Enhancing Prompt Engineering Application using Artificial Intelligence

Dhyankumar Patel, Sahil Kadbhane, Arya Chandorkar, Mohammed Sameed, Aniruddha S. Rumale


Abstract— The optimization of prompts stands as a fundamental element driving the comprehensive evolution of artificial intelligence (AI), particularly within the expansive domains of interactive AI and platform development. This abstract intricately probes the multifaceted interplay among chain prompting, AI functionality, and the artistry involved in prompt construction, accentuating their inherent and consequential interconnections. Meticulously designed prompts form the bedrock, fostering nuanced, contextually resonant, and captivating interactions, significantly manifest within conversational AI landscapes. The precise tailoring of prompts assumes a pivotal role in soliciting targeted responses from sophisticated AI models such as GPT-3, ensuring discourse imbued with elevated relevance and depth. Simultaneously, the strategic orchestration of chain processing intricately weaves a tapestry of seamless, natural dialogue, skillfully interlinking inquiries, and responses. The symbiotic fusion of prompt engineering and chain processing serves as the cornerstone for architecting impactful platform design, enriching, and refining user experiences across a myriad of diverse applications. This explorative discourse adeptly navigates the dynamic and evolving terrain innate to the realm of generative AI, spotlighting the paramount significance of prompt optimization in sculpting and enhancing the fabric of AI capabilities and interactions.


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