full transcript

From the Ted Talk by Jonathan Harris: The web as art


Unscramble the Blue Letters


So I'm going to talk today about collecting stories in some unconventional ways. This is a picture of me from a very akawwrd stgae in my life. You might enjoy the awkwardly tight, cut-off pajama bottoms with balloons. Anyway, it was a time when I was mainly iettsenred in collecting imaginary stories. So this is a picture of me hnlodig one of the first woltoearcr paintings I ever made. And recently I've been much more interested in cicnlotelg stories from reality — so, real stories. And specifically, I'm interested in collecting my own stories, stories from the Internet, and then recently, seotris from life, which is kind of a new area of work that I've been doing recently. So I'll be tkainlg about each of those today. So, first of all, my own stories. These are two of my sketchbooks. I have many of these books, and I've been keeping them for about the last eight or nine years. They accompany me wherever I go in my life, and I fill them with all sorts of things, records of my lived experience: so watercolor paintings, drawings of what I see, dead fowelrs, dead ienctss, peastd ticket stubs, rsnutig cions, business cards, wirtngis. And in these books, you can find these srhot, little glimpses of moments and eineepxcers and people that I meet. And, you know, after keeping these books for a number of years, I started to become very interested in collecting not only my own personal artifacts, but also the artifacts of other people. So, I started collecting found objects. This is a ptrhgpooah I found lying in a gutter in New York City about 10 years ago. On the frnot, you can see the tttareed black-and-white phtoo of a woman's face, and on the back it says, "To Judy, the girl with the Bill Bailey voice. Have fun in whatever you do." And I really loevd this idea of the partial glimpse into somebody's life. As oppseod to knowing the whole story, just knowing a little bit of the story, and then letting your own mind fill in the rest. And that idea of a pritaal glimpse is something that will come back in a lot of the work I'll be showing later today. So, around this time I was studying computer science at proicetnn urntsvieiy, and I noticed that it was suddenly possible to collect these sotrs of personal afarictts, not just from street corners, but also from the Internet. And that suddenly, people, en masse, were leaving seocrs and scores of digital fooiprtnts online that told stories of their private lives. Blog posts, photographs, thtguohs, feelings, opinions, all of these things were being expressed by people oilnne, and leaving behind trails. So, I started to write computer prmorags that study very, very large sets of these online footprints. One such project is about a year and a half old. It's called "We Feel Fine." This is a project that scans the world's newly posted blog ertines every two or three minutes, searching for occurrences of the phrases "I feel" and "I am feeling." And when it finds one of those prehass, it grabs the full secentne up to the period and also tries to identify daigpheomrc information about the aohutr. So, their gender, their age, their ggepahiroc location and what the weather conditions were like when they wrote that sentence. It collects about 20,000 such sneectnes a day and it's been running for about a year and a half, having collected over 10 and a half million feelings now. This is, then, how they're presented. These dots here represent some of the English-speaking world's feelings from the last few hours, each dot being a single sentence stated by a single blogger. And the color of each dot corresponds to the type of feeling inside, so the bhgirt ones are happy, and the dark ones are sad. And the dmteaier of each dot corresponds to the lngteh of the sentence inside. So the small ones are short, and the bigger ones are longer. "I feel fine with the body I'm in, there'll be no easy excuse for why I still feel urcnofmtbloae being close to my boyfriend," from a twenty-two-year-old in jaapn. "I got this on some trading locally, but really don't feel like snwcerig with wiring and crap." Also, some of the feelings contain photographs in the blog posts. And when that happens, these maongte compositions are automatically created, which consist of the sentence and images being combined. And any of these can be opened up to reveal the sentence inside. "I feel good." "I feel rough now, and I probably geaind 100,000 pounds, but it was worth it." "I love how they were able to preserve most in everything that makes you feel close to nature — berfteltius, man-made forests, limestone caves and hey, even a huge python." So the next movement is called mobs. This provides a slightly more statistical look at things. This is showing the world's most comomn feelings overall right now, dominated by better, then bad, then good, then guilty, and so on. Weather causes the feelings to assume the physical tatris of the weather they represent. So the sunny ones swirl around, the cloudy ones float along, the rainy ones fall down, and the snowy ones fultter to the ground. You can also stop a raindrop and open the fleneig inside. fnalliy, location causes the feelings to move to their spots on a world map, giving you a sense of their geographic distribution. So I'll show you now some of my favorite montages from "We Feel Fine." These are the images that are alaaomuctilty costntcuerd. "I feel like I'm diagonally parked in a parallel universe." (Laughter) "I've keissd numerous other boys and it hasn't felt good, the kisses felt messy and wonrg, but kissing Lucas feles beautiful and almost spiritual." "I can feel my cancer grow." "I feel pretty." "I feel skinny, but I'm not." "I'm 23, and a recovering meth and hireon addict, and feel auolsbltey blessed to still be alive." "I can't wait to see them racing for the first time at Daytona next mntoh, because I feel the need for speed." (Laughter) "I feel sassy." "I feel so sexy in this new wig." As you can see, "We Feel Fine" collects very, very small-scale personal stories. Sometimes, stories as short as two or three words. So, really even cniahgnellg the notion of what can be considered a story. And recently, I've become interested in diinvg much more deeply into a single story. And that's led me to doing some work with the physical wolrd, not with the Internet, and only using the Internet at the very last mnmoet, as a poistteaernn medium. So these are some newer projects that actually aren't even laencuhd publicly yet. The first such one is called "The Whale Hunt." Last May, I spent nine days living up in Barrow, Alaska, the northernmost settlement in the untied States, with a family of Inupiat emiokss, documenting their annual spring whale hunt. This is the whaling camp here, we're about six miles from shore, cimapng on five and a half feet of thick, frozen pack ice. And that water that you see there is the open lead, and through that lead, bowhead whales migrate north each springtime. And the Eskimo cntummioy basically camps out on the edge of the ice here, waits for a whale to come close enough to attcak. And when it does, it throws a harpoon at it, and then hauls the whale up under the ice, and cuts it up. And that would provide the community's food supply for a long time. So I went up there, and I lveid with these guys out in their whaling camp here, and photographed the entire experience, bgeinnnig with the taxi ride to Newark airport in New York, and ending with the butchering of the second whale, seven and a half days later. I photographed that entire experience at five-minute intervals. So every five mtenius, I took a photograph. When I was awake, with the camera around my neck. When I was sleeping, with a tripod and a timer. And then in moments of high adrenaline, like when something exciting was happening, I would up that photographic frequency to as many as 37 photographs in five minutes. So what this created was a photographic heartbeat that sped up and slowed down, more or less matching the changing pace of my own heartbeat. That was the first concept here. The second concept was to use this experience to think about the fundamental components of any story. What are the things that make up a story? So, stories have ccrahreats. Stories have cnotceps. Stories take plcae in a certain area. They have contexts. They have colors. What do they look like? They have time. When did it take place? Dates — when did it ouccr? And in the case of the whale hunt, also this idea of an excitement leevl. The thing about stories, though, in most of the existing mumdies that we're accustomed to — things like novels, rdaio, photographs, meoivs, even lectures like this one — we're very accustomed to this idea of the narrator or the camera position, some kind of ocmnieisnt, external body through whose eyes you see the srtoy. We're very used to this. But if you think about real life, it's not like that at all. I mean, in real life, things are much more nuanced and complex, and there's all of these overlapping stories intersecting and tonhicug each other. And so I toguhht it would be interesting to biuld a framework to surface those types of stories. So, in the case of "The Whale Hunt," how could we extract something like the story of smeion and cafrwrod, involving the concepts of wildlife, tools and bolod, taking place on the Arctic Ocean, dominated by the color red, happening around 10 a.m. on May 3, with an excitement level of high? So, how to extract this order of narrative from this larger story? I built a web interface for viewing "The Whale Hunt" that attempts to do just this. So these are all 3,214 priucets taken up there. This is my studio in Brooklyn. This is the Arctic Ocean, and the bnuceitrhg of the second whale, seven days later. You can start to see some of the story here, told by color. So this red strip signifies the color of the wallpaper in the basement anrpmatet where I was staying. And things go white as we move out onto the Arctic Ocean. Introduction of red down here, when whales are being cut up. You can see a timeline, showing you the exciting moments throughout