1 00:00:01,078 --> 00:00:04,627 The world is filled with incredible objects 2 00:00:04,627 --> 00:00:07,483 and rich cultural heritage. 3 00:00:07,483 --> 00:00:09,643 And when we get access to them, 4 00:00:09,643 --> 00:00:12,659 we are blown away, we fall in love. 5 00:00:12,659 --> 00:00:14,473 But most of the time, 6 00:00:14,473 --> 00:00:20,233 the world's population is living without real access to arts and culture. 7 00:00:20,233 --> 00:00:22,429 What might the connections be 8 00:00:22,429 --> 00:00:25,523 when we start exploring our heritage, 9 00:00:25,523 --> 00:00:29,710 the beautiful locations and the art in this world. 10 00:00:29,710 --> 00:00:32,514 Before we get started in this presentation, 11 00:00:32,514 --> 00:00:35,851 I just want to take care of a few housekeeping points. 12 00:00:35,851 --> 00:00:39,223 First, I am no expert in art or culture. 13 00:00:39,223 --> 00:00:42,556 I fell into this by mistake, but I'm loving it. 14 00:00:42,556 --> 00:00:45,576 Secondly, all of what I'm going to show you 15 00:00:45,576 --> 00:00:49,565 belongs to the amazing museums, archives and foundations 16 00:00:49,565 --> 00:00:51,015 that we partner with. 17 00:00:51,015 --> 00:00:53,435 None of this belongs to Google. 18 00:00:53,435 --> 00:00:56,648 And finally, what you see behind me 19 00:00:56,648 --> 00:01:00,121 is available right now on your mobile phones, 20 00:01:00,121 --> 00:01:01,176 on your laptops. 21 00:01:01,176 --> 00:01:03,599 This is our current platform where you can explore 22 00:01:03,599 --> 00:01:07,084 thousands of museums and objects at your finger tips 23 00:01:07,084 --> 00:01:09,698 in extremely high-definition detail. 24 00:01:09,698 --> 00:01:12,536 The diversity of the content is what's is what's amazing. 25 00:01:12,536 --> 00:01:14,563 If we just had European paintings, 26 00:01:14,563 --> 00:01:16,564 if we just had modern art, 27 00:01:16,564 --> 00:01:18,458 I think it gets a bit boring. 28 00:01:18,458 --> 00:01:22,404 For example, we, this month, launched the Black History channel 29 00:01:22,404 --> 00:01:25,016 with 82 curated exhibitions, 30 00:01:25,016 --> 00:01:28,516 which talk about arts and culture in that community. 31 00:01:28,516 --> 00:01:32,126 We also have some amazing objects from Japan 32 00:01:32,126 --> 00:01:36,171 around craftsmanship in Japan called "Made in Japan". 33 00:01:36,171 --> 00:01:39,322 And one of my favorite exhibitions, 34 00:01:39,322 --> 00:01:41,827 which actually is the idea of my talk, 35 00:01:41,827 --> 00:01:45,638 is I didn't expect to become a fan of Japanese dolls. 36 00:01:45,638 --> 00:01:47,092 But, I am. 37 00:01:47,092 --> 00:01:50,561 And thanks to this exhibition that has really taught me 38 00:01:50,561 --> 00:01:54,635 what is the craftsmanship behind the soul of a Japanese doll. 39 00:01:54,635 --> 00:01:57,101 Trust me, it's very exciting. 40 00:01:57,101 --> 00:01:58,472 Take my word for it. 41 00:01:58,472 --> 00:02:00,231 So, moving on swiftly, 42 00:02:00,231 --> 00:02:03,066 one quick thing I wanted to showcase in this platform, 43 00:02:03,086 --> 00:02:06,203 which you can share with your kids and your friends right now, 44 00:02:06,203 --> 00:02:10,234 is you can travel to all these amazing institutions virtually as well. 45 00:02:10,234 --> 00:02:13,753 So one of our recent ideas was with The Guggenheim Museum in New York 46 00:02:13,753 --> 00:02:17,276 where you can actually get a taste of what it might feel like 47 00:02:17,276 --> 00:02:18,380 to actually be there. 