ChatGPT: Optimizing Text Generation Model for Knowledge Creation

0*, Vikas Somani**, Prashant Dahiwale***
* Department of Computer Science and Engineering, Sangam University, Bhilwara, Rajasthan, India.
** School of Engineering and Technology, Sangam University, Bhilwara, Rajasthan, India.
***Department of Computer Engineering, Government Polytechnic, Daman, India.
Periodicity:January - March'2023
DOI : https://doi.org/10.26634/jse.17.3.19469

Abstract

Chatbots are a famous answering and text generation tool which became more popular with its real time based answering mechanism; use of Artificial Intelligence (AI) made them widely acceptable. Older version of Open AI's ChatGPT has issues like limited memory, inconsistent responses, and limited domain knowledge compared to ChatGPT- 4. ChatGPT-4 is able to answer like human in real time; it can write essays, poems, generate stories too. At present ChatGPT from OpenAI seems to be leading the trend compared to Bard AI, Bing AI, ChatSonic, OpenAI playground, LaMDA, Socratic, etc. This paper gives a brief knowledge on how ChatGPT got trained, its internal working mechanism, guidelines for effective utilization of ChatGPT and future of such AI based text generation tools.

Keywords

Chatbot, ChatGPT, Emotional Intelligence, OpenAI.

How to Cite this Article?

Mate, S., Somani, V., and Dahiwale, P. (2023). ChatGPT: Optimizing Text Generation Model for Knowledge Creation. i-manager’s Journal on Software Engineering, 17(3), 21-26. https://doi.org/10.26634/jse.17.3.19469

References

[1]. Aljanabi, M., Ghazi, M., Ali, A. H., & Abed, S. A. (2023). ChatGpt: Open possibilities. Iraqi Journal for Computer Science and Mathematics, 4(1), 62-64.
[7]. Kalla, D., & Smith, N. (2023). Study and analysis of ChatGPT and its impact on different fields of study. International Journal of Innovative Science and Research Technology, 8(3). 1-7.
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