the story. These are organized chronologically. Wheel provides a slightly more paulyfl version of the same, so these are also all the photographs organized chronologically. And any of these can be clicked, and then the nrvrtaaie is eernetd at that position. So here I am sleeping on the airplane heiadng up to Alaska. That's "Moby Dick." This is the food we ate. This is in the Patkotak's family living room in their house in barorw. The boxed wine they served us. Cigarette break outside — I don't smoke. This is a really exciting sequence of me sleeping. This is out at wlhae camp, on the Arctic Ocean. This graph that I'm clicking down here is meant to be reminiscent of a medical heartbeat graph, showing the exciting moments of adrenaline. This is the ice starting to freeze over. The snow fence they bliut. And so what I'll show you now is the ability to pull out sub-stories. So, here you see the cast. These are all of the people in "The Whale Hunt" and the two whales that were killed down here. And we could do something as arbitrary as, say, extract the story of Rony, involving the concepts of blood and whales and tools, taking place on the Arctic oeacn, at Ahkivgaq camp, with the heartbeat level of fast. And now we've whittled down that whole story to just 29 mhnatcig photographs, and then we can enter the narrative at that ptsiooin. And you can see Rony cutting up the whale here. These welhas are about 40 feet long, and weighing over 40 tons. And they provide the food source for the community for much of the year. Skipping ahead a bit more here, this is Rony on the whale carcass. They use no chainsaws or anything; it's entirely just bdales, and an ibrlcdeniy efficient process. This is the guys on the rope, pulling open the carcass. This is the muktuk, or the blubber, all lined up for community drotituibisn. It's baleen. Moving on. So what I'm going to tell you about next is a very new thing. It's not even a pcoerjt yet. So, just yesterday, I flew in here from Singapore, and before that, I was siendpng two weeks in Bhutan, the small hiyaamlan kingdom nestled between Tibet and India. And I was doing a project there about happiness, interviewing a lot of local people. So Bhutan has this really wacky thing where they base most of their high-level governmental decisions around the coecnpt of gosrs national hpianpess instead of gross domestic product, and they've been doing this since the '70s. And it leads to just a completely different value system. It's an incredibly non-materialistic culture, where people don't have a lot, but they're incredibly hppay. So I went around and I talked to people about some of these iaeds. So, I did a number of things. I asked people a number of set questions, and took a number of set pgahprothos, and inwtereveid them with audio, and also took pictures. I would start by asking people to rate their happiness between one and 10, which is kind of inherently absurd. And then when they awrseend, I would inflate that number of balloons and give them that number of balloons to hold. So, you have some really happy porsen holding 10 balloons, and some really sad soul holding one blaloon. But you know, even holding one balloon is like, kind of happy. (Laughter) And then I would ask them a nbmuer of questions like what was the happiest day in their life, what makes them happy. And then finally, I would ask them to make a wish. And when they made a wish, I would write their wish onto one of the balloons and take a picture of them holding it. So I'm going to show you now just a few brief snippets of some of the interviews that I did, some of the people I spoke with. This is an 11-year-old student. He was playing cops and robbers with his friends, running around town, and they all had plastic toy guns. His wish was to become a police ofcfier. He was getting started early. Those were his hands. I took pictures of everybody's hands, because I think you can often tell a lot about somebody from how their hdans look. I took a portrait of everybody, and asked everybody to make a fnuny face. A 17-year-old student. Her wish was to have been born a boy. She thinks that women have a pretty tough go of things in Bhutan, and it's a lot easier if you're a boy. A 28-year-old cell phone shop owner. If you knew what Paro lkoeod like, you'd understand how amazing it is that there's a cell phone shop there. He wanted to help poor people. A 53-year-old farmer. She was chaffing wheat, and that pile of wehat behind her had taken her about a week to make. She wanted to keep farming until she dies. You can really start to see the stories told by the hands here. She was wearing this silver ring that had the word "love" engraved on it, and she'd found it in the road somewhere. A 16-year-old qarury worker. This guy was breaking rocks with a hammer in the hot sunlight, but he just wanted to spend his life as a farmer. A 21-year-old monk. He was very happy. He wanted to live a long life at the monastery. He had this amazing series of hairs growing out of a mole on the left side of his face, which I'm told is very good luck. He was kind of too shy to make a funny face. A 16-year-old student. She wanted to become an independent woman. I asked her about that, and she said she meant that she doesn't want to be mrraied, because, in her oiipnon, when you get married in Bhutan as a woman, your chances to live an independent life kind of end, and so she had no interest in that. A 24-year-old truck driver. There are these tyeinlgrirfy huge Indian trucks that come careening around one-lane roads with two-lane triffac, with 3,000-foot drop-offs right next to the road, and he was driving one of these trucks. But all he wanted was to just live a comfortable life, like other people. A 24-year-old road seepwer. I cughat her on her lunch break. She'd built a little fire to keep warm, right next to the road. Her wish was to mrary someone with a car. She watend a change in her life. She lives in a little worker's camp right next to the road, and she wanted a different lot on things. An 81-year-old itinerant farmer. I saw this guy on the side of the road, and he actually doesn't have a home. He travels from farm to farm each day trying to find work, and then he tries to sleep at whatever farm he gets work at. So his wish was to come with me, so that he had somewhere to live. He had this amazing knife that he pulled out of his gho and started brandishing when I akesd him to make a funny face. It was all good-natured. A 10-year-old. He wanted to join a school and learn to read, but his pntears didn't have enough money to send him to school. He was eating this orange, sugary candy that he kept dipping his fingers into, and since there was so much saliva on his hands, this orange paste srttead to form on his palms. (lghtaeur) A 37-year-old road worker. One of the more touchy political subjects in bhuatn is the use of Indian cheap labor that they ipromt from India to build the roads, and then they send these people home once the rdoas are built. So these guys were in a worker's gang mixing up asphalt one mrniong on the side of the highway. His wish was to make some money and open a store. A 75-year-old feamrr. She was selling oranges on the side of the road. I asked her about her wish, and she said, "You know, maybe I'll live, maybe I'll die, but I don't have a wish." She was chewing bteel nut, which caused her teeth over the years to turn very red. Finally, this is a 26-year-old nun I spoke to. Her wish was to make a pilgrimage to Tibet. I asked her how long she planned to live in the nrenuny and she said, "Well, you know, of course, it's ierpnmenamt, but my plan is to live here until I'm 30, and then enter a hgtearime." And I said, "You mean, like a cave?" And she said, "Yeah, like a cave." And I said, "Wow, and how long will you live in the cave?" And she said, "Well, you know, I think I'd kind of like to live my whole life in the cave." I just thought that was amznaig. I mean, she spoke in a way — with amazing English, and amazing homur, and amazing laughter — that made her seem like somebody I could have bumped into on the seetrts of New York, or in Vermont, where I'm from. But here she had been linvig in a nunnery for the last seven years. I asked her a little bit more about the cave and what she planned would happen once she went there, you know. What if she saw the truth after just one year, what would she do for the next 35 years in her life? And this is what she said. Woman: I think I'm going to stay for 35. Maybe — maybe I'll die. Jonathan Harris: Maybe you'll die? Woman: Yes. JH: 10 years? Woman: Yes, yes. JH: 10 years, that's a long time. Woman: Yes, not maybe one, 10 years, maybe I can die within one year, or something like that. JH: Are you hoping to? Woman: Ah, because you know, it's impermanent. JH: Yeah, but — yeah, OK. Do you hope — would you prefer to live in the cave for 40 years, or to live for one year? Woman: But I pfreer for maybe 40 to 50. JH: 40 to 50? Yeah. Woman: Yes. From then, I'm going to the heaven. JH: Well, I wish you the best of luck with it. Woman: Thank you. JH: I hope it's everything that you hope it will be. So thank you again, so much. Woman: You're most welcome. JH: So if you caught that, she said she hoped to die when she was around 40. That was enough life for her. So, the last thing we did, very qkciluy, is I took all those wish balloons — there were 117 interviews, 117 wishes — and I brought them up to a place called Dochula, which is a mountain pass in Bhutan, at 10,300 feet, one of the more sacred places in Bhutan. And up there, there are thaunsods of prayer flags that polpee have spread out over the yares. And we re-inflated all of the boalnols, put them up on a snitrg, and hung them up there among the prayer flags. And they're actually still flying up there taody. So if any of you have any Bhutan travel plans in the near future, you can go cechk these out. Here are some iagmes from that. We said a bsuiddht prayer so that all these wishes could come true. You can start to see some fiaimlar balloons here. "To make some mnoey and to open a store" was the Indian road worker. Thanks very much. (Applause)

