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Is there a place here away from riff-raffs and peasants?

Discussion in 'The Courtyard Café' started by pakchewcheng, Oct 1, 2017.

  1. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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    China is opening a new quantum research supercenter


    The country wants to build a quantum computer with a million times the computing power of all others presently in the world.





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    NATIONAL LABORATORY FOR QUANTUM INFORMATION SCIENCES

    The $10 billion National Laboratory for Quantum Information Sciences in Hefei will be the center of China's attempt to take the global lead in quantum computing and sensing.

    CNTV

    On 37 hectares (nearly 4 million square feet) in Hefei, Anhui Province, China is building a $10 billion research center for quantum applications. This news comes on the heels of the world's first video call made via quantum-encrypted communications and the completion of a quantum-encrypted fiber optic trunk cable.

    The National Laboratory for Quantum Information Sciences, slated to open in 2020, has two major research goals: quantum metrology and building a quantum computer. Both efforts would support military and national defense efforts, as well civilian innovators.
     
  2. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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  3. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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  4. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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  5. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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  6. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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    [​IMG]

    Remember AlphaGo? You know, the artificial intelligence that in 2016 soundly defeated the finest players humanity could muster in the ancient Chinese strategy game of Go; thus forcing us to relinquish the last vestige of board game superiority flesh-and-blood held over machines?

    Remember that?

    Well, here’s something to chew on: Google’s AI research arm DeepMind, the same benevolent creator that spawned AlphaGo, has already rendered that gluteus maximus-spanking version obsolete. In a study published Wednesday in the journal Nature, researchers describe a swifter, leaner, autodidact AI that defeated AlphaGo 100 games to zero. Zilch. Nada. Nothing.

    Appropriately, this new AI prodigy is named AlphaGo Zero, and its secret to superiority is truly fascinating.


    With this, it marks the first real step into true AI.
    And hopefully in time, we have an AI, whether they like it or not, to be our government and our leader of a Renaissance Singapore instead of all those self serving cockroaches who know only how to laugh all the way to the banks and fucking us all the time in the process .
     
  7. pakchewcheng

    pakchewcheng Alfrescian Old Timer

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    What is Go (WeiChi) ?

    The game of Go originated in China 3,000 years ago. The rules of the game are simple: players take turns to place black or white stones on a board, trying to capture the opponent's stones or surround empty space to make points of territory. As simple as the rules are, Go is a game of profound complexity. There are an astonishing 10 to the power of 170 possible board configurations - more than the number of atoms in the known universe - making Go a googol times more complex than Chess.

    Go is played primarily through intuition and feel, and because of its beauty, subtlety and intellectual depth it has captured the human imagination for centuries.

    Interested in discovering the game of Go for yourself, but not sure where to start? Head over to this interactive online training game!

    Mastering the game of Go
    The complexity of Go means it has long been viewed as the most challenging of classical games for artificial intelligence. Despite decades of work, the strongest computer Go programs were only able to play at the level of human amateurs.

    Traditional AI methods, which construct a search tree over all possible positions, don’t have a chance in Go. This is because of the sheer number of possible moves and the difficulty of evaluating the strength of each possible board position.

    In order to capture the intuitive aspect of the game, we knew that we would need to take a novel approach. AlphaGo therefore combines an advanced tree search with deep neural networks. These neural networks take a description of the Go board as an input and process it through a number of different network layers containing millions of neuron-like connections. One neural network, the “policy network”, selects the next move to play. The other neural network, the “value network”, predicts the winner of the game.

    We showed AlphaGo a large number of strong amateur games to help it develop its own understanding of what reasonable human play looks like. Then we had it play against different versions of itself thousands of times, each time learning from its mistakes and incrementally improving until it became immensely strong, through a process known as reinforcement learning.

    Our Nature paper, published on 28th January 2016, describes the technical details behind this original approach in greater detail.

    Read more about how AlphaGo uses machine learning to master the game of Go in our blog post.
     
  8. eatshitndie

    eatshitndie Alfrescian (Inf)

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    how about riff raff jeans coming onto the apparel market in 2018?

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