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 cocnteillg stories in some unconventional ways. This is a picture of me from a very awkward stage in my life. You might enjoy the awkwardly thgit, cut-off pajama bottoms with balloons. Anyway, it was a time when I was mainly interested in collecting iianamrgy 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, seitros 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 stros of things, records of my lived experience: so watercolor paintings, drawings of what I see, dead flowers, dead insects, patesd ticket stubs, rusting coins, business cards, wnigitrs. 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 stertad 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 cpumetor seicnce at ptieorcnn usieirtnvy, and I noticed that it was suddenly possible to ccoellt these sorts of personal articftas, not just from street corners, but also from the Internet. And that sdeldnuy, plpoee, en masse, were leaving scores and scores of digital footprints online that told stories of their private lives. Blog posts, photographs, thoughts, feelings, oiponins, 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 fnoittoprs. One such project is about a year and a half old. It's called "We Feel Fine." This is a project that sancs 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 stenence 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 cnnoitiods were like when they wrote that sentence. It ccetlols about 20,000 such sentences a day and it's been running for about a year and a half, having ceetolcld 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 fgenelis 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 fleenig inside, so the bhrigt 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 bgiger 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 bfriyenod," 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 rgouh now, and I probably gained 100,000 pounds, but it was worth it." "I love how they were able to pvsreere most in everything that makes you feel close to nature — butterflies, man-made forests, ltoemnsie 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 cmomon feelings overall right now, deamontid by better, then bad, then good, then guilty, and so on. Weather causes the feelings to amusse the physical titras of the weather they represent. So the sunny ones swirl around, the cloudy ones float along, the riany 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 stpos 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 plaerlal universe." (Laughter) "I've kissed numerous other boys and it hasn't felt good, the kisses felt mssey and wrong, but kissing Lucas feels beautiful and almost spiritual." "I can feel my cancer grow." "I feel pretty." "I feel snnkiy, 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 seped." (Laughter) "I feel ssasy." "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 sroht as two or three words. So, really even challenging the notion of what can be considered a story. And recently, I've become isrtetneed in diving much more delpey into a single story. And that's led me to doing some work with the pacsyhil 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 brraow, Alaska, the ntrhosenmort settlement in the United States, with a family of Inupiat emoisks, 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 waelhs migrate ntroh each springtime. And the emksio cmtoinumy basically cmpas out on the edge of the ice here, waits for a whale to come close enough to aatctk. And when it does, it throws a hooaprn at it, and then hauls the whale up under the ice, and cuts it up. And that would pvrodie the community's food supply for a long time. So I went up there, and I lived with these guys out in their wnilhag 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 pgphrehatood that etnire experience at five-minute intervals. So every five minetus, I took a photograph. When I was awake, with the camera around my neck. When I was sleeping, with a tirpod and a timer. And then in moments of high adrenaline, like when something exciting was hnaneppig, I would up that phgpthaioroc frequency to as many as 37 photographs in five minutes. So what this created was a photographic htaberaet that sped up and soewld down, more or less matching the changing pace of my own heartbeat. That was the first cenopct 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 cloros. 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 lerteucs like this one — we're very acuoesctmd to this idea of the narrator or the camera position, some kind of omniscient, ertenaxl 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 tpyes 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 eitecxnmet 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 beuchtnirg of the second whale, seven days later. You can start to see some of the sroty here, told by coolr. So this red strip sfenigiis the color of the wallpaper in the basement ampeatrnt where I was staying. And things go withe as we move out onto the Arctic Ocean. iotodinrtcun 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 pyflual version of the same, so these are also all the photographs organized chronologically. And any of these can be clicked, and then the nriavtrae is entered at that position. So here I am sleeping on the airplane heading up to alkasa. That's "Moby Dick." This is the food we ate. This is in the Patkotak's failmy 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 meicdal heartbeat graph, soniwhg 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 cectnpos of bolod and whales and tools, taking place on the aitcrc ocaen, at Ahkivgaq camp, with the heartbeat level of fast. And now we've wthltied down that whole story to just 29 mnaihtcg pathpoorhgs, 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 wlhae 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 prjeoct there about happiness, interviewing a lot of local people. So Bhutan has this really wacky thing where they base most of their high-level gnenmertavol decisions around the concept of gross ntoanail hipanesps instead of gross diesomtc 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 qseuotins, 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 nebumr of balloons to hold. So, you have some really happy perosn holding 10 balloons, and some really sad soul hndiolg 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 hpapy. And then fiallny, 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 ofeficr. He was getting started early. Those were his hands. I took pictures of everybody's hnads, 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 woemn 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 uanndsterd 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 cnhiffag wheat, and that pile of weaht 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 wtaned 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 fnuny face. A 16-year-old student. She wanted to become an idnennepdet 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 caechns 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 cniereang 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 coftorlbmae 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 mrray someone with a car. She wanted a cnhage 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 fearmr. 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 mneoy to send him to school. He was etaing this orange, sgaury candy that he kept dipping his fenrgis 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 sbuecjts in Bhutan is the use of Indian cheap labor that they import from iinda to build the roads, and then they send these people home once the roads are bulit. So these guys were in a worker's gang mxniig 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 slileng 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 tbeit. I aeskd 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 etenr a hgraitmee." 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 ltuegahr — 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 pnelnad 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. jahaontn 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 yaers, 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 pfeerr 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 qlckuiy, is I took all those wish balloons — there were 117 interviews, 117 whseis — and I brought them up to a plcae cllaed Dochula, which is a mountain pass in buthan, 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 bnoalols, 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 sratt to see some faiimlar balloons here. "To make some money and to open a store" was the Indian road worker. Thanks very much. (Applause)