48 00:02:18,380 --> 00:02:20,096 You can actually go to the ground floor 49 00:02:20,096 --> 00:02:22,148 and obviously, most of you, I assume, have been there. 50 00:02:22,148 --> 00:02:25,238 And you can see the architectural masterpiece that it is. 51 00:02:25,238 --> 00:02:26,691 But imagine this accesibility for a kid in Bombay 52 00:02:29,253 --> 00:02:29,503 who's studying architecture, 53 00:02:29,610 --> 00:02:34,236 who hasn't had a chance to go to The Guggenheim as yet. 54 00:02:34,236 --> 00:02:34,486 You can obviously look at objects in the Guggenheim Museum, 55 00:02:34,585 --> 00:02:39,556 you can obviously get in to them and so on and so forth. 56 00:02:39,556 --> 00:02:41,207 There's a lot of information here. 57 00:02:41,207 --> 00:02:45,989 But this is not the purpose of my talk today. 58 00:02:45,989 --> 00:02:47,778 This exists right now. 59 00:02:47,778 --> 00:02:49,881 What we now have are the building blocks 60 00:02:49,881 --> 00:02:51,537 to a very exciting future 61 00:02:51,537 --> 00:02:53,329 when it comes to arts and culture 62 00:02:53,329 --> 00:02:55,857 and accessibility to arts and culture. 63 00:02:55,857 --> 00:03:00,349 So I am joined today on stage by my good friend and artist in residence 64 00:03:00,349 --> 00:03:02,798 at our office in Paris, ? 65 00:03:02,798 --> 00:03:04,869 who is the professor of interactive design 66 00:03:04,869 --> 00:03:07,530 at Ecal University in Lausanne, Switzerland. 67 00:03:07,530 --> 00:03:09,610 What ? and our team of engineers have been doing 68 00:03:09,610 --> 00:03:13,327 is trying to find these connections and visualize a few of these. 69 00:03:13,327 --> 00:03:15,057 So I'm going to go quite quick now. 70 00:03:15,057 --> 00:03:18,798 Just clarification: 71 00:03:18,798 --> 00:03:20,519 Always, seeing the real thing is better. 72 00:03:20,519 --> 00:03:23,188 In case people try to think I'm replicating the real thing. 73 00:03:23,188 --> 00:03:25,458 So moving on, 74 00:03:25,458 --> 00:03:27,270 this object you see behind me 75 00:03:27,270 --> 00:03:28,895 is the Venus of Berekhat Ram. 76 00:03:28,895 --> 00:03:30,761 It's one of the oldest objects in the world, 77 00:03:30,761 --> 00:03:33,026 around 233,000 years ago 78 00:03:33,026 --> 00:03:35,067 found in the Golan Heights 79 00:03:35,067 --> 00:03:37,126 and currently residing in the Israel Museum in Jerusalem. 80 00:03:37,126 --> 00:03:40,604 It is also one of the oldest objects on our platform. 81 00:03:40,604 --> 00:03:41,892 So let's zoom. 82 00:03:41,892 --> 00:03:44,186 We start from this one object. 83 00:03:44,186 --> 00:03:46,746 And what if we zoomed out 84 00:03:46,746 --> 00:03:51,532 and actually tried to experience our own cultural big bang. 85 00:03:51,532 --> 00:03:53,674 What might that look like? 86 00:03:53,674 --> 00:03:56,460 This is what we deal with on a daily basis 87 00:03:56,460 --> 00:03:57,418 at The Cultural Institute. 88 00:03:57,418 --> 00:04:02,342 Over 6 million cultural artifacts curated and given to us by institutions 89 00:04:02,342 --> 00:04:04,311 to actually make these connections. 90 00:04:04,311 --> 00:04:05,734 You can travel through time, 91 00:04:05,734 --> 00:04:09,107 you can understand more about our society through these. 92 00:04:09,107 --> 00:04:13,806 You can obviously look at it from the perspective of our planet 93 00:04:13,806 --> 00:04:16,428 and try to see how it might look without borders 94 00:04:16,428 --> 00:04:19,047 if we just organized art and culture. 