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Sang Jitao, Yu Jian. ChatGPT: A Glimpse into AI’s Future[J]. Journal of Computer Research and Development, 2023, 60(6): 1191-1201. DOI: 10.7544/issn1000-1239.202330304
Citation: Sang Jitao, Yu Jian. ChatGPT: A Glimpse into AI’s Future[J]. Journal of Computer Research and Development, 2023, 60(6): 1191-1201. DOI: 10.7544/issn1000-1239.202330304

ChatGPT: A Glimpse into AI’s Future

Funds: This work was supported by the Beijing Natural Science Foundation for Distinguished Young Scholars (JQ20023), and the National Natural Science Foundation of China (61832002).
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  • Author Bio:

    Sang Jitao: born in 1985. PhD, Professor. His main research interests include multimedia analysis, Web mining, and trustworthy machine learning

    Yu Jian: born in 1969. PhD, Professor. CCF Fellow and CAAI Fellow.His main research interests include machine learning and artificial intelligence

  • Received Date: April 09, 2023
  • Revised Date: April 11, 2023
  • Available Online: April 17, 2023
  • ChatGPT has been a significant breakthrough and drawn widespread attention. ChatGPT’s role in AI development and its future impact is examined in this paper. We first introduce ChatGPT’s exceptional dialogue generation capabilities, enabling it to handle nearly all natural language processing tasks and be applied as a data generator, knowledge mining tool, model dispatcher, and natural interaction interface. We then analyze ChatGPT’s limitations in factual errors, toxic content generation, safety, fairness, interpretability, and data privacy, and discuss the importance of clarifying its capability boundaries. After that, we analyze the concept of truth and explain why ChatGPT cannot distinguish truth from falsehood from the non-equivalence of three references. In discussing AI's future, we analyze mid-to-short term technological trends and the long-term development path from the relationship between perception, cognition, emotion, and behavioral intelligence. Lastly, we explore ChatGPT’s potential impact on cognitive cost, education, Turing Test understanding, academia’s opportunities and challenges, information cocoons, energy and environmental issues, and productivity enhancement.

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