Open Cloze


So I'm going to talk today about collecting stories in some unconventional ways. This is a picture of me from a very _______ _____ in my life. You might enjoy the awkwardly tight, cut-off pajama bottoms with balloons. Anyway, it was a time when I was mainly __________ in collecting imaginary stories. So this is a picture of me _______ one of the first __________ paintings I ever made. And recently I've been much more interested in __________ stories from reality — so, real stories. And specifically, I'm interested in collecting my own stories, stories from the Internet, and then recently, _______ from life, which is kind of a new area of work that I've been doing recently. So I'll be _______ about each of those today. So, first of all, my own stories. These are two of my sketchbooks. I have many of these books, and I've been keeping them for about the last eight or nine years. They accompany me wherever I go in my life, and I fill them with all sorts of things, records of my lived experience: so watercolor paintings, drawings of what I see, dead _______, dead _______, ______ ticket stubs, _______ _____, business cards, ________. And in these books, you can find these _____, little glimpses of moments and ___________ and people that I meet. And, you know, after keeping these books for a number of years, I started to become very interested in collecting not only my own personal artifacts, but also the artifacts of other people. So, I started collecting found objects. This is a __________ I found lying in a gutter in New York City about 10 years ago. On the _____, you can see the ________ black-and-white _____ of a woman's face, and on the back it says, "To Judy, the girl with the Bill Bailey voice. Have fun in whatever you do." And I really _____ this idea of the partial glimpse into somebody's life. As _______ to knowing the whole story, just knowing a little bit of the story, and then letting your own mind fill in the rest. And that idea of a _______ glimpse is something that will come back in a lot of the work I'll be showing later today. So, around this time I was studying computer science at _________ __________, and I noticed that it was suddenly possible to collect these _____ of personal _________, not just from street corners, but also from the Internet. And that suddenly, people, en masse, were leaving ______ and scores of digital __________ online that told stories of their private lives. Blog posts, photographs, ________, feelings, opinions, all of these things were being expressed by people ______, and leaving behind trails. So, I started to write computer ________ that study very, very large sets of these online footprints. One such project is about a year and a half old. It's called "We Feel Fine." This is a project that scans the world's newly posted blog _______ every two or three minutes, searching for occurrences of the phrases "I feel" and "I am feeling." And when it finds one of those _______, it grabs the full ________ up to the period and also tries to identify ___________ information about the ______. So, their gender, their age, their __________ location and what the weather conditions were like when they wrote that sentence. It collects about 20,000 such _________ a day and it's been running for about a year and a half, having collected over 10 and a half million feelings now. This is, then, how they're presented. These dots here represent some of the English-speaking world's feelings from the last few hours, each dot being a single sentence stated by a single blogger. And the color of each dot corresponds to the type of feeling inside, so the ______ ones are happy, and the dark ones are sad. And the ________ of each dot corresponds to the ______ of the sentence inside. So the small ones are short, and the bigger ones are longer. "I feel fine with the body I'm in, there'll be no easy excuse for why I still feel _____________ being close to my boyfriend," from a twenty-two-year-old in _____. "I got this on some trading locally, but really don't feel like ________ with wiring and crap." Also, some of the feelings contain photographs in the blog posts. And when that happens, these _______ compositions are automatically created, which consist of the sentence and images being combined. And any of these can be opened up to reveal the sentence inside. "I feel good." "I feel rough now, and I probably ______ 100,000 pounds, but it was worth it." "I love how they were able to preserve most in everything that makes you feel close to nature — ___________, man-made forests, limestone caves and hey, even a huge python." So the next movement is called mobs. This provides a slightly more statistical look at things. This is showing the world's most ______ feelings overall right now, dominated by better, then bad, then good, then guilty, and so on. Weather causes the feelings to assume the physical ______ of the weather they represent. So the sunny ones swirl around, the cloudy ones float along, the rainy ones fall down, and the snowy ones _______ to the ground. You can also stop a raindrop and open the _______ inside. _______, location causes the feelings to move to their spots on a world map, giving you a sense of their geographic distribution. So I'll show you now some of my favorite montages from "We Feel Fine." These are the images that are _____________ ___________. "I feel like I'm diagonally parked in a parallel universe." (Laughter) "I've ______ numerous other boys and it hasn't felt good, the kisses felt messy and _____, but kissing Lucas _____ beautiful and almost spiritual." "I can feel my cancer grow." "I feel pretty." "I feel skinny, but I'm not." "I'm 23, and a recovering meth and ______ addict, and feel __________ blessed to still be alive." "I can't wait to see them racing for the first time at Daytona next _____, because I feel the need for speed." (Laughter) "I feel sassy." "I feel so sexy in this new wig." As you can see, "We Feel Fine" collects very, very small-scale personal stories. Sometimes, stories as short as two or three words. So, really even ___________ the notion of what can be considered a story. And recently, I've become interested in ______ much more deeply into a single story. And that's led me to doing some work with the physical _____, not with the Internet, and only using the Internet at the very last ______, as a ____________ medium. So these are some newer projects that actually aren't even ________ publicly yet. The first such one is called "The Whale Hunt." Last May, I spent nine days living up in Barrow, Alaska, the northernmost settlement in the ______ States, with a family of Inupiat _______, documenting their annual spring whale hunt. This is the whaling camp here, we're about six miles from shore, _______ on five and a half feet of thick, frozen pack ice. And that water that you see there is the open lead, and through that lead, bowhead whales migrate north each springtime. And the Eskimo _________ basically camps out on the edge of the ice here, waits for a whale to come close enough to ______. And when it does, it throws a harpoon at it, and then hauls the whale up under the ice, and cuts it up. And that would provide the community's food supply for a long time. So I went up there, and I _____ with these guys out in their whaling camp here, and photographed the entire experience, _________ with the taxi ride to Newark airport in New York, and ending with the butchering of the second whale, seven and a half days later. I photographed that entire experience at five-minute intervals. So every five _______, I took a photograph. When I was awake, with the camera around my neck. When I was sleeping, with a tripod and a timer. And then in moments of high adrenaline, like when something exciting was happening, I would up that photographic frequency to as many as 37 photographs in five minutes. So what this created was a photographic heartbeat that sped up and slowed down, more or less matching the changing pace of my own heartbeat. That was the first concept here. The second concept was to use this experience to think about the fundamental components of any story. What are the things that make up a story? So, stories have __________. Stories have ________. Stories take _____ in a certain area. They have contexts. They have colors. What do they look like? They have time. When did it take place? Dates — when did it _____? And in the case of the whale hunt, also this idea of an excitement _____. The thing about stories, though, in most of the existing _______ that we're accustomed to — things like novels, _____, photographs, ______, even lectures like this one — we're very accustomed to this idea of the narrator or the camera position, some kind of __________, external body through whose eyes you see the _____. We're very used to this. But if you think about real life, it's not like that at all. I mean, in real life, things are much more nuanced and complex, and there's all of these overlapping stories intersecting and ________ each other. And so I _______ it would be interesting to _____ a framework to surface those types of stories. So, in the case of "The Whale Hunt," how could we extract something like the story of ______ and ________, involving the concepts of wildlife, tools and _____, taking place on the Arctic Ocean, dominated by the color red, happening around 10 a.m. on May 3, with an excitement level of high? So, how to extract this order of narrative from this larger story? I built a web interface for viewing "The Whale Hunt" that attempts to do just this. So these are all 3,214 ________ taken up there. This is my studio in Brooklyn. This is the Arctic Ocean, and the __________ of the second whale, seven days later. You can start to see some of the story here, told by color. So this red strip signifies the color of the wallpaper in the basement _________ where I was staying. And things go white as we move out onto the Arctic Ocean. Introduction of red down here, when whales are being cut up. You can see a timeline, showing you the exciting moments throughout the story. These are organized