95 00:04:19,047 --> 00:04:21,376 We can also, then, plot it by time, 96 00:04:21,376 --> 00:04:25,403 which obviously, for the data geek in me is very fascinating. 97 00:04:25,403 --> 00:04:28,813 And you can spend hours looking at every decade 98 00:04:28,813 --> 00:04:32,153 and the contributions in that decade and in those years 99 00:04:32,153 --> 00:04:34,510 for art history and cultures. 100 00:04:34,510 --> 00:04:37,913 We would love to spend hours showing you each and every decade, 101 00:04:37,913 --> 00:04:39,798 but we don't have the time right now. 102 00:04:39,798 --> 00:04:42,261 So you can go on your phone and actually do it yourseld. 103 00:04:42,261 --> 00:04:45,981 (Applause) 104 00:04:45,981 --> 00:04:48,230 But if you don't mind, 105 00:04:48,230 --> 00:04:49,769 and you can hold your applause 'till later, 106 00:04:49,769 --> 00:04:50,986 I don't want to run out of time 107 00:04:50,986 --> 00:04:52,728 because I want to show you a lot of really cool stuff. 108 00:04:52,728 --> 00:04:53,726 (Laughter) 109 00:04:53,726 --> 00:04:54,670 So just very quickly, 110 00:04:54,670 --> 00:04:56,126 you can move on from here 111 00:04:56,126 --> 00:04:58,940 to another very interesting idea. 112 00:04:58,940 --> 00:05:00,674 Beyond the pretty picture, 113 00:05:00,674 --> 00:05:02,570 beyond the nice visualization, 114 00:05:02,570 --> 00:05:04,920 what is the purpose, how is this useful? 115 00:05:04,920 --> 00:05:09,400 This next idea comes from discussions with curators 116 00:05:09,400 --> 00:05:11,053 that we've been having with museums, 117 00:05:11,053 --> 00:05:12,730 who, by the way, I've fallen in love with 118 00:05:12,730 --> 00:05:16,256 because they get their whole life to actually try to tell these stories. 119 00:05:16,256 --> 00:05:17,825 And one of the curators told me, 120 00:05:17,825 --> 00:05:19,553 "Amit, what would it be like 121 00:05:19,553 --> 00:05:22,056 if you could create a virtual curator's table 122 00:05:22,056 --> 00:05:24,383 where all these 6 million objects 123 00:05:24,383 --> 00:05:28,952 are displayed in a way for us to look at the connections between them. 124 00:05:28,952 --> 00:05:30,307 And let's start -- 125 00:05:30,307 --> 00:05:32,787 you can spend a lot of time, trust me, looking at different objects 126 00:05:32,787 --> 00:05:34,736 and understanding where they come from, 127 00:05:34,736 --> 00:05:37,066 it's a crazy matric experience. 128 00:05:37,066 --> 00:05:39,340 Just moving on, 129 00:05:39,340 --> 00:05:42,225 let's take the world-famous Vincent Van Gogh 130 00:05:42,225 --> 00:05:46,477 who is very well represented on this platform. 131 00:05:46,477 --> 00:05:50,159 Thanks to the diversity of the institutions we have, 132 00:05:50,420 --> 00:05:54,791 we have over 211 high-definition, amazing artworks by this artist 133 00:05:54,791 --> 00:05:58,896 now organized in one beautiful view. 134 00:05:58,896 --> 00:06:00,291 And as it ? 135 00:06:00,291 --> 00:06:01,787 and as the seril goes deeper 136 00:06:01,787 --> 00:06:03,882 you can see all the self-portraits, 137 00:06:03,882 --> 00:06:05,607 you can see still life. 138 00:06:05,607 --> 00:06:07,637 But I just wanted to highlight one very quick example 139 00:06:07,637 --> 00:06:09,887 which is very timely: 140 00:06:09,887 --> 00:06:11,191 The Bedroom. 141 00:06:11,191 --> 00:06:13,493 This is an artwork where three copies exist. 