
Based on natural language processing, human-computer dialogue, image recognition, and machine learning analysis whether artificial intelligence will surpass the human brain
- 1 School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
* Author to whom correspondence should be addressed.
Abstract
With the popularization and development of the concept of artificial intelligence, the application of artificial intelligence has also begun to deepen into people's lives. While bringing convenience to people, it has also made some people worry about whether artificial intelligence will replace humans. Therefore, In order to make people understand the current development status and bottlenecks of artificial intelligence more intuitively, as well as the difference between artificial intelligence and human brain, this article will turn from speech recognition and natural language processing, human-computer dialogue, image recognition, and machine learning ability, that is, machine listening, reading, and thinking four aspects of research and discussion, and finally summarize why artificial intelligence cannot completely surpass humans.
Keywords
artificial intelligence, speech recognition, natural language processing, human-computer dialogue, machine learning.
[1]. Maruyama, Y. Quantum (2017) Pancomputationalism and Statistical Data Science: From Symbolic to Statistical AI, and to Quantum AI. Studies in Applied Philosophy Epistemology and Rational Ethics. 207-211.
[2]. Rahhal Errattahi, Asmaa El Hannani, Hassan Ouahmane(2018), Automatic Speech Recognition Errors Detection and Correction: A Review. Procedia Computer Science 128.32-37.
[3]. Swietojanski, P., Ghoshal, A., Renals, S (2014). Convolutional neural networks for distant speech recognition. IEEE Signal Processing Letters 21, 1120–1124.
[4]. Bassil, Y., Semaan, P., (2012). Asr context-sensitive error correction based on microsoft n-gram dataset. arXiv preprint arXiv:1203.5262.
[5]. Lindell Bromham, Russell Dinnage, Hedvig Skirgård, Andrew Ritchie, Marcel Cardillo, Felicity Meakins, Simon Greenhill and Xia Hua (2022). Global predictors of language endangerment and the future of linguistic diversity. Nature Ecology & Evolution volume 6, pages 163–173.
[6]. Hu Quanyi, Yang Jie, Qin Peng and Fong Simon(2020) Towards a context-free machine universal grammar (CF-MUG) in natural language processing, IEEE Access, Volume 8, Pages 165111-165129.
[7]. D. Jurafsky, J.H. Martin(2021).Chatbots & dialogue systems. Speech and Language Processing. Draft of December 29, 2021
[8]. Kapociute-Dzikiene, Jurgita(2020).A Domain-Specific Generative Chatbot Trained from Little Data. APPLIED SCIENCES-BASEL.2221,10.7.
[9]. Isabel Kathleen Fornell Haugeland, Asbjørn Følstad, Cameron Taylor, Cato Alexander Bjørklia(2022) International Journal of Human-Computer Studies, Volume 161.
[10]. Ivo Benke, Ulrich Gnewuch, Alexander Maedche(2022). Understanding the impact of control levels over emotion-aware chatbots. Computers in Human Behavior, Volume 129.
[11]. David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche(2017), Thore Graepel & Demis Hassabis. Mastering the game of Go without human knowledge. Nature volume 550, pages354–359
[12]. D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, Y. Chen, T. Lillicrap, F. Hui, L. Sifre, G. van den Driessche, T. Graepel, D. Hassabis (2017), Mastering the game of Go without human knowledge. Nature 550, 354–359.
[13]. David Silver, Thomas Hubert, et al (2018). A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. SCIENCE, VOL. 362, NO. 6419 pp.
[14]. Sana Khanam, Safdar Tanweer, and Syed Khalid (2020). Artificial Intelligence Surpassing Human Intelligence: Factual or Hoax. The Computer Journal.
Cite this article
MU,C. (2023). Based on natural language processing, human-computer dialogue, image recognition, and machine learning analysis whether artificial intelligence will surpass the human brain. Applied and Computational Engineering,5,40-47.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
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