Mastering Prompt Engineering: Optimizing Interaction with Generative AI Agents

Authors

  • Vijay Kartik Sikha USA Author
  • Dayakar Siramgari USA Author
  • Laxminarayana Korada USA Author

DOI:

https://doi.org/10.47363/JEAST/2023(5)E117

Keywords:

Prompt Engineering, Generative AI, Transformer Architecture, Bias Mitigation, Contextual Relevance

Abstract

Generative AI technologies are reshaping multiple sectors by enhancing how tasks are executed, and information is processed. With advancements from companies like OpenAI, Microsoft, and Google, these AI agents have become pivotal in automating workflows, generating text that resembles human writing, and offering actionable insights. Central to harnessing their potential is mastering prompt engineering-the art of designing effective queries to optimize AI responses. This article delves into the burgeoning field of generative AI, emphasizing the significance of prompt engineering in enhancing the interaction with these sophisticated tools. It provides an overview of leading AI tools like ChatGPT, Microsoft Copilot, and Google Bard, explores the technical underpinnings of these models, and addresses key aspects of prompt engineering including linguistic nuances, iterative refinement, and bias mitigation. The article also examines practical strategies for mastering prompt engineering, discusses security concerns such as prompt injection attacks and data privacy, and highlights future trends in AI technology. Through case studies and expert insights, the article underscores the critical role of prompt engineering in maximizing the effectiveness and ethical use of generative AI systems.

Author Biographies

  • Vijay Kartik Sikha, USA

    Vijay Kartik Sikha, USA

  • Dayakar Siramgari, USA

    Dayakar Siramgari, USA

  • Laxminarayana Korada, USA

    Laxminarayana Korada, USA

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Published

2023-12-19