142 00:06:13,493 --> 00:06:15,685 One at the Van Gogh Museum in Amsterdam, 143 00:06:15,685 --> 00:06:17,629 one at the d'Orsay in Paris, 144 00:06:17,629 --> 00:06:19,445 and one at the Art Institute in Chicago, 145 00:06:19,445 --> 00:06:22,181 which actually is currently hosting a reunion 146 00:06:22,181 --> 00:06:23,980 of all three artworks physically, 147 00:06:23,980 --> 00:06:26,141 I think only for the second time ever. 148 00:06:26,141 --> 00:06:30,860 But, it is united digitally and virtually for anybody to look at 149 00:06:30,860 --> 00:06:33,124 in a very different way, 150 00:06:33,124 --> 00:06:36,086 and you won't get pushed in the line in the crowd. 151 00:06:36,086 --> 00:06:39,635 So let's take you and let's travel through the bedroom 152 00:06:39,635 --> 00:06:41,894 very quickly so you can experience 153 00:06:41,894 --> 00:06:44,303 what we are doing for every single object. 154 00:06:44,303 --> 00:06:47,938 We want the image to speak as much as it can 155 00:06:47,938 --> 00:06:49,778 on a digital platform. 156 00:06:49,778 --> 00:06:51,967 And all you need is an internet connection and a computer 157 00:06:51,967 --> 00:06:57,139 (Applause) 158 00:06:57,139 --> 00:06:59,796 And Seril, if you can go deeper, quickly. 159 00:06:59,796 --> 00:07:01,382 I'm sorry, this is all live, 160 00:07:01,382 --> 00:07:04,703 so you have to give Seril a little bit of -- 161 00:07:04,703 --> 00:07:06,815 and this is available for every object: 162 00:07:06,815 --> 00:07:09,322 modern art, contemporary art, renaissance -- you name it, 163 00:07:09,322 --> 00:07:10,533 even sculpture. 164 00:07:10,533 --> 00:07:15,234 Sometimes, you don't know what can attract you 165 00:07:15,234 --> 00:07:21,325 to an artwork or to a museum or to a cultural discovery. 166 00:07:21,325 --> 00:07:22,725 So for me personally, 167 00:07:22,725 --> 00:07:23,861 it was quite a challenge 168 00:07:23,861 --> 00:07:26,965 because when I to make this my full-time job at Google, 169 00:07:26,965 --> 00:07:29,631 my mother was not very supportive. 170 00:07:29,631 --> 00:07:30,783 I love my mother, 171 00:07:30,783 --> 00:07:34,420 but she thought I was wasting my life with this museum stuff. 172 00:07:34,420 --> 00:07:37,142 And for her, a museum is what you do when you go on vacation 173 00:07:37,142 --> 00:07:39,133 and you tick-mark and it's over, right? 174 00:07:39,133 --> 00:07:41,640 And so, it took about 4 and a half years 175 00:07:41,640 --> 00:07:43,963 for me to convince my lovely Indian mother 176 00:07:43,963 --> 00:07:45,363 that actually, this is worthwhile. 177 00:07:45,363 --> 00:07:46,460 And the way I did it 178 00:07:46,460 --> 00:07:49,155 was I realized one day that she loves gold, 179 00:07:49,155 --> 00:07:51,900 and so I started showing her objects 180 00:07:51,900 --> 00:07:54,914 that have the material gold in them 181 00:07:54,914 --> 00:07:57,513 and the first thing my mom asks me is, 182 00:07:57,513 --> 00:07:59,887 "How can we buy these?" 183 00:07:59,887 --> 00:08:01,714 (Laughter) 184 00:08:01,714 --> 00:08:04,802 And obviously, my salary is not that high 185 00:08:04,802 --> 00:08:07,290 so I was like, "We can't actually do that, mom. 186 00:08:07,290 --> 00:08:09,633 But you can explore them virtually." 187 00:08:09,633 --> 00:08:10,935 And so now my mom -- 188 00:08:10,935 --> 00:08:13,866 every time I meet she's like, "Any more gold, 189 00:08:13,866 --> 00:08:15,326 any more silver in your project? 190 00:08:15,326 --> 00:08:16,383 Can you show me?" 191 00:08:16,383 --> 00:08:18,002 And that's the idea I'm trying to illustrate. 