NLP and Prompt Engineering for AI Chatbots

Abstract

Natural language processing (NLP) is a rapidly evolving field, and artificial intelligence (AI chatbots have become a potent tool for a range of sectors and applications. As one of its advanced models, large language models (LLMs) have created new ethical conundrums in addition to previously unheard-of possibilities. Large-scale production of coherent, well-structured written content is possible with these models, which may help users with their tasks. Understanding and mastering the technique of prompt engineering—the act of creating and optimizing input prompts to elicit desired responses from an AI NLP model—is essential to maximizing the potential of chatbots. Prompt engineering may be used to automate processes and enforce regulations to guarantee high-quality and consistent output from LLMs. This chapter offers a comprehensive guide on how to become proficient in prompt engineering methods, suggestions, and best practices to get the most out of AI chatbots and LLMs. An introduction to NLP and AI chatbots is covered first, followed by the basics of prompt engineering. In addition, the chapter discusses best practices for prompt engineering and looks at methods for constructing prompts effectively. This chapter will also cover advanced techniques such as managing ambiguous inputs, prompt chaining, and domain-specific modifications. Current research in prompt engineering, such as the emergence of autonomous prompt generation and selection techniques, will be covered as well.

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