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- W4387191696 abstract "ChatGPT is a new artificial intelligence technology driven natural language processing tool launched by Open AI, an American artificial intelligence research laboratory. It uses Transformer neural network architecture. A model used by the system to process sequential data. It trains the model by linking large corpora containing real-world conversations that allow ChatGPT to interact in the context of the chat. This paper analyzes ChatGPT's Transformer neural network architecture. A new parameter saving residual module is proposed, and a simplified network architecture is designed. This structure design can effectively avoid the obvious reduction of parameters by over-fitting merging. Compared with existing deep learning methods, the proposed method has certain advantages in time efficiency and accuracy. The accuracy can be improved by more than 11%, and the average processing time of a single sample is less than 1 Ms." @default.
- W4387191696 created "2023-09-30" @default.
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- W4387191696 date "2023-08-18" @default.
- W4387191696 modified "2023-09-30" @default.
- W4387191696 title "Research on Information Intelligent Service Terminal Based on Big Data Intelligent ChatGPT Technology" @default.
- W4387191696 doi "https://doi.org/10.1109/icsece58870.2023.10263438" @default.
- W4387191696 hasPublicationYear "2023" @default.
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