192 00:08:18,002 --> 00:08:20,632 It does not matter how you get in, 193 00:08:20,632 --> 00:08:22,086 as long as you get in. 194 00:08:22,086 --> 00:08:23,652 Once you get in, you're hooked. 195 00:08:23,652 --> 00:08:26,025 Moving on from here very quickly, 196 00:08:26,025 --> 00:08:29,040 there is kind of a playful idea, actually, 197 00:08:29,040 --> 00:08:30,471 to illustrate the point of access, 198 00:08:30,471 --> 00:08:32,382 and I'm going to go quite quickly on this one. 199 00:08:32,382 --> 00:08:38,592 We all know that seeing the artwork in-person is amazing. 200 00:08:38,592 --> 00:08:41,041 But we also know that most of us can't do it, 201 00:08:41,041 --> 00:08:43,055 and the ones that can afford to do it, 202 00:08:43,055 --> 00:08:44,137 it's complicated. 203 00:08:44,137 --> 00:08:47,062 So Seril, can we just load up our art trip, 204 00:08:47,062 --> 00:08:47,856 what do we call it? 205 00:08:47,856 --> 00:08:49,184 We don't have a good name for this. 206 00:08:49,184 --> 00:08:52,062 But essentially, let's. -- 207 00:08:52,062 --> 00:08:55,135 so we have around 1,000 amazing institutions, 60 countries. 208 00:08:55,135 --> 00:08:57,637 But let's start with Rembrandt, 209 00:08:57,637 --> 00:08:59,671 we might have time for only one example. 210 00:08:59,671 --> 00:09:01,536 But thanks to the diversity, 211 00:09:01,536 --> 00:09:05,797 we have around 500 amazing Rembrandt object artworks 212 00:09:05,797 --> 00:09:08,090 from 46 institutions and 17 countries. 213 00:09:08,090 --> 00:09:10,666 And let's say you on your next vacation 214 00:09:10,666 --> 00:09:12,740 want to go see every single one of them. 215 00:09:12,740 --> 00:09:14,176 That is your itinerary, 216 00:09:14,176 --> 00:09:18,151 you will probably travel 53,000 kilometers, 217 00:09:18,151 --> 00:09:20,724 visit around, I think, 46 institutions, 218 00:09:20,724 --> 00:09:29,092 and just FYI, you might release 10 tons of CO2 emissions. 219 00:09:29,092 --> 00:09:30,109 (Laughter) 220 00:09:30,109 --> 00:09:30,774 But remember, it's art, 221 00:09:30,774 --> 00:09:31,783 so you can justify it, perhaps, in some way. 222 00:09:31,783 --> 00:09:33,104 Moving on swiftly from here 223 00:09:33,104 --> 00:09:35,668 is something a little bit more technical and more interesting. 224 00:09:35,668 --> 00:09:37,820 So all that we've shown you so far uses metadata to make the connections. 225 00:09:37,820 --> 00:09:42,923 But obviously we have something cool nowadays 226 00:09:42,923 --> 00:09:45,990 that everyone likes to talk about called machine-learning. 227 00:09:45,990 --> 00:09:47,008 And so what we thought is, 228 00:09:47,008 --> 00:09:49,071 "Let's strip out all the metadata, 229 00:09:49,071 --> 00:09:52,707 let's look at what machine-learning can do 230 00:09:52,707 --> 00:09:55,301 based on visual recognition of this entire collection." 231 00:09:55,301 --> 00:10:01,271 And what we ended up with is this very interesting map, 232 00:10:01,271 --> 00:10:05,526 these clusters that have no reference point of information 233 00:10:05,526 --> 00:10:09,631 but has just used visuals to cluster things together. 234 00:10:09,631 --> 00:10:13,322 Each cluster is an art? to itself of discovery. 235 00:10:13,322 --> 00:10:15,823 But one of the clusters we want to show you very quickly 236 00:10:15,823 --> 00:10:18,563 is this amazing cluster of portraits 237 00:10:18,563 --> 00:10:20,989 that we found from museums around the world. 238 00:10:20,989 --> 00:10:23,024 If you could zoom in a little but more Seril, 239 00:10:23,024 --> 00:10:27,179 just to show you, you can just be traveling through portraits. 