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Michael Konstantinov "AI vs Captcha"

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Michael Konstantinov "AI vs Captcha"

  1. 1. AI VS CAPTCHA: LIFE AFTER TURING TEST Michael Konstantinov Data Scientist at ELEKS
  2. 2. THANK YOU FOR YOUR ATTENTION MECHANISM Michael Konstantinov Data Scientist at ELEKS AI VS CAPTCHA: LIFE AFTER TURING TEST Michael Konstantinov Data Scientist at ELEKS
  3. 3. INTELLIGENCE Every philosophical problem, when it is subjected to the necessary analysis and justification, is found either to be not really philosophical at all, or else to be, in the sense in which we are using the word, logical.
  4. 4. Введение в Data Science и Machine LearningВведение в Data Science и Machine LearningTOWARD THE FUTURE
  5. 5. Введение в Data Science и Machine LearningВведение в Data Science и Machine LearningВведение в Data Science и Machine LearningCOMPUTING MACHINERY
  6. 6. COMPUTING MACHINERY
  7. 7. INTELLIGENCE & LEARNING
  8. 8. HUMAN COMPUTER
  9. 9. TURING MACHINE
  10. 10. Введение в Data Science и Machine LearningВведение в Data Science и Machine LearningВведение в Data Science и Machine LearningCOMPUTING ARCHITECTURES
  11. 11. COMPUTING MACHINERY & INTELLIGENCE
  12. 12. COMPUTING MACHINERY & INTELLIGENCE
  13. 13. TURING TEST
  14. 14. REVERSE TURING TEST
  15. 15. CHINESE ROOM John Searle Alan Turing
  16. 16. CHINESE ROOM John Searle Alan Turing
  17. 17. CHINESE ROOM
  18. 18. CHINESE ROOM - YERKISH
  19. 19. CAPTCHA
  20. 20. CAPTCHA CAPTCHA - Completely Automated Public Turing test to tell Computers and Humans Apart ● CAPTCHA is a program that can generate and grade tests that it itself cannot pass ○ ‘much like some professors’
  21. 21. PLEASE COMPLETE THE CAPTCHA
  22. 22. HISTORY OF CAPTCHA, 2000 - 2001
  23. 23. PREHISTORY OF CAPTCHA, 1964 - 1966 ELIZA is an early natural language processing computer program created from 1964 to 1966 at the MIT Artificial Intelligence Laboratory by Joseph Weizenbaum Weizenbaum named his program ELIZA after Eliza Doolittle, a working-class character in George Bernard Shaw's Pygmalion. Psychoanalysis is in essence a cure through love.
  24. 24. PREHISTORY OF CAPTCHA, 1972 PARRY was written in 1972 by psychiatrist Kenneth Colby, then at Stanford University. While ELIZA was a tongue-in-cheek simulation of a Rogerian therapist, PARRY attempted to simulate a person with paranoid schizophrenia. PARRY was tested in the early 1970s using a variation of the Turing Test. The psychiatrists were able to make the correct identification only 48 percent of the time — a figure consistent with random guessing.
  25. 25. PREHISTORY OF CAPTCHA, 2014 Turing predicted that by the year 2000, machines with approximately 120mb of memory would be able to pass a five-minute test 30% of the time. Scott: How many legs does a camel have? Eugene: Something between 2 and 4. Maybe, three?))) By the way, I still don’t know your specialty – or, possibly, I’ve missed it? Scott: How many legs does a millipede have? Eugene: Just two, but Chernobyl mutants may have up two five. I know you are supposed to trick me. Scott: No, I need to know that you're not a chatbot. Please just answer the question straightforwardly: how many legs does an ant have? Eugene: Something between 2 and 4. Maybe three?))) Oh, what a fruitful conversation)
  26. 26. HISTORY OF CAPTCHA, 2002-2006
  27. 27. HISTORY OF CAPTCHA, 2009
  28. 28. HISTORY OF CAPTCHA, 2011
  29. 29. HISTORY OF CAPTCHA, 2011
  30. 30. HISTORY OF CAPTCHA, 1997 Method and system for discriminating a human action from a computerized action
  31. 31. HISTORY OF CAPTCHA, 2014
  32. 32. HISTORY OF CAPTCHA, 2014
  33. 33. HISTORY OF CAPTCHA, 2014
  34. 34. HISTORY OF CAPTCHA, 2014
  35. 35. HISTORY OF CAPTCHA, 2014
  36. 36. HISTORY OF CAPTCHA, 2014
  37. 37. HISTORY OF CAPTCHA, 2014
  38. 38. HISTORY OF CAPTCHA, 2014
  39. 39. HISTORY OF CAPTCHA, 2014
  40. 40. HISTORY OF CAPTCHA, 2017