chronologically. Wheel provides a slightly more _______ version of the same, so these are also all the photographs organized chronologically. And any of these can be clicked, and then the _________ is _______ at that position. So here I am sleeping on the airplane _______ up to Alaska. That's "Moby Dick." This is the food we ate. This is in the Patkotak's family living room in their house in ______. The boxed wine they served us. Cigarette break outside — I don't smoke. This is a really exciting sequence of me sleeping. This is out at _____ camp, on the Arctic Ocean. This graph that I'm clicking down here is meant to be reminiscent of a medical heartbeat graph, showing the exciting moments of adrenaline. This is the ice starting to freeze over. The snow fence they _____. And so what I'll show you now is the ability to pull out sub-stories. So, here you see the cast. These are all of the people in "The Whale Hunt" and the two whales that were killed down here. And we could do something as arbitrary as, say, extract the story of Rony, involving the concepts of blood and whales and tools, taking place on the Arctic _____, at Ahkivgaq camp, with the heartbeat level of fast. And now we've whittled down that whole story to just 29 ________ photographs, and then we can enter the narrative at that ________. And you can see Rony cutting up the whale here. These ______ are about 40 feet long, and weighing over 40 tons. And they provide the food source for the community for much of the year. Skipping ahead a bit more here, this is Rony on the whale carcass. They use no chainsaws or anything; it's entirely just ______, and an __________ efficient process. This is the guys on the rope, pulling open the carcass. This is the muktuk, or the blubber, all lined up for community ____________. It's baleen. Moving on. So what I'm going to tell you about next is a very new thing. It's not even a _______ yet. So, just yesterday, I flew in here from Singapore, and before that, I was ________ two weeks in Bhutan, the small _________ kingdom nestled between Tibet and India. And I was doing a project there about happiness, interviewing a lot of local people. So Bhutan has this really wacky thing where they base most of their high-level governmental decisions around the _______ of _____ national _________ instead of gross domestic product, and they've been doing this since the '70s. And it leads to just a completely different value system. It's an incredibly non-materialistic culture, where people don't have a lot, but they're incredibly _____. So I went around and I talked to people about some of these _____. So, I did a number of things. I asked people a number of set questions, and took a number of set ___________, and ___________ them with audio, and also took pictures. I would start by asking people to rate their happiness between one and 10, which is kind of inherently absurd. And then when they ________, I would inflate that number of balloons and give them that number of balloons to hold. So, you have some really happy ______ holding 10 balloons, and some really sad soul holding one _______. But you know, even holding one balloon is like, kind of happy. (Laughter) And then I would ask them a ______ of questions like what was the happiest day in their life, what makes them happy. And then finally, I would ask them to make a wish. And when they made a wish, I would write their wish onto one of the balloons and take a picture of them holding it. So I'm going to show you now just a few brief snippets of some of the interviews that I did, some of the people I spoke with. This is an 11-year-old student. He was playing cops and robbers with his friends, running around town, and they all had plastic toy guns. His wish was to become a police _______. He was getting started early. Those were his hands. I took pictures of everybody's hands, because I think you can often tell a lot about somebody from how their _____ look. I took a portrait of everybody, and asked everybody to make a _____ face. A 17-year-old student. Her wish was to have been born a boy. She thinks that women have a pretty tough go of things in Bhutan, and it's a lot easier if you're a boy. A 28-year-old cell phone shop owner. If you knew what Paro ______ like, you'd understand how amazing it is that there's a cell phone shop there. He wanted to help poor people. A 53-year-old farmer. She was chaffing wheat, and that pile of _____ behind her had taken her about a week to make. She wanted to keep farming until she dies. You can really start to see the stories told by the hands here. She was wearing this silver ring that had the word "love" engraved on it, and she'd found it in the road somewhere. A 16-year-old ______ worker. This guy was breaking rocks with a hammer in the hot sunlight, but he just wanted to spend his life as a farmer. A 21-year-old monk. He was very happy. He wanted to live a long life at the monastery. He had this amazing series of hairs growing out of a mole on the left side of his face, which I'm told is very good luck. He was kind of too shy to make a funny face. A 16-year-old student. She wanted to become an independent woman. I asked her about that, and she said she meant that she doesn't want to be _______, because, in her _______, when you get married in Bhutan as a woman, your chances to live an independent life kind of end, and so she had no interest in that. A 24-year-old truck driver. There are these ____________ huge Indian trucks that come careening around one-lane roads with two-lane _______, with 3,000-foot drop-offs right next to the road, and he was driving one of these trucks. But all he wanted was to just live a comfortable life, like other people. A 24-year-old road _______. I ______ her on her lunch break. She'd built a little fire to keep warm, right next to the road. Her wish was to _____ someone with a car. She ______ a change in her life. She lives in a little worker's camp right next to the road, and she wanted a different lot on things. An 81-year-old itinerant farmer. I saw this guy on the side of the road, and he actually doesn't have a home. He travels from farm to farm each day trying to find work, and then he tries to sleep at whatever farm he gets work at. So his wish was to come with me, so that he had somewhere to live. He had this amazing knife that he pulled out of his gho and started brandishing when I _____ him to make a funny face. It was all good-natured. A 10-year-old. He wanted to join a school and learn to read, but his _______ didn't have enough money to send him to school. He was eating this orange, sugary candy that he kept dipping his fingers into, and since there was so much saliva on his hands, this orange paste _______ to form on his palms. (________) A 37-year-old road worker. One of the more touchy political subjects in ______ is the use of Indian cheap labor that they ______ from India to build the roads, and then they send these people home once the _____ are built. So these guys were in a worker's gang mixing up asphalt one _______ on the side of the highway. His wish was to make some money and open a store. A 75-year-old ______. She was selling oranges on the side of the road. I asked her about her wish, and she said, "You know, maybe I'll live, maybe I'll die, but I don't have a wish." She was chewing _____ nut, which caused her teeth over the years to turn very red. Finally, this is a 26-year-old nun I spoke to. Her wish was to make a pilgrimage to Tibet. I asked her how long she planned to live in the _______ and she said, "Well, you know, of course, it's ___________, but my plan is to live here until I'm 30, and then enter a _________." And I said, "You mean, like a cave?" And she said, "Yeah, like a cave." And I said, "Wow, and how long will you live in the cave?" And she said, "Well, you know, I think I'd kind of like to live my whole life in the cave." I just thought that was _______. I mean, she spoke in a way — with amazing English, and amazing _____, and amazing laughter — that made her seem like somebody I could have bumped into on the _______ of New York, or in Vermont, where I'm from. But here she had been ______ in a nunnery for the last seven years. I asked her a little bit more about the cave and what she planned would happen once she went there, you know. What if she saw the truth after just one year, what would she do for the next 35 years in her life? And this is what she said. Woman: I think I'm going to stay for 35. Maybe — maybe I'll die. Jonathan Harris: Maybe you'll die? Woman: Yes. JH: 10 years? Woman: Yes, yes. JH: 10 years, that's a long time. Woman: Yes, not maybe one, 10 years, maybe I can die within one year, or something like that. JH: Are you hoping to? Woman: Ah, because you know, it's impermanent. JH: Yeah, but — yeah, OK. Do you hope — would you prefer to live in the cave for 40 years, or to live for one year? Woman: But I ______ for maybe 40 to 50. JH: 40 to 50? Yeah. Woman: Yes. From then, I'm going to the heaven. JH: Well, I wish you the best of luck with it. Woman: Thank you. JH: I hope it's everything that you hope it will be. So thank you again, so much. Woman: You're most welcome. JH: So if you caught that, she said she hoped to die when she was around 40. That was enough life for her. So, the last thing we did, very _______, is I took all those wish balloons — there were 117 interviews, 117 wishes — and I brought them up to a place called Dochula, which is a mountain pass in Bhutan, at 10,300 feet, one of the more sacred places in Bhutan. And up there, there are _________ of prayer flags that ______ have spread out over the _____. And we re-inflated all of the ________, put them up on a ______, and hung them up there among the prayer flags. And they're actually still flying up there _____. So if any of you have any Bhutan travel plans in the near future, you can go _____ these out. Here are some ______ from that. We said a ________ prayer so that all these wishes could come true. You can start to see some ________ balloons here. "To make some _____ and to open a store" was the Indian road worker. Thanks very much. (Applause)