240 00:10:27,179 --> 00:10:29,499 And essentially, you can do nature, you can do horses, 241 00:10:29,499 --> 00:10:31,630 and clusters galore. 242 00:10:31,630 --> 00:10:34,401 When we say all these portraits, we were like, 243 00:10:34,401 --> 00:10:38,002 "Hey, can we do something fun for kids, 244 00:10:38,002 --> 00:10:39,664 can we just do something playful 245 00:10:39,664 --> 00:10:41,678 to get people interested in portraits?" 246 00:10:41,678 --> 00:10:42,795 Because I haven't really seen 247 00:10:42,795 --> 00:10:47,462 young kids really excited to go to a portrait gallery. 248 00:10:47,462 --> 00:10:49,048 So I want to try to figure something out. 249 00:10:49,048 --> 00:10:51,464 So we created something called the portrait matcher. 250 00:10:51,464 --> 00:10:53,005 It's quite self-explnatory, 251 00:10:53,005 --> 00:10:56,284 so i'm just going to let Seril show his beautiful face. 252 00:10:56,284 --> 00:10:58,122 And essentially what's happening 253 00:10:58,122 --> 00:11:00,345 is with the movement of his head, 254 00:11:00,345 --> 00:11:04,721 we are matching different portraits around the world from museums. 255 00:11:04,721 --> 00:11:07,609 (Applause) 256 00:11:07,609 --> 00:11:18,535 And I don't know about you, 257 00:11:18,535 --> 00:11:20,202 but I've shown it to my nephew 258 00:11:20,202 --> 00:11:23,389 and the reaction is just phenominal. 259 00:11:23,389 --> 00:11:27,957 All they ask me is when can we go see this. 260 00:11:27,957 --> 00:11:29,436 And by the way, if you're nice, 261 00:11:29,436 --> 00:11:33,737 maybe Seril you can smile and find a happy one. 262 00:11:33,737 --> 00:11:34,826 Oh, perfect. 263 00:11:34,826 --> 00:11:36,838 And by the way, this is not rehearsed. 264 00:11:36,838 --> 00:11:39,911 Congrats, Seril. 265 00:11:39,911 --> 00:11:43,234 Let's move on. 266 00:11:43,234 --> 00:11:44,309 Otherwise, this will take the whole time. 267 00:11:44,309 --> 00:11:48,243 So, art and culture can be fun, also. 268 00:11:48,243 --> 00:11:51,820 So for our last quick experiment -- 269 00:11:51,820 --> 00:11:53,468 we call all of these experiments -- 270 00:11:53,468 --> 00:11:56,480 our last quick experiment comes bck to machine learning. 271 00:11:56,480 --> 00:11:59,326 So we show you clusters, visual clusters, 272 00:11:59,326 --> 00:12:01,986 but what if we could ask the machine 273 00:12:01,986 --> 00:12:04,142 to also name these clusters? 274 00:12:04,142 --> 00:12:06,779 What if it could automatically tag them 275 00:12:06,779 --> 00:12:08,869 using no actual metadata? 276 00:12:08,869 --> 00:12:13,009 So what we have is this kind of explorer 277 00:12:13,009 --> 00:12:16,763 where we have managed to match around 4,000 labels 278 00:12:16,763 --> 00:12:19,972 and we haven't really done anything special here, 279 00:12:19,972 --> 00:12:21,819 just feed the collection, 280 00:12:21,819 --> 00:12:23,553 and we found interesting categories. 281 00:12:23,553 --> 00:12:26,173 We can start with horses, very straightforward catgeory. 282 00:12:26,173 --> 00:12:28,357 You would expect to see that the machine 283 00:12:28,357 --> 00:12:30,371 has put images of horses, right? 284 00:12:30,371 --> 00:12:31,632 It has. 285 00:12:31,632 --> 00:12:33,694 But you also notice right over there 286 00:12:33,694 --> 00:12:35,883 that it has a very abstract image 287 00:12:35,883 --> 00:12:38,958 that it has still managed to recognize and cluster as horses. 288 00:12:38,958 --> 00:12:41,514 We also have an amazing head in terms of a horse. 