full transcript

From the Ted Talk by Dan Berkenstock: The world is one big dataset. Now, how to photograph it ...

Unscramble the Blue Letters


Now it was using the lessons learned from these early missions that my fnrieds and I began a series of sketches of our own satellite design. And I can't remember a specific day where we made a conscious decision that we were actually going to go out and build these things, but once we got that idea in our mnids of the wlord as a dataset, of being able to capture mliolins of data points on a daliy basis describing the global economy, of being able to unearth billions of connections between them that had never before been found, it just seemed boring to go work on anything else.

And so we moved into a cramped, windowless ocfife in Palo Alto, and began working to take our design from the drawing board into the lab. The first major question we had to tackle was just how big to build this thing. In space, size drives cost, and we had worked with these very small, breadbox-sized satellites in school, but as we began to better understand the laws of physics, we found that the qaiulty of pictures those satellites could take was very limited, because the laws of physics dictate that the best picture you can take through a telescope is a function of the diameter of that telescope, and these satellites had a very salml, very constrained volume. And we found that the best ptcurie we would have been able to get looked something like this. Although this was the low-cost option, quite frankly it was just too blurry to see the things that make satellite imagery valuable. So about three or four weeks later, we met a group of engineers randomly who had weorkd on the first ptriave imaging sltteilae ever developed, and they told us that back in the 1970s, the U.S. government had found a powerful optimal toafderf — that in taking pictures at right about one meter resolution, being able to see objects one meter in size, they had found that they could not just get very high-quality images, but get a lot of them at an ablfadfroe price. From our own computer simulations, we quickly found that one meter really was the mniiumm viable product to be able to see the drivers of our global economy, for the first time, being able to cuont the ships and cars and shipping ctrinaenos and trckus that move around our world on a daily basis, while cnneniotlevy still not being able to see individuals. We had found our compromise. We would have to build something larger than the original breadbox, now more like a mini-fridge, but we still wouldn't have to build a pickup truck. So now we had our constraint. The laws of physics dittecad the absolute minimum-sized tlosepece that we could build.

Open Cloze


Now it was using the lessons learned from these early missions that my _______ and I began a series of sketches of our own satellite design. And I can't remember a specific day where we made a conscious decision that we were actually going to go out and build these things, but once we got that idea in our _____ of the _____ as a dataset, of being able to capture ________ of data points on a _____ basis describing the global economy, of being able to unearth billions of connections between them that had never before been found, it just seemed boring to go work on anything else.

And so we moved into a cramped, windowless ______ in Palo Alto, and began working to take our design from the drawing board into the lab. The first major question we had to tackle was just how big to build this thing. In space, size drives cost, and we had worked with these very small, breadbox-sized satellites in school, but as we began to better understand the laws of physics, we found that the _______ of pictures those satellites could take was very limited, because the laws of physics dictate that the best picture you can take through a telescope is a function of the diameter of that telescope, and these satellites had a very _____, very constrained volume. And we found that the best _______ we would have been able to get looked something like this. Although this was the low-cost option, quite frankly it was just too blurry to see the things that make satellite imagery valuable. So about three or four weeks later, we met a group of engineers randomly who had ______ on the first _______ imaging _________ ever developed, and they told us that back in the 1970s, the U.S. government had found a powerful optimal ________ — that in taking pictures at right about one meter resolution, being able to see objects one meter in size, they had found that they could not just get very high-quality images, but get a lot of them at an __________ price. From our own computer simulations, we quickly found that one meter really was the _______ viable product to be able to see the drivers of our global economy, for the first time, being able to _____ the ships and cars and shipping __________ and ______ that move around our world on a daily basis, while ____________ still not being able to see individuals. We had found our compromise. We would have to build something larger than the original breadbox, now more like a mini-fridge, but we still wouldn't have to build a pickup truck. So now we had our constraint. The laws of physics ________ the absolute minimum-sized _________ that we could build.