Solution


  1. bhutan
  2. marry
  3. sorts
  4. years
  5. phrases
  6. familiar
  7. finally
  8. diving
  9. omniscient
  10. presentation
  11. prefer
  12. absolutely
  13. front
  14. camping
  15. string
  16. geographic
  17. traits
  18. demographic
  19. playful
  20. simeon
  21. whales
  22. check
  23. impermanent
  24. photographs
  25. gained
  26. distribution
  27. himalayan
  28. position
  29. balloon
  30. japan
  31. talking
  32. build
  33. incredibly
  34. sweeper
  35. quickly
  36. today
  37. feeling
  38. spending
  39. awkward
  40. author
  41. footprints
  42. looked
  43. flowers
  44. farmer
  45. money
  46. person
  47. happy
  48. bright
  49. montage
  50. buddhist
  51. kissed
  52. quarry
  53. feels
  54. coins
  55. heading
  56. writings
  57. whale
  58. uncomfortable
  59. princeton
  60. thousands
  61. happiness
  62. online
  63. programs
  64. living
  65. moment
  66. interviewed
  67. ocean
  68. screwing
  69. blood
  70. barrow
  71. challenging
  72. apartment
  73. attack
  74. amazing
  75. terrifyingly
  76. entered
  77. started
  78. thoughts
  79. funny
  80. morning
  81. radio
  82. hands
  83. photograph
  84. opinion
  85. built
  86. diameter
  87. project
  88. streets
  89. stage
  90. people
  91. eskimos
  92. number
  93. narrative
  94. sentence
  95. touching
  96. occur
  97. parents
  98. insects
  99. loved
  100. constructed
  101. thought
  102. butchering
  103. wrong
  104. artifacts
  105. heroin
  106. wanted
  107. interested
  108. scores
  109. crawford
  110. traffic
  111. launched
  112. blades
  113. automatically
  114. common
  115. gross
  116. world
  117. watercolor
  118. pasted
  119. wheat
  120. caught
  121. story
  122. partial
  123. mediums
  124. minutes
  125. tattered
  126. beginning
  127. university
  128. lived
  129. flutter
  130. answered
  131. balloons
  132. humor
  133. photo
  134. collecting
  135. married
  136. rusting
  137. butterflies
  138. concepts
  139. stories
  140. united
  141. short
  142. ideas
  143. officer
  144. pictures
  145. import
  146. sentences
  147. asked
  148. images
  149. movies
  150. month
  151. concept
  152. betel
  153. nunnery
  154. level
  155. roads
  156. place
  157. community
  158. hermitage
  159. holding
  160. characters
  161. opposed
  162. laughter
  163. entries
  164. matching
  165. experiences
  166. length