289 00:12:41,514 --> 00:12:46,094 And each one has the tags as to why it got categorized. 290 00:12:46,094 --> 00:12:50,659 So let's move to another one which I found very funny and interesting, 291 00:12:50,659 --> 00:12:53,078 because I don't understand how this category came up. 292 00:12:53,078 --> 00:12:55,171 It's called Lady in Waiting. 293 00:12:55,171 --> 00:12:57,935 If Seril, you do it very quickly, 294 00:12:57,935 --> 00:13:01,410 you will see that we have these amazing images 295 00:13:01,410 --> 00:13:04,210 of ladies, I guess, in waiting or posing, 296 00:13:04,210 --> 00:13:05,535 I don't really understand it 297 00:13:05,535 --> 00:13:06,565 (Laughter) 298 00:13:06,565 --> 00:13:07,665 But I've been trying to ask my museum contacts 299 00:13:07,665 --> 00:13:09,899 what is this, what's going on here, 300 00:13:09,899 --> 00:13:11,777 and it's fascinating. 301 00:13:11,777 --> 00:13:14,079 Coming back to gold very quickly, 302 00:13:14,079 --> 00:13:16,101 I wanted to search for gold 303 00:13:16,101 --> 00:13:18,196 and see how the machine tagged all the gold, 304 00:13:18,196 --> 00:13:20,666 but actually, it doesn't tag it as gold. 305 00:13:20,666 --> 00:13:22,048 We are living in popular times. 306 00:13:22,048 --> 00:13:24,400 It tags it as "bling bling". 307 00:13:24,400 --> 00:13:26,326 (Laughter) 308 00:13:26,326 --> 00:13:30,702 I'm being hard on Seril because I'm moving too fast. 309 00:13:30,702 --> 00:13:33,079 Essentially, here you have all the bling bling 310 00:13:33,079 --> 00:13:36,311 of the world's museums organized for you. 311 00:13:36,311 --> 00:13:39,721 And finally to end this talk and these experiments, 312 00:13:39,721 --> 00:13:43,130 what I hope you feel after this talk is happiness and emotion. 313 00:13:43,130 --> 00:13:45,420 And what would we see when we see happiness? 314 00:13:45,420 --> 00:13:49,077 If we actually look at all the objects 315 00:13:49,077 --> 00:13:50,582 that have been tagged under happines, 316 00:13:50,582 --> 00:13:53,825 you would expect happiness, I guess. 317 00:13:53,825 --> 00:13:55,655 But there was one that came up 318 00:13:55,655 --> 00:14:01,556 that was very fascinating and interesting 319 00:14:01,556 --> 00:14:04,438 which was this artwork by Douglas Coupland, 320 00:14:04,438 --> 00:14:06,618 our friend and artist in residence as well 321 00:14:06,618 --> 00:14:08,856 called "I Miss My Pre-Internet Brain". 322 00:14:08,856 --> 00:14:10,345 I don't know why the machine feels like 323 00:14:10,345 --> 00:14:12,332 it misses it's pre-Internet brain, 324 00:14:12,332 --> 00:14:13,718 it's been tagged here. 325 00:14:13,718 --> 00:14:16,316 But you know, it's a very interesting part. 326 00:14:16,316 --> 00:14:17,778 I sometimes do miss my pre-Internet brain, 327 00:14:17,778 --> 00:14:20,872 but now when it comes to exploring arts and culture online. 328 00:14:20,872 --> 00:14:22,775 So take out your phones, take out your computers, 329 00:14:22,775 --> 00:14:23,687 go visit museums. 330 00:14:23,687 --> 00:14:26,763 And just a quick call-out to all the amazing archivists, 331 00:14:26,763 --> 00:14:28,425 historians, curators, 332 00:14:28,425 --> 00:14:31,420 who are sitting in museums preserving all this culture. 333 00:14:31,420 --> 00:14:34,153 And the least we can do is get our daily dose of art and culture 334 00:14:34,153 --> 00:14:35,918 for ourselves and our kids. 335 00:14:35,918 --> 00:14:36,682 Thank you. 336 00:14:36,682 --> 00:14:47,536 (Applause)