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Thread: Nick Land and Neocameralism

  1. #391
    Join Date
    Oct 2004
    The Fear - Dublin


    There's more possible Go moves than atoms in the known universe.

  2. #392


    way, way more (at least 10^(10^48) according to

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  4. #393


    even chess has more moves than the universe has atoms - at least according to shannon. fact is the number of atoms in the universe is just not that big compared to the number of possible states in a typical game (complexity in a game can grow very fast). football, for example, is far more complicated, with an infinite number of possible game states.

  5. #394
    Join Date
    Jun 2006


    If you want a real computational challenge, try estimating lower bound on the number of different Scrabble games (using a given set of allowed words, of course).

    People have made estimates: https://sublimityofinfinity.wordpres...-there-part-3/ but I don't know how rigorous these are really.
    Doin' the Lambeth Warp New: DISSENSUS - THE NOVEL - PM me your email address and I'll add you

  6. #395
    Join Date
    Jan 2018


    " ... his ballyhooed philosophy appears to consist of little more than gothic sci-fi-flavored intellectualizations of his fantasies of oppressing the poor by remote control from an automated oriental massage parlor."

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  8. #396

  9. #397


    The first hints of that vocabulary emerged in 1962, when Torsten Wiesel and David Hubel showed that specific neurons in the brain’s visual centers are tuned to specific stimuli—lights moving in particular directions, or lines aligned in particular ways. Since then, other neuroscientists have identified neurons that respond to colors, curvatures, faces, hands, and outdoor scenes. But here’s the catch: Those scientists always chose which kinds of shape to test, and their intuition might not reflect the actual stimuli to which the neurons are attuned. “Just because a cell responds to a specific category of image doesn’t mean you really understand what it wants,” says Livingstone.

    So why not ask the neurons what they want to see?

    That was the idea behind XDREAM, an algorithm dreamed up by a Harvard student named Will Xiao. Sets of those gray, formless images, 40 in all, were shown to watching monkeys, and the algorithm tweaked and shuffled those that provoked the strongest responses in chosen neurons to create a new generation of pics. Xiao had previously trained XDREAM using 1.4 million real-world photos so that it would generate synthetic images with the properties of natural ones. Over 250 such generations, the synthetic images became more and more effective, until they were exciting their target neurons far more intensely than any natural image. “It was exciting to finally let a cell tell us what it’s encoding instead of having to guess,” says Ponce, who is now at Washington University in St. Louis.

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