Solution


  1. conveniently
  2. friends
  3. containers
  4. tradeoff
  5. dictated
  6. minds
  7. affordable
  8. daily
  9. worked
  10. office
  11. minimum
  12. satellite
  13. private
  14. picture
  15. world
  16. count
  17. quality
  18. trucks
  19. telescope
  20. millions
  21. small

Original Text


Now it was using the lessons learned from these early missions that my friends and I began a series of sketches of our own satellite design. And I can't remember a specific day where we made a conscious decision that we were actually going to go out and build these things, but once we got that idea in our minds of the world as a dataset, of being able to capture millions of data points on a daily basis describing the global economy, of being able to unearth billions of connections between them that had never before been found, it just seemed boring to go work on anything else.

And so we moved into a cramped, windowless office in Palo Alto, and began working to take our design from the drawing board into the lab. The first major question we had to tackle was just how big to build this thing. In space, size drives cost, and we had worked with these very small, breadbox-sized satellites in school, but as we began to better understand the laws of physics, we found that the quality of pictures those satellites could take was very limited, because the laws of physics dictate that the best picture you can take through a telescope is a function of the diameter of that telescope, and these satellites had a very small, very constrained volume. And we found that the best picture we would have been able to get looked something like this. Although this was the low-cost option, quite frankly it was just too blurry to see the things that make satellite imagery valuable. So about three or four weeks later, we met a group of engineers randomly who had worked on the first private imaging satellite ever developed, and they told us that back in the 1970s, the U.S. government had found a powerful optimal tradeoff — that in taking pictures at right about one meter resolution, being able to see objects one meter in size, they had found that they could not just get very high-quality images, but get a lot of them at an affordable price. From our own computer simulations, we quickly found that one meter really was the minimum viable product to be able to see the drivers of our global economy, for the first time, being able to count the ships and cars and shipping containers and trucks that move around our world on a daily basis, while conveniently still not being able to see individuals. We had found our compromise. We would have to build something larger than the original breadbox, now more like a mini-fridge, but we still wouldn't have to build a pickup truck. So now we had our constraint. The laws of physics dictated the absolute minimum-sized telescope that we could build.

Frequently Occurring Word Combinations


ngrams of length 2

collocation frequency
satellite imagery 4
daily basis 4
data scientist 2
satellite design 2
imaging satellites 2
short weeks 2


Important Words


  1. absolute
  2. affordable
  3. alto
  4. basis
  5. began
  6. big
  7. billions
  8. blurry
  9. board
  10. boring
  11. breadbox
  12. build
  13. capture
  14. cars
  15. compromise
  16. computer
  17. connections
  18. conscious
  19. constrained
  20. constraint
  21. containers
  22. conveniently
  23. cost
  24. count
  25. cramped
  26. daily
  27. data
  28. dataset
  29. day
  30. decision
  31. describing
  32. design
  33. developed
  34. diameter
  35. dictate
  36. dictated
  37. drawing
  38. drivers
  39. drives
  40. early
  41. economy
  42. engineers
  43. frankly
  44. friends
  45. function
  46. global
  47. government
  48. group
  49. idea
  50. imagery
  51. images
  52. imaging
  53. individuals
  54. lab
  55. larger
  56. laws
  57. learned
  58. lessons
  59. limited
  60. looked
  61. lot
  62. major
  63. met
  64. meter
  65. millions
  66. minds
  67. minimum
  68. missions
  69. move
  70. moved
  71. objects
  72. office
  73. optimal
  74. option
  75. original
  76. palo
  77. physics
  78. pickup
  79. picture
  80. pictures
  81. points
  82. powerful
  83. price
  84. private
  85. product
  86. quality
  87. question
  88. quickly
  89. randomly
  90. remember
  91. resolution
  92. satellite
  93. satellites
  94. school
  95. series
  96. shipping
  97. ships
  98. simulations
  99. size
  100. sketches
  101. small
  102. space
  103. specific
  104. tackle
  105. telescope
  106. time
  107. told
  108. tradeoff
  109. truck
  110. trucks
  111. understand
  112. unearth
  113. valuable
  114. viable
  115. volume
  116. weeks
  117. windowless
  118. work
  119. worked
  120. working
  121. world