Streamlining Text Generation with AI Powered Prompt Simplification Strategies

DOI

10.2991/978-94-6463-471-6_16How to use a DOI?

Keywords

Artificial Intelligence; Prompt Engineering; Natural Language Processing; MERN Stack

Abstract

In recent times, generating understandable prompts for AI has been a significant problem, which in turn leads to inaccurate results. In essence, the problem is about finding ways to make AI understand and respond accurately to the prompts given to it, which is crucial for improving its overall performance and usefulness in various applications. This paper proposes a novel approach to enhance AI comprehension by generating tailored understanding prompts through prompt engineering techniques in Natural Language Processing, along with advanced Transformer-based deep learning models. Our project integrates these techniques to transform a base prompt into a set of diverse and comprehensive understanding prompts. To ensure data security, we have also implemented data encryption standard and Blowfish encryption algorithms to protect sensitive information during the transformation process. The resulting prompts will be used to train AI models, enabling them to grasp nuanced details and context when responding to user queries. The paper's significance lies in its potential to improve the quality of AI-generated responses across a range of applications, including natural language understanding, question answering, and content generation. Crucially, the developed web application, constructed using the MERN Stack, promises more reliable and insightful interactions with AI systems, effectively bridging the gap between human comprehension and AI-generated content.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Maddula Ratna Mohitha
AU  - Panduranga Vital Terlapu
AU  - B. Anusrilekha
AU  - R. Narendra
AU  - P. Uday Shekar
AU  - P. Krishna Chaitanya
AU  - T. Rohith Kumar
PY  - 2024
DA  - 2024/07/30
TI  - Streamlining Text Generation with AI Powered Prompt Simplification Strategies
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 160
EP  - 169
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_16
DO  - 10.2991/978-94-6463-471-6_16
ID  - Mohitha2024
ER  -