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The Generation of Semantics in Natural Language and the Formation of Brain Intelligence
  • Lei Tang
Lei Tang
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This paper first discussed that based on the radial basis function principle, the brain neuron system has achieved the primary representations to color, sound, and object shape. Note that this is a kind of distributed representation approach, and through combining these primary representations, the neuron system is able to generate a large number of semantics particles in the higher representation layers, which exist on a large number of fiber bundle nodes in the neuron system. In addition, as the three primary colors in the color representation, we have found that through utilizing the three neuron groups that respectively have most sensitive responses to the directions 45o, 90o, and 135o, the vision neuron system is able to achieve the effective representation to line segment direction. In addition, based on our more understandings to the characteristics of the brain processing information, we have better explained the core principle of intelligence behavior. Just like the appearance of steam engine liberated man-power, and from now on, through further researches to the brain intelligence we expect to be able to liberate the computing-power involving in creating machine intelligence, and achieve more powerful intelligence.