Open Cloze

So I'm going to talk today about __________ stories in some unconventional ways. This is a picture of me from a very awkward stage in my life. You might enjoy the awkwardly _____, cut-off pajama bottoms with balloons. Anyway, it was a time when I was mainly interested in collecting _________ 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, _______ 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 _____ of things, records of my lived experience: so watercolor paintings, drawings of what I see, dead flowers, dead insects, ______ ticket stubs, rusting coins, business cards, ________. 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 _______ 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 ________ _______ at _________ __________, and I noticed that it was suddenly possible to _______ these sorts of personal _________, not just from street corners, but also from the Internet. And that ________, ______, en masse, were leaving scores and scores of digital footprints online that told stories of their private lives. Blog posts, photographs, thoughts, feelings, ________, 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 __________. One such project is about a year and a half old. It's called "We Feel Fine." This is a project that _____ 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 ________ 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 __________ were like when they wrote that sentence. It ________ about 20,000 such sentences a day and it's been running for about a year and a half, having _________ 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 ________ 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 _______ inside, so the ______ 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 ______ 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 _________," 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 _____ now, and I probably gained 100,000 pounds, but it was worth it." "I love how they were able to ________ most in everything that makes you feel close to nature — butterflies, man-made forests, _________ 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, _________ by better, then bad, then good, then guilty, and so on. Weather causes the feelings to ______ the physical ______ of the weather they represent. So the sunny ones swirl around, the cloudy ones float along, the _____ 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 _____ 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 ________ universe." (Laughter) "I've kissed numerous other boys and it hasn't felt good, the kisses felt _____ and wrong, but kissing Lucas feels beautiful and almost spiritual." "I can feel my cancer grow." "I feel pretty." "I feel ______, 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 _____." (Laughter) "I feel _____." "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 _____ as two or three words. So, really even challenging the notion of what can be considered a story. And recently, I've become __________ in diving much more ______ into a single story. And that's led me to doing some work with the ________ 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 ______, Alaska, the ____________ settlement in the United 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, 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 ______ migrate _____ each springtime. And the ______ _________ basically _____ out on the edge of the ice here, waits for a whale to come close enough to ______. And when it does, it throws a _______ at it, and then hauls the whale up under the ice, and cuts it up. And that would _______ the community's food supply for a long time. So I went up there, and I lived with these guys out in their _______ 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 ____________ that ______ 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 ______ and a timer. And then in moments of high adrenaline, like when something exciting was _________, I would up that ____________ frequency to as many as 37 photographs in five minutes. So what this created was a photographic _________ that sped up and ______ down, more or less matching the changing pace of my own heartbeat. That was the first _______ 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 ______. 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 ________ like this one — we're very __________ to this idea of the narrator or the camera position, some kind of omniscient, ________ 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 _____ 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 __________ 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 __________ of the second whale, seven days later. You can start to see some of the _____ here, told by _____. So this red strip _________ the color of the wallpaper in the basement _________ where I was staying. And things go _____ as we move out onto the Arctic Ocean. ____________ 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 entered at that position. So here I am sleeping on the airplane heading up to ______. That's "Moby Dick." This is the food we ate. This is in the Patkotak's ______ 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 _______ heartbeat graph, _______ 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 ________ of _____ and whales and tools, taking place on the ______ _____, at Ahkivgaq camp, with the heartbeat level of fast. And now we've ________ down that whole story to just 29 ________ ___________, 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 _____ 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 _______ there about happiness, interviewing a lot of local people. So Bhutan has this really wacky thing where they base most of their high-level ____________ decisions around the concept of gross ________ _________ instead of gross ________ 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 _________, 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 ______ of balloons to hold. So, you have some really happy ______ holding 10 balloons, and some really sad soul _______ 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 _____. And then _______, 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 _____, 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 _____ 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 __________ 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 ________ 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 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 ______ 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 _____ face. A 16-year-old student. She wanted to become an ___________ 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 _______ 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 _________ 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 ___________ 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 _____ someone with a car. She wanted a ______ 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 ______. 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 _____ to send him to school. He was ______ this orange, ______ candy that he kept dipping his _______ 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 ________ in Bhutan is the use of Indian cheap labor that they import from _____ to build the roads, and then they send these people home once the roads are _____. So these guys were in a worker's gang ______ 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 _______ 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 _____. I _____ 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 _____ 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 amazing. I mean, she spoke in a way — with amazing English, and amazing humor, and amazing ________ — 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 _______ 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. ________ 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 _____, 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 ______ — and I brought them up to a _____ ______ Dochula, which is a mountain pass in ______, 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 ________, 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 _____ to see some ________ balloons here. "To make some money and to open a store" was the Indian road worker. Thanks very much. (Applause)

