The Power of Prompt Engineering: Refining Human - AI Interaction with Large Language Models in The Field of Engineering
Abstract: This paper presents a pioneering exploration into prompt engineering, a critical aspect of interactions with Large Language Models (LLMs) in engineering contexts. We delve into the nuanced strategies and methodologies of prompt engineering, demonstrating its profound impact on the performance and reliability of LLMs like GPT - 4. We explored a range of techniques, from simple, clear instructions to more complex few - shot learning prompts and evaluated their effectiveness in various scenarios. The findings highlight the significant potential of prompt engineering in enhancing the precision, efficiency, and applicability of LLMs in engineering, setting a foundation for future advancements in human - AI collaboration.
Keywords: Large Language Model, Prompt Pattern, Prompt Engineering, Human - AI Interaction, Few - shot Learning, GPT - 4, Foundation Model
How to Cite?: Satish Kathiriya, Mahidhar Mullapudi, Abhishek Shende, "The Power of Prompt Engineering: Refining Human - AI Interaction with Large Language Models in The Field of Engineering", Volume 12 Issue 11, November 2023, International Journal of Science and Research (IJSR), Pages: 2134-2144, https://www.ijsr.net/getabstract.php?paperid=SR24304112157, DOI: https://dx.doi.org/10.21275/SR24304112157