i-manager Publications

ChatGPT: Optimizing Text Generation Model for Knowledge Creation

Sanjay Mate*, 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

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	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25

ChatGPT: Optimizing Text Generation Model for Knowledge Creation

Abstract

Keywords

How to Cite this Article?

References

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