Streamlining Text Generation with AI Powered Prompt Simplification Strategies
Maddula Ratna Mohitha, Panduranga Vital Terlapu, B. Anusrilekha, R. Narendra, P. Uday Shekar, P.B.Krishna Chaitanya, T. Rohith Kumar · Advances in computer science research · 2024
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 AIgenerated content.