Original Text


So I'm going to talk today about collecting stories in some unconventional ways. This is a picture of me from a very awkward stage in my life. You might enjoy the awkwardly tight, cut-off pajama bottoms with balloons. Anyway, it was a time when I was mainly interested in collecting imaginary stories. So this is a picture of me holding one of the first watercolor paintings I ever made. And recently I've been much more interested in collecting stories from reality — so, real stories. And specifically, I'm interested in collecting my own stories, stories from the Internet, and then recently, stories from life, which is kind of a new area of work that I've been doing recently. So I'll be talking about each of those today. So, first of all, my own stories. These are two of my sketchbooks. I have many of these books, and I've been keeping them for about the last eight or nine years. They accompany me wherever I go in my life, and I fill them with all sorts of things, records of my lived experience: so watercolor paintings, drawings of what I see, dead flowers, dead insects, pasted ticket stubs, rusting coins, business cards, writings. And in these books, you can find these short, little glimpses of moments and experiences and people that I meet. And, you know, after keeping these books for a number of years, I started to become very interested in collecting not only my own personal artifacts, but also the artifacts of other people. So, I started collecting found objects. This is a photograph I found lying in a gutter in New York City about 10 years ago. On the front, you can see the tattered black-and-white photo of a woman's face, and on the back it says, "To Judy, the girl with the Bill Bailey voice. Have fun in whatever you do." And I really loved this idea of the partial glimpse into somebody's life. As opposed to knowing the whole story, just knowing a little bit of the story, and then letting your own mind fill in the rest. And that idea of a partial glimpse is something that will come back in a lot of the work I'll be showing later today. So, around this time I was studying computer science at Princeton University, and I noticed that it was suddenly possible to collect these sorts of personal artifacts, not just from street corners, but also from the Internet. And that suddenly, people, en masse, were leaving scores and scores of digital footprints online that told stories of their private lives. Blog posts, photographs, thoughts, feelings, opinions, all of these things were being expressed by people online, and leaving behind trails. So, I started to write computer programs that study very, very large sets of these online footprints. One such project is about a year and a half old. It's called "We Feel Fine." This is a project that scans the world's newly posted blog entries every two or three minutes, searching for occurrences of the phrases "I feel" and "I am feeling." And when it finds one of those phrases, it grabs the full sentence up to the period and also tries to identify demographic information about the author. So, their gender, their age, their geographic location and what the weather conditions were like when they wrote that sentence. It collects about 20,000 such sentences a day and it's been running for about a year and a half, having collected over 10 and a half million feelings now. This is, then, how they're presented. These dots here represent some of the English-speaking world's feelings from the last few hours, each dot being a single sentence stated by a single blogger. And the color of each dot corresponds to the type of feeling inside, so the bright ones are happy, and the dark ones are sad. And the diameter of each dot corresponds to the length of the sentence inside. So the small ones are short, and the bigger ones are longer. "I feel fine with the body I'm in, there'll be no easy excuse for why I still feel uncomfortable being close to my boyfriend," from a twenty-two-year-old in Japan. "I got this on some trading locally, but really don't feel like screwing with wiring and crap." Also, some of the feelings contain photographs in the blog posts. And when that happens, these montage compositions are automatically created, which consist of the sentence and images being combined. And any of these can be opened up to reveal the sentence inside. "I feel good." "I feel rough now, and I probably gained 100,000 pounds, but it was worth it." "I love how they were able to preserve most in everything that makes you feel close to nature — butterflies, man-made forests, limestone caves and hey, even a huge python." So the next movement is called mobs. This provides a slightly more statistical look at things. This is showing the world's most common feelings overall right now, dominated by better, then bad, then good, then guilty, and so on. Weather causes the feelings to assume the physical traits of the weather they represent. So the sunny ones swirl around, the cloudy ones float along, the rainy ones fall down, and the snowy ones flutter to the ground. You can also stop a raindrop and open the feeling inside. Finally, location causes the feelings to move to their spots on a world map, giving you a sense of their geographic distribution. So I'll show you now some of my favorite montages from "We Feel Fine." These are the images that are automatically constructed. "I feel like I'm diagonally parked in a parallel universe." (Laughter) "I've kissed numerous other boys and it hasn't felt good, the kisses felt messy and wrong, but kissing Lucas feels beautiful and almost spiritual." "I can feel my cancer grow." "I feel pretty." "I feel skinny, but I'm not." "I'm 23, and a recovering meth and heroin addict, and feel absolutely blessed to still be alive." "I can't wait to see them racing for the first time at Daytona next month, because I feel the need for speed." (Laughter) "I feel sassy." "I feel so sexy in this new wig." As you can see, "We Feel Fine" collects very, very small-scale personal stories. Sometimes, stories as short as two or three words. So, really even challenging the notion of what can be considered a story. And recently, I've become interested in diving much more deeply into a single story. And that's led me to doing some work with the physical world, not with the Internet, and only using the Internet at the very last moment, as a presentation medium. So these are some newer projects that actually aren't even launched publicly yet. The first such one is called "The Whale Hunt." Last May, I spent nine days living up in Barrow, Alaska, the northernmost settlement in the United States, with a family of Inupiat Eskimos, documenting their annual spring whale hunt. This is the whaling camp here, we're about six miles from shore, camping on five and a half feet of thick, frozen pack ice. And that water that you see there is the open lead, and through that lead, bowhead whales migrate north each springtime. And the Eskimo community basically camps out on the edge of the ice here, waits for a whale to come close enough to attack. And when it does, it throws a harpoon at it, and then hauls the whale up under the ice, and cuts it up. And that would provide the community's food supply for a long time. So I went up there, and I lived with these guys out in their whaling camp here, and photographed the entire experience, beginning with the taxi ride to Newark airport in New York, and ending with the butchering of the second whale, seven and a half days later. I photographed that entire experience at five-minute intervals. So every five minutes, I took a photograph. When I was awake, with the camera around my neck. When I was sleeping, with a tripod and a timer. And then in moments of high adrenaline, like when something exciting was happening, I would up that photographic frequency to as many as 37 photographs in five minutes. So what this created was a photographic heartbeat that sped up and slowed down, more or less matching the changing pace of my own heartbeat. That was the first concept here. The second concept was to use this experience to think about the fundamental components of any story. What are the things that make up a story? So, stories have characters. Stories have concepts. Stories take place in a certain area. They have contexts. They have colors. What do they look like? They have time. When did it take place? Dates — when did it occur? And in the case of the whale hunt, also this idea of an excitement level. The thing about stories, though, in most of the existing mediums that we're accustomed to — things like novels, radio, photographs, movies, even lectures like this one — we're very accustomed to this idea of the narrator or the camera position, some kind of omniscient, external body through whose eyes you see the story. We're very used to this. But if you think about real life, it's not like that at all. I mean, in real life, things are much more nuanced and complex, and there's all of these overlapping stories intersecting and touching each other. And so I thought it would be interesting to build a framework to surface those types of stories. So, in the case of "The Whale Hunt," how could we extract something like the story of Simeon and Crawford, involving the concepts of wildlife, tools and blood, taking place on the Arctic Ocean, dominated by the color red, happening around 10 a.m. on May 3, with an excitement level of high? So, how to extract this order of narrative from this larger story? I built a web interface for viewing "The Whale Hunt" that attempts to do just this. So these are all 3,214 pictures taken up there. This is my studio in Brooklyn. This is the Arctic Ocean, and the butchering of the second whale, seven days later. You can start to see some of the story here, told by color. So this red strip signifies the color of the wallpaper in the basement apartment where I was staying. And things go white as we move out onto the Arctic Ocean. Introduction of red down here, when whales are being cut up. You can see a timeline, showing you the exciting moments throughout the story. These are organized