A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development
Abstract
ChatGPT, an artificial intelligence generated content (AIGC) model developed by OpenAI, has attracted world-wide attention for its capability of dealing with challenging language understanding and generation tasks in the form of conversations. This paper briefly provides an overview on the history, status quo and potential future development of ChatGPT, helping to provide an entry point to think about ChatGPT. Specifically, from the limited open-accessed resources, we conclude the core techniques of ChatGPT, mainly including large-scale language models, in-context learning, reinforcement learning from human feedback and the key technical steps for developing Chat-GPT. We further analyze the pros and cons of ChatGPT and we rethink the duality of ChatGPT in various fields. Although it has been widely acknowledged that ChatGPT brings plenty of opportunities for various fields, mankind should still treat and use ChatGPT properly to avoid the potential threat, e.g., academic integrity and safety challenge. Finally, we discuss several open problems as the potential development of ChatGPT.
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Chatbots are activated by a plain-language instruction, or prompt, provided by the user, and generate responses using statistical and probability-based language models.
“Chatbots are activated by a plain-language instruction, or “prompt,” provided by the user. They generate responses using statistical and probability-based language models 5 .”
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References 135 · Cited by 1,452
- Authors
- Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q.-L., & Tang, Y.
- Affiliations
- East China University of Science and Technology (CN)
- Chinese Academy of Sciences (CN)
- Fudan University (CN)
- Swinburne University of Technology (AU)
- Venue
- IEEE/CAA Journal of Automatica Sinica
- Published
- 2023-05
- Volume
- 10
- Issue
- 5
- Pages
- 1122-1136
- ISSN
- 2329-9266 (ISSN-L)
- 2329-9274
- OpenAlex
- W4367595583
- Cited by
- 1,452
- References
- 135
- Citations by year
- 2026: 219 · 2025: 577 · 2024: 579 · 2023: 76 · 2022: 1
- FWCI
- 136.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE/CAA Journal of Automatica Sinica (publishedVersion)
- Funders
- National Key Research and Development Program of China (2021YFB1714300)
- National Natural Science Foundation of China (62293502,61831022,61976211)
- Youth Innovation Promotion Association CAS
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- ChatGPT, large language models, in-context learning, reinforcement learning from human feedback, conversational AI, AI-generated content, academic integrity, AI safety
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