1. Neural Networks

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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD
  2. About Neural Networks

    :See also Artificial neural network.

    Traditionally, the term neural network had been used to refer to a network of biological neurons. In more common usage, the term is often used to refer to artificial neural networks, which are composed of artificial neurons or nodes. Thus the term 'Neural Network' has two distinct connotations:
    # Biological neural networks are made up of real biological neurons that are connected or functionally-related in the peripheral nervous system or the central nervous system. In the field of neuroscience, they are often identified as groups of neurons that perform a specific physiological function in laboratory analysis.
    # Artificial neural networks are made up of interconnecting artificial neurons (usually simplified neurons) which may share some properties of biological neural networks. Artificial neural networks may either be used to gain an understanding of biological neural networks, or for solving traditional artificial intelligence tasks without necessarily attempting to model a real biological system.

    Please see the corresponding articles for details on artificial neural networks or biological neural networks. This article focuses on the relationship between the two concepts."

  3. Quotes about Neural Networks

    1. Neural networks are already well known for modeling language.
      In Google Made A Chatbot That Debates The Meaning of Life
    2. It's basically gone from not working to working because of neural networks.
      In Picture this: Microsoft Research project can interpret, caption photos
    3. The chip gives you a highly efficient way of executing neural networks.
      In IBM’s ‘Rodent Brain’ Chip Could Make Our Phones Hyper-Smart