chronologically. Wheel provides a slightly more playful version of the same, so these are also all the photographs organized chronologically. And any of these can be clicked, and then the narrative is entered at that position. So here I am sleeping on the airplane heading up to Alaska. That's "Moby Dick." This is the food we ate. This is in the Patkotak's family living room in their house in Barrow. The boxed wine they served us. Cigarette break outside — I don't smoke. This is a really exciting sequence of me sleeping. This is out at whale camp, on the Arctic Ocean. This graph that I'm clicking down here is meant to be reminiscent of a medical heartbeat graph, showing the exciting moments of adrenaline. This is the ice starting to freeze over. The snow fence they built. And so what I'll show you now is the ability to pull out sub-stories. So, here you see the cast. These are all of the people in "The Whale Hunt" and the two whales that were killed down here. And we could do something as arbitrary as, say, extract the story of Rony, involving the concepts of blood and whales and tools, taking place on the Arctic Ocean, at Ahkivgaq camp, with the heartbeat level of fast. And now we've whittled down that whole story to just 29 matching photographs, and then we can enter the narrative at that position. And you can see Rony cutting up the whale here. These whales are about 40 feet long, and weighing over 40 tons. And they provide the food source for the community for much of the year. Skipping ahead a bit more here, this is Rony on the whale carcass. They use no chainsaws or anything; it's entirely just blades, and an incredibly efficient process. This is the guys on the rope, pulling open the carcass. This is the muktuk, or the blubber, all lined up for community distribution. It's baleen. Moving on. So what I'm going to tell you about next is a very new thing. It's not even a project yet. So, just yesterday, I flew in here from Singapore, and before that, I was spending two weeks in Bhutan, the small Himalayan kingdom nestled between Tibet and India. And I was doing a project there about happiness, interviewing a lot of local people. So Bhutan has this really wacky thing where they base most of their high-level governmental decisions around the concept of gross national happiness instead of gross domestic product, and they've been doing this since the '70s. And it leads to just a completely different value system. It's an incredibly non-materialistic culture, where people don't have a lot, but they're incredibly happy. So I went around and I talked to people about some of these ideas. So, I did a number of things. I asked people a number of set questions, and took a number of set photographs, and interviewed them with audio, and also took pictures. I would start by asking people to rate their happiness between one and 10, which is kind of inherently absurd. And then when they answered, I would inflate that number of balloons and give them that number of balloons to hold. So, you have some really happy person holding 10 balloons, and some really sad soul holding one balloon. But you know, even holding one balloon is like, kind of happy. (Laughter) And then I would ask them a number of questions like what was the happiest day in their life, what makes them happy. And then finally, I would ask them to make a wish. And when they made a wish, I would write their wish onto one of the balloons and take a picture of them holding it. So I'm going to show you now just a few brief snippets of some of the interviews that I did, some of the people I spoke with. This is an 11-year-old student. He was playing cops and robbers with his friends, running around town, and they all had plastic toy guns. His wish was to become a police officer. He was getting started early. Those were his hands. I took pictures of everybody's hands, because I think you can often tell a lot about somebody from how their hands look. I took a portrait of everybody, and asked everybody to make a funny face. A 17-year-old student. Her wish was to have been born a boy. She thinks that women have a pretty tough go of things in Bhutan, and it's a lot easier if you're a boy. A 28-year-old cell phone shop owner. If you knew what Paro looked like, you'd understand how amazing it is that there's a cell phone shop there. He wanted to help poor people. A 53-year-old farmer. She was chaffing wheat, and that pile of wheat behind her had taken her about a week to make. She wanted to keep farming until she dies. You can really start to see the stories told by the hands here. She was wearing this silver ring that had the word "love" engraved on it, and she'd found it in the road somewhere. A 16-year-old quarry worker. This guy was breaking rocks with a hammer in the hot sunlight, but he just wanted to spend his life as a farmer. A 21-year-old monk. He was very happy. He wanted to live a long life at the monastery. He had this amazing series of hairs growing out of a mole on the left side of his face, which I'm told is very good luck. He was kind of too shy to make a funny face. A 16-year-old student. She wanted to become an independent woman. I asked her about that, and she said she meant that she doesn't want to be married, because, in her opinion, when you get married in Bhutan as a woman, your chances to live an independent life kind of end, and so she had no interest in that. A 24-year-old truck driver. There are these terrifyingly huge Indian trucks that come careening around one-lane roads with two-lane traffic, with 3,000-foot drop-offs right next to the road, and he was driving one of these trucks. But all he wanted was to just live a comfortable life, like other people. A 24-year-old road sweeper. I caught her on her lunch break. She'd built a little fire to keep warm, right next to the road. Her wish was to marry someone with a car. She wanted a change in her life. She lives in a little worker's camp right next to the road, and she wanted a different lot on things. An 81-year-old itinerant farmer. I saw this guy on the side of the road, and he actually doesn't have a home. He travels from farm to farm each day trying to find work, and then he tries to sleep at whatever farm he gets work at. So his wish was to come with me, so that he had somewhere to live. He had this amazing knife that he pulled out of his gho and started brandishing when I asked him to make a funny face. It was all good-natured. A 10-year-old. He wanted to join a school and learn to read, but his parents didn't have enough money to send him to school. He was eating this orange, sugary candy that he kept dipping his fingers into, and since there was so much saliva on his hands, this orange paste started to form on his palms. (Laughter) A 37-year-old road worker. One of the more touchy political subjects in Bhutan is the use of Indian cheap labor that they import from India to build the roads, and then they send these people home once the roads are built. So these guys were in a worker's gang mixing up asphalt one morning on the side of the highway. His wish was to make some money and open a store. A 75-year-old farmer. She was selling oranges on the side of the road. I asked her about her wish, and she said, "You know, maybe I'll live, maybe I'll die, but I don't have a wish." She was chewing betel nut, which caused her teeth over the years to turn very red. Finally, this is a 26-year-old nun I spoke to. Her wish was to make a pilgrimage to Tibet. I asked her how long she planned to live in the nunnery and she said, "Well, you know, of course, it's impermanent, but my plan is to live here until I'm 30, and then enter a hermitage." And I said, "You mean, like a cave?" And she said, "Yeah, like a cave." And I said, "Wow, and how long will you live in the cave?" And she said, "Well, you know, I think I'd kind of like to live my whole life in the cave." I just thought that was amazing. I mean, she spoke in a way — with amazing English, and amazing humor, and amazing laughter — that made her seem like somebody I could have bumped into on the streets of New York, or in Vermont, where I'm from. But here she had been living in a nunnery for the last seven years. I asked her a little bit more about the cave and what she planned would happen once she went there, you know. What if she saw the truth after just one year, what would she do for the next 35 years in her life? And this is what she said. Woman: I think I'm going to stay for 35. Maybe — maybe I'll die. Jonathan Harris: Maybe you'll die? Woman: Yes. JH: 10 years? Woman: Yes, yes. JH: 10 years, that's a long time. Woman: Yes, not maybe one, 10 years, maybe I can die within one year, or something like that. JH: Are you hoping to? Woman: Ah, because you know, it's impermanent. JH: Yeah, but — yeah, OK. Do you hope — would you prefer to live in the cave for 40 years, or to live for one year? Woman: But I prefer for maybe 40 to 50. JH: 40 to 50? Yeah. Woman: Yes. From then, I'm going to the heaven. JH: Well, I wish you the best of luck with it. Woman: Thank you. JH: I hope it's everything that you hope it will be. So thank you again, so much. Woman: You're most welcome. JH: So if you caught that, she said she hoped to die when she was around 40. That was enough life for her. So, the last thing we did, very quickly, is I took all those wish balloons — there were 117 interviews, 117 wishes — and I brought them up to a place called Dochula, which is a mountain pass in Bhutan, at 10,300 feet, one of the more sacred places in Bhutan. And up there, there are thousands of prayer flags that people have spread out over the years. And we re-inflated all of the balloons, put them up on a string, and hung them up there among the prayer flags. And they're actually still flying up there today. So if any of you have any Bhutan travel plans in the near future, you can go check these out. Here are some images from that. We said a Buddhist prayer so that all these wishes could come true. You can start to see some familiar balloons here. "To make some money and to open a store" was the Indian road worker. Thanks very much. (Applause)

