narenarya

thinking about thinking

Apr 23rd, 2014
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  1. John picked up the two double Latte Grandes and walked over to the corner table
  2. near the fireplace where Mary was setting up the chess game. She took a pawn
  3. of each color and concealed them in her hands before offering two fists to John.
  4. Putting the cups down, he tapped Mary’s left hand and was pleased to see the
  5. white piece as he took his chair.
  6.  
  7. John said “Playing chess always reminds me of the game between IBMs Deep
  8. Blue Supercomputer and the reigning World Chess Champion at the time, Garry
  9. Kasparov.” He glanced at the board, “d4, I think,” as he moved his pawn.
  10.  
  11. Mary said, “Me too.” Mary smiled to herself as she moved her own queen’s
  12. pawn forward to d5. She knew that John had strong feelings about the limits of
  13. true Artificial Intelligence and she hoped to gain an advantage by baiting him.
  14. “That was the first time a computer won a complete match against the world’s
  15. best human player. It took almost 50 years of research in the field, but a computer
  16. finally was thinking like a human.”
  17.  
  18. John bristled slightly, but then realized that Mary was just poking a little fun.
  19. Taking his next move, c4, he said “You can guess my position on that subject.
  20. The basic approach of Deep Blue was to decide on a chess move by assessing
  21. all possible moves and responses. It could identify up to a depth of about 14
  22. moves and value-rank the resulting game positions using an algorithm developed
  23. in advance by a team of grand masters. Deep Blue did not think in any real
  24. sense. It was merely computational brute force.”
  25.  
  26. Mary reached over and took John’s pawn, accepting the gambit. “You must
  27. admit,” she replied, “although Kasparov’s ‘thought’ processes were without a
  28. doubt something very different than Deep Blue’s, their performances were very
  29. similar. After all, it was a team of grand masters that designed Deep Blue’s
  30. decision-making ability to think like them.”
  31.  
  32. John played his usual Nc3, continuing the main line of the Queen’s Pawn Gambit.
  33. “You’ve made my point,” he exclaimed, “Deep Blue did not make its own decisions before it moved. All it did was accurately execute, the very sophisticated
  34. judgments that had been preprogrammed by the human experts.”
  35.  
  36. “Let’s look at it from another angle,” Mary said as she moved Nf6. “Much like
  37. a computer, Kasparov’s brain used its billions of neurons to carry out hundreds
  38. of tiny operations per second, none of which, in isolation, demonstrates intelligence. In totality, though, we call his play ‘brilliant’. Kasparov was processing
  39. information very much like a computer does. Over the years, he had memorized
  40. and pre-analyzed thousands of positions and strategies.”
  41.  
  42. “I disagree,” said John quickly moving e3. “Deep Blue’s behavior was merely
  43. logic algebra—expertly and quickly calculated, I admit. However, logic established the rules between positional relationships and sets of value-data. A fundamental set of instructions allowed operations including sequencing, branching,
  44. and recursion within an accepted hierarchy.”
  45.  
  46. Mary grimaced and held up her hands, “No lectures please.” Moving to e6 she
  47. added, “A perfectly reasonable alternative explanation to logic methods is to
  48. use heuristics methods, which observe and mimic the human brain. In particular, pattern recognition seems intimately related to a sequence of unique images
  49. connected by special relationships. Heuristic methods seem as effective in producing AI as logic methods. The success of Deep Blue in chess programming is
  50. important because it employed both logic and heuristic AI methods.”
  51.  
  52. “Now who’s lecturing,” responded John, taking Mary’s pawn with his bishop. “In
  53. my opinion, human grandmasters do not examine 200,000,000 move sequences
  54. per second.”
  55.  
  56. Without hesitation Mary moved c5 and said, “How do we know? Just because
  57. human grandmasters are not aware of searching such a number of positions
  58. doesn’t prove it. Individuals are generally unaware of what actually does go on
  59. in their minds. Patterns in the position suggest what lines of play to look at,
  60. and the pattern recognition processes in the human mind seem to be invisible to
  61. the mind.”
  62.  
  63. John said, “You mean like your playing the same Queen’s Gambit Accepted line
  64. over and over again?” as he castled.
  65.  
  66. Ignoring him, Mary moved a6 and said, “Suppose most of the chess player’s skill
  67. actually comes from an ability to compare the current position against images of
  68. thousands of positions already studied. We would call selecting the best position
  69. (or image) insightful. Still, if the unconscious human version yields intelligent
  70. results, and the explicit algorithmic Deep Blue version yields essentially the same
  71. results, then why can’t I call Deep Blue intelligent too?”
  72.  
  73. John said, “I’m sorry, but for me you’ve overstated your case by calling Deep
  74. Blue intelligent,” moving Qe2. He continued, “Would you like to reconsider your
  75. position?”
  76.  
  77. Mary moved Nc3 and said, “Of course not, I still have plenty of options to think
  78. about alone this line.”
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