Solution

  1. minutes
  2. balloons
  3. camps
  4. attack
  5. mixing
  6. harpoon
  7. interested
  8. questions
  9. national
  10. assume
  11. money
  12. called
  13. common
  14. funny
  15. artifacts
  16. photographic
  17. suddenly
  18. ocean
  19. hands
  20. photographs
  21. university
  22. colors
  23. marry
  24. women
  25. north
  26. chances
  27. imaginary
  28. community
  29. stories
  30. blood
  31. india
  32. careening
  33. tibet
  34. science
  35. comfortable
  36. princeton
  37. boyfriend
  38. butchering
  39. white
  40. playful
  41. hermitage
  42. alaska
  43. familiar
  44. bhutan
  45. quickly
  46. jonathan
  47. farmer
  48. spots
  49. governmental
  50. external
  51. eating
  52. concept
  53. happy
  54. parallel
  55. sassy
  56. built
  57. laughter
  58. change
  59. domestic
  60. wheat
  61. medical
  62. concepts
  63. writings
  64. showing
  65. subjects
  66. story
  67. opinions
  68. apartment
  69. finally
  70. preserve
  71. place
  72. skinny
  73. introduction
  74. northernmost
  75. whaling
  76. officer
  77. whales
  78. people
  79. whittled
  80. feelings
  81. collected
  82. rough
  83. fingers
  84. chaffing
  85. pasted
  86. footprints
  87. messy
  88. tripod
  89. wishes
  90. signifies
  91. eskimos
  92. independent
  93. collecting
  94. sorts
  95. collect
  96. asked
  97. feeling
  98. rainy
  99. photographed
  100. heartbeat
  101. eskimo
  102. family
  103. start
  104. wanted
  105. slowed
  106. understand
  107. traits
  108. dominated
  109. arctic
  110. bigger
  111. enter
  112. accustomed
  113. person
  114. short
  115. lectures
  116. physical
  117. project
  118. prefer
  119. planned
  120. narrative
  121. bright
  122. barrow
  123. scans
  124. entire
  125. whale
  126. matching
  127. sentence
  128. provide
  129. number
  130. deeply
  131. computer
  132. types
  133. years
  134. tight
  135. selling
  136. color
  137. speed
  138. conditions
  139. excitement
  140. started
  141. collects
  142. happiness
  143. limestone
  144. happening
  145. sugary
  146. holding

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)

ngrams of length 2

collocation frequency
whale hunt 6
arctic ocean 5
feel fine 4
funny face 3

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