how this category came up. 269 00:12:53,069 --> 00:12:54,819 It's called "Lady in Waiting." 270 00:12:54,843 --> 00:12:57,455 If, Cyril, you do it very quickly, 271 00:12:57,479 --> 00:13:01,021 you will see that we have these amazing images 272 00:13:01,045 --> 00:13:03,806 of ladies, I guess, in waiting or posing. 273 00:13:03,830 --> 00:13:05,276 I don't really understand it. 274 00:13:05,300 --> 00:13:07,540 But I've been trying to ask my museum contacts, 275 00:13:07,564 --> 00:13:09,809 you know, "What is this? What's going on here?" 276 00:13:09,833 --> 00:13:11,445 And it's fascinating. 277 00:13:11,469 --> 00:13:14,158 Coming back to gold very quickly, 278 00:13:14,182 --> 00:13:15,745 I wanted to search for gold 279 00:13:15,769 --> 00:13:17,871 and see how the machine tagged all the gold. 280 00:13:17,895 --> 00:13:19,975 But, actually, it doesn't tag it as gold. 281 00:13:20,320 --> 00:13:21,835 We are living in popular times. 282 00:13:21,859 --> 00:13:23,962 It tags it as "bling-bling." 283 00:13:23,986 --> 00:13:25,800 (Laughter) 284 00:13:27,200 --> 00:13:30,121 I'm being hard on Cyril, because I'm moving too fast. 285 00:13:30,145 --> 00:13:32,772 Essentially, here you have all the bling-bling 286 00:13:32,796 --> 00:13:35,957 of the world's museums organized for you. 287 00:13:35,981 --> 00:13:39,497 And finally, to end this talk and these experiments, 288 00:13:39,521 --> 00:13:42,838 what I hope you feel after this talk is happiness and emotion. 289 00:13:42,862 --> 00:13:45,301 And what would we see when we see happiness? 290 00:13:45,325 --> 00:13:48,484 If we actually look at all the objects 291 00:13:48,508 --> 00:13:50,452 that have been tagged under "happiness," 292 00:13:50,476 --> 00:13:53,540 you would expect happiness, I guess. 293 00:13:53,564 --> 00:13:59,667 But there was one that came up that was very fascinating and interesting, 294 00:13:59,691 --> 00:14:04,066 which was this artwork by Douglas Coupland, 295 00:14:04,090 --> 00:14:06,185 our friend and artist in residence as well, 296 00:14:06,209 --> 00:14:08,470 called, "I Miss My Pre-Internet Brain." 297 00:14:08,494 --> 00:14:12,109 I don't know why the machine feels like it misses its pre-Internet brain 298 00:14:12,133 --> 00:14:13,403 and it's been tagged here, 299 00:14:13,427 --> 00:14:15,341 but it's a very interesting thought. 300 00:14:15,365 --> 00:14:17,548 I sometimes do miss my pre-Internet brain, 301 00:14:17,572 --> 00:14:20,572 but not when it comes to exploring arts and culture online. 302 00:14:20,596 --> 00:14:22,909 So take out your phones, take out your computers, 303 00:14:22,933 --> 00:14:24,090 go visit museums. 304 00:14:24,114 --> 00:14:26,793 And just a quick call-out to all the amazing archivists, 305 00:14:26,817 --> 00:14:28,201 historians, curators, 306 00:14:28,225 --> 00:14:30,997 who are sitting in museums, preserving all this culture. 307 00:14:31,021 --> 00:14:34,339 And the least we can do is get our daily dose of art and culture 308 00:14:34,363 --> 00:14:35,694 for ourselves and our kids. 309 00:14:35,718 --> 00:14:36,871 Thank you. 310 00:14:36,895 --> 00:14:47,536 (Applause)