Frequently Occurring Word Combinations


ngrams of length 2

collocation frequency
funny face 3
collecting stories 2
partial glimpse 2
dot corresponds 2
whaling camp 2
long time 2
excitement level 2
arctic ocean 2
exciting moments 2
organized chronologically 2
cell phone 2
phone shop 2
road worker 2
prayer flags 2

ngrams of length 3

collocation frequency
cell phone shop 2


Important Words


  1. ability
  2. absolutely
  3. absurd
  4. accompany
  5. accustomed
  6. addict
  7. adrenaline
  8. age
  9. ah
  10. ahkivgaq
  11. airplane
  12. airport
  13. alaska
  14. alive
  15. amazing
  16. annual
  17. answered
  18. apartment
  19. applause
  20. arbitrary
  21. arctic
  22. area
  23. artifacts
  24. asked
  25. asphalt
  26. assume
  27. ate
  28. attack
  29. attempts
  30. audio
  31. author
  32. automatically
  33. awake
  34. awkward
  35. awkwardly
  36. bad
  37. bailey
  38. baleen
  39. balloon
  40. balloons
  41. barrow
  42. base
  43. basement
  44. basically
  45. beautiful
  46. beginning
  47. betel
  48. bhutan
  49. bigger
  50. bill
  51. bit
  52. blades
  53. blessed
  54. blog
  55. blogger
  56. blood
  57. blubber
  58. body
  59. books
  60. born
  61. bottoms
  62. bowhead
  63. boxed
  64. boy
  65. boyfriend
  66. boys
  67. brandishing
  68. break
  69. breaking
  70. bright
  71. brooklyn
  72. brought
  73. buddhist
  74. build
  75. built
  76. bumped
  77. business
  78. butchering
  79. butterflies
  80. called
  81. camera
  82. camp
  83. camping
  84. camps
  85. cancer
  86. candy
  87. car
  88. carcass
  89. cards
  90. careening
  91. case
  92. cast
  93. caught
  94. caused
  95. cave
  96. caves
  97. cell
  98. chaffing
  99. chainsaws
  100. challenging
  101. chances
  102. change
  103. changing
  104. characters
  105. cheap
  106. check
  107. chewing
  108. chronologically
  109. cigarette
  110. city
  111. clicked
  112. clicking
  113. close
  114. cloudy
  115. coins
  116. collect
  117. collected
  118. collecting
  119. collects
  120. color
  121. colors
  122. combined
  123. comfortable
  124. common
  125. community
  126. completely
  127. complex
  128. components
  129. compositions
  130. computer
  131. concept
  132. concepts
  133. conditions
  134. considered
  135. consist
  136. constructed
  137. contexts
  138. cops
  139. corners
  140. corresponds
  141. crap
  142. crawford
  143. created
  144. culture
  145. cut
  146. cuts
  147. cutting
  148. dark
  149. dates
  150. day
  151. days
  152. daytona
  153. dead
  154. decisions
  155. deeply
  156. demographic
  157. diagonally
  158. diameter
  159. dick
  160. die
  161. dies
  162. digital
  163. dipping
  164. distribution
  165. diving
  166. dochula
  167. documenting
  168. domestic
  169. dominated
  170. dot
  171. dots
  172. drawings
  173. driver
  174. driving
  175. early
  176. easier
  177. easy
  178. eating
  179. edge
  180. efficient
  181. en
  182. english
  183. engraved
  184. enjoy
  185. enter
  186. entered
  187. entire
  188. entries
  189. eskimo
  190. eskimos
  191. excitement
  192. exciting
  193. excuse
  194. existing
  195. experience
  196. experiences
  197. expressed
  198. external
  199. extract
  200. eyes
  201. face
  202. fall
  203. familiar
  204. family
  205. farm
  206. farmer
  207. farming
  208. fast
  209. favorite
  210. feel
  211. feeling
  212. feelings
  213. feels
  214. feet
  215. felt
  216. fence
  217. fill
  218. finally
  219. find
  220. finds
  221. fine
  222. fingers
  223. fire
  224. flags
  225. flew
  226. float
  227. flowers
  228. flutter
  229. flying
  230. food
  231. footprints
  232. forests
  233. form
  234. framework
  235. freeze
  236. frequency
  237. friends
  238. front
  239. frozen
  240. full
  241. fun
  242. fundamental
  243. funny
  244. future
  245. gained
  246. gang
  247. gender
  248. geographic
  249. gho
  250. girl
  251. give
  252. giving
  253. glimpse
  254. glimpses
  255. good
  256. governmental
  257. grabs
  258. graph
  259. gross
  260. ground
  261. grow
  262. growing
  263. guilty
  264. guns
  265. gutter
  266. guy
  267. guys
  268. hairs
  269. hammer
  270. hands
  271. happen
  272. happening
  273. happiest
  274. happiness
  275. happy
  276. harpoon
  277. hauls
  278. heading
  279. heartbeat
  280. heaven
  281. hermitage
  282. heroin
  283. hey
  284. high
  285. highway
  286. himalayan
  287. hold
  288. holding
  289. home
  290. hope
  291. hoped
  292. hoping
  293. hot
  294. hours
  295. house
  296. huge
  297. humor
  298. hung
  299. hunt
  300. ice
  301. idea
  302. ideas
  303. identify
  304. images
  305. imaginary
  306. impermanent
  307. import
  308. incredibly
  309. independent
  310. india
  311. indian
  312. inflate
  313. information
  314. inherently
  315. insects
  316. interest
  317. interested
  318. interesting
  319. interface
  320. internet
  321. intersecting
  322. intervals
  323. interviewed
  324. interviewing
  325. interviews
  326. introduction
  327. inupiat
  328. involving
  329. itinerant
  330. japan
  331. join
  332. jonathan
  333. judy
  334. keeping
  335. killed
  336. kind
  337. kingdom
  338. kissed
  339. kisses
  340. kissing
  341. knew
  342. knife
  343. knowing
  344. labor
  345. large
  346. larger
  347. laughter
  348. launched
  349. lead
  350. leads
  351. learn
  352. leaving
  353. lectures
  354. led
  355. left
  356. length
  357. letting
  358. level
  359. life
  360. limestone
  361. lined
  362. live
  363. lived
  364. lives
  365. living
  366. local
  367. locally
  368. location
  369. long
  370. longer
  371. looked
  372. lot
  373. love
  374. loved
  375. lucas
  376. luck
  377. lunch
  378. lying
  379. map
  380. married
  381. marry
  382. masse
  383. matching
  384. meant
  385. medical
  386. medium
  387. mediums
  388. meet
  389. messy
  390. meth
  391. migrate
  392. miles
  393. million
  394. mind
  395. minutes
  396. mixing
  397. mobs
  398. mole
  399. moment
  400. moments
  401. monastery
  402. money
  403. monk
  404. montage
  405. montages
  406. month
  407. morning
  408. mountain
  409. move
  410. movement
  411. movies
  412. moving
  413. muktuk
  414. narrative
  415. narrator
  416. national
  417. nature
  418. neck
  419. nestled
  420. newark
  421. newer
  422. newly
  423. north
  424. northernmost
  425. noticed
  426. notion
  427. novels
  428. nuanced
  429. number
  430. numerous
  431. nun
  432. nunnery
  433. nut
  434. objects
  435. occur
  436. occurrences
  437. ocean
  438. officer
  439. omniscient
  440. online
  441. open
  442. opened
  443. opinion
  444. opinions
  445. opposed
  446. orange
  447. oranges
  448. order
  449. organized
  450. overlapping
  451. owner
  452. pace
  453. pack
  454. paintings
  455. pajama
  456. palms
  457. parallel
  458. parents
  459. parked
  460. paro
  461. partial
  462. pass
  463. paste
  464. pasted
  465. people
  466. period
  467. person
  468. personal
  469. phone
  470. photo
  471. photograph
  472. photographed
  473. photographic
  474. photographs
  475. phrases
  476. physical
  477. picture
  478. pictures
  479. pile
  480. pilgrimage
  481. place
  482. places
  483. plan
  484. planned
  485. plans
  486. plastic
  487. playful
  488. playing
  489. police
  490. political
  491. poor
  492. portrait
  493. position
  494. posted
  495. posts
  496. pounds
  497. prayer
  498. prefer
  499. presentation
  500. presented
  501. preserve
  502. pretty
  503. princeton
  504. private
  505. process
  506. product
  507. programs
  508. project
  509. projects
  510. provide
  511. publicly
  512. pull
  513. pulled
  514. pulling
  515. put
  516. python
  517. quarry
  518. questions
  519. quickly
  520. racing
  521. radio
  522. raindrop
  523. rainy
  524. rate
  525. read
  526. real
  527. reality
  528. records
  529. recovering
  530. red
  531. reminiscent
  532. represent
  533. rest
  534. reveal
  535. ride
  536. ring
  537. road
  538. roads
  539. robbers
  540. rocks
  541. rony
  542. room
  543. rope
  544. rough
  545. running
  546. rusting
  547. sacred
  548. sad
  549. saliva
  550. sassy
  551. scans
  552. school
  553. science
  554. scores
  555. screwing
  556. searching
  557. selling
  558. send
  559. sense
  560. sentence
  561. sentences
  562. sequence
  563. series
  564. served
  565. set
  566. sets
  567. settlement
  568. sexy
  569. shop
  570. shore
  571. short
  572. show
  573. showing
  574. shy
  575. side
  576. signifies
  577. silver
  578. simeon
  579. singapore
  580. single
  581. sketchbooks
  582. skinny
  583. skipping
  584. sleep
  585. sleeping
  586. slightly
  587. slowed
  588. small
  589. smoke
  590. snippets
  591. snow
  592. snowy
  593. sorts
  594. soul
  595. source
  596. specifically
  597. sped
  598. speed
  599. spend
  600. spending
  601. spent
  602. spiritual
  603. spoke
  604. spots
  605. spread
  606. spring
  607. springtime
  608. stage
  609. start
  610. started
  611. starting
  612. stated
  613. states
  614. statistical
  615. stay
  616. staying
  617. stop
  618. store
  619. stories
  620. story
  621. street
  622. streets
  623. string
  624. strip
  625. stubs
  626. student
  627. studio
  628. study
  629. studying
  630. subjects
  631. suddenly
  632. sugary
  633. sunlight
  634. sunny
  635. supply
  636. surface
  637. sweeper
  638. swirl
  639. system
  640. talk
  641. talked
  642. talking
  643. tattered
  644. taxi
  645. teeth
  646. terrifyingly
  647. thick
  648. thinks
  649. thought
  650. thoughts
  651. thousands
  652. throws
  653. tibet
  654. ticket
  655. tight
  656. time
  657. timeline
  658. timer
  659. today
  660. told
  661. tons
  662. tools
  663. touching
  664. touchy
  665. tough
  666. town
  667. toy
  668. trading
  669. traffic
  670. trails
  671. traits
  672. travel
  673. travels
  674. tripod
  675. truck
  676. trucks
  677. true
  678. truth
  679. turn
  680. type
  681. types
  682. uncomfortable
  683. unconventional
  684. understand
  685. united
  686. universe
  687. university
  688. vermont
  689. version
  690. viewing
  691. voice
  692. wacky
  693. wait
  694. waits
  695. wallpaper
  696. wanted
  697. warm
  698. water
  699. watercolor
  700. ways
  701. wearing
  702. weather
  703. web
  704. week
  705. weeks
  706. weighing
  707. whale
  708. whales
  709. whaling
  710. wheat
  711. wheel
  712. white
  713. whittled
  714. wig
  715. wildlife
  716. wine
  717. wiring
  718. wishes
  719. woman
  720. women
  721. word
  722. words
  723. work
  724. worker
  725. world
  726. worth
  727. write
  728. writings
  729. wrong
  730. wrote
  731. yeah
  732. year
  733. years
  734. yesterday
  735. york