A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development
By Tianyu Wu, Shizhu He, Jingping Liu, Siqi Sun, Kang Liu, Qing‐Long Han, Yang Tang. IEEE/CAA Journal of Automatica Sinica, 2023
1,248 citations recorded by the source corpus.
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.
Subfields: Artificial Intelligence, Health Informatics
View Paper: https://www.semanticscholar.org/paper/8cf819f6ee33909484ece40d79944c9c37f01a89
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Citations in the corpus
- Cultural bias and cultural alignment of large language models (2023, methodology): “5-turbo incorporated Reinforcement Learning with Human Feedback (RLHF) [49].”
- Aligning Cyber Space With Physical World: A Comprehensive Survey on Embodied AI (2024, neutral): “Different from conversational agents like ChatGPT [4], embodied AI believes that the true AGI can be achieved by controlling physical embodiments and interacting with both simulated and physical environments [5], [6].”