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Demos of Passing Turing Test Successfully

  • Conference paper
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Data Science (ICPCSEE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1452))

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Abstract

Recently, a new kind of machine intelligence was born, called as UI (Ubit intelligence). The basic difference between UI and AI is encoding; UI is based on word encoding; but AI is based on character encoding. UI machine can learn from human, remember the characters, pronunciation, and meaning of a word like human. UI machine can think among the character, pronunciation, and meaning of words like human. Turing Test is similar to a teacher testing a student; Before Test, tester must teach the content of the test questions to UI machine first; after UI machine learning, tester asks testee questions; to check testee has remembered what he taught; to check testee can think among character, pronunciation, and meaning of words. This paper demonstrates that testee can remember what testee taught; and answer all 6 questions correctly by thinking. UI machine passes Turing Test easily and successfully with score 100. Following on, the works related to this study is briefly introduced. At last, this paper concludes that UI machine is based on word encoding, can form word, form concept, can possess brain like intelligence, also can possess human like Intelligence; therefore UI machine passes Turing Test easily and successfully. On the contrary, AI machine is based on character encoding; can’t form word; can’t form concept, AI machine can’t possess brain like intelligence, nor possess human like Intelligence. Therefore, AI machine can’t pass Turing Test.

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Acknowledgment

Thank Bin Wu, my wife, for her great contributions and fully supporting. During the three decades, she helps me to do everything about thinking machine; such as experiment, prepare material, discuss problems with me; as difficulties met, she gives me confidence.

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Authors and Affiliations

  1. Shandong University, Jinan, China

    Shengyuan Wu

Authors
  1. Shengyuan Wu
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Correspondence to Shengyuan Wu .

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Editors and Affiliations

  1. North University of China, Taiyuan, China

    Jianchao Zeng

  2. North University of China, Taiyuan, China

    Pinle Qin

  3. Northeast Forestry University, Harbin, China

    Weipeng Jing

  4. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

  5. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

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Wu, S. (2021). Demos of Passing Turing Test Successfully. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2021. Communications in Computer and Information Science, vol 1452. Springer, Singapore. https://doi.org/10.1007/978-981-16-5943-0_41

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  • DOI: https://doi.org/10.1007/978-981-16-5943-0_41

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5942-3

  • Online ISBN: 978-981-16-5943-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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