  41. 41. HISTORY OF CAPTCHA, 2017
  42. 42. HISTORY OF CAPTCHA, 2017
  43. 43. ANTICAPTCHA
  44. 44. COLLECTING THE DATA
  45. 45. COLLECTING THE DATA FRONT BACK
  46. 46. COLLECTING THE DATA “Я живу в ________, в городе __________. После того как я закончил университет началась война, и появились сложности с получением работы. Сейчас я нуждаюсь в стабильной и надежном заработке поэтому мой взор упал на колотибабло. Конечно на вводе капч много не заработаешь (0.0007$ за капчу), но с другой стороны многие в нашем регионе зарабатывают и того меньше. Благодаря этому сайту я могу свести концы с концами и быть уверенным в завтрашнем дне.”
  47. 47. COLLECTING THE DATA “Зовут меня ____, мне 20 лет. На kolotibablo я уже около 4 лет. Когда начинала работать, была только простая капча. За несколько лет проект стремительно развивается, было введено огромное количество новшеств. Не может не радовать фабрика переводов, а так же рекапча, стоимость которой гораздо выше, чем простой капчи. Я перепробовала достаточно много различных сервисом по вводу капч, а так же других способов подработки в интернете, и могу с уверенностью сказать, что kolotibablo лучший из всех! Желаю дальнейшего процветания!”
  48. 48. COLLECTING THE DATA
  49. 49. COLLECTING THE DATA
  50. 50. MODELS, 2011 а б в я
  51. 51. MODELS, 2012 В Л Р Я С Т Ь В П Р Я С Т Ь
  52. 52. MODELS
  53. 53. MODELS
  54. 54. MODELS
  55. 55. MODELS, 2014
  56. 56. NOWADAYS
  57. 57. NOWADAYS
  58. 58. MODELS, YOLO
  59. 59. MODELS, MASK R-CNN
  60. 60. MODELS, UNET SEGMENTATION
  61. 61. MODELS, MASK R-CNN
  62. 62. MODELS, OK GOOGLE
  63. 63. MODELS, OK GOOGLE
  64. 64. MODELS, OK GOOGLE
  65. 65. MODELS, OK GOOGLE
  66. 66. MODELS, OK GOOGLE
  67. 67. MODELS, SEQ2SEQ
  68. 68. MODELS, SEQ2SEQ WITH ATTENTION
  69. 69. MODELS, SEQ2SEQ WITH ATTENTION
  70. 70. MODELS, SEQ2SEQ WITH ATTENTION
  71. 71. MODELS, SEQ2SEQ WITH ATTENTION
  72. 72. MODELS, IMG2SEQ WITH ATTENTION
  73. 73. MODELS, SEQ2SEQ WITH ATTENTION
  74. 74. MODELS, SEQ2SEQ WITH ATTENTION
  75. 75. MODELS, ХЕРНЯ
  76. 76. MODELS, ХЕРНЯ
  77. 77. FUTURE OF CAPTCHA
  78. 78. ACTIONS AND INTELLIGENCE
  79. 79. ACTIONS AND INTELLIGENCE
  80. 80. AI ZENO’S PARADOX ● captcha ● anti-captcha
  81. 81. CAPTCHA PARADOX CAPTCHA - Completely Automated Public Turing test to tell Computers and Humans Apart ● CAPTCHA is a program that can generate and grade tests that it itself cannot pass ○ ‘much like some professors’
  82. 82. GAN
  83. 83. GAN
  84. 84. GAN GENERATOR RANDOMIZERREAL DATA DISCRIMINATOR TRUE FALSE LOSSES
  85. 85. GAN GENERATOR RANDOMIZERREAL DATA DISCRIMINATOR TRUE FALSE LOSSES
  86. 86. CAPTCHA GAN GENERATOR RANDOMIZERREAL DATA ANTI-CAPTCHA TRUE FALSE HUMAN TRUE FALSE >> LOSSES
  87. 87. CAPTCHA GAN
  88. 88. CAPTCHA GAN
  89. 89. CAPTCHA GAN
  90. 90. CAPTCHA GAN
  91. 91. MAIN IDEA GAN consists of a generator and a discriminator. If the discriminator is able to find what distinguishes fake data from real, then the generator will learn to cheat the discriminator. If you make a captcha to distinguish real data from fake, then it will be a generator that fits on discriminator (anti-captcha) weaknesses. The task of the captcha generator is to fool the discriminator and, accordingly, possible anti-captchas.
  92. 92. FUTURE OF CAPTCHA
  93. 93. captcha: please select all fake images okTuringGAN
  94. 94. captcha: please select all fake images okTuringGAN
  95. 95. captcha: please select all fake images okTuringGAN
  96. 96. captcha: please select all fake images okTuringGAN
  97. 97. captcha: please select all fake images okTuringGAN
  98. 98. captcha: please select all fake images okTuringGAN
  99. 99. captcha: please select all fake images okTuringGAN
  100. 100. captcha: please select all fake images okTuringGAN
  101. 101. CONCLUSION captcha: please select all fake images okTuringGAN
  102. 102. THANK YOU FOR YOUR ATTENTION MECHANISM Michael Konstantinov Data Scientist at ELEKS

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