Название: Prompt Engineering Using ChatGPT: Crafting Effective Interactions and Building GPT AppsАвтор: Mehrzad Tabatabaian
Издательство: Mercury Learning and Information
Год: 2024
Страниц: 157
Язык: английский
Формат: epub (true)
Размер: 10.1 MB
This book is designed for mastering the art and science of prompt engineering in the realm of artificial intelligence. It provides a thorough exploration of the fundamental principles, practical techniques, and real-world applications of prompt engineering, with a special focus on ChatGPT and its advanced iterations, including GPT-4 and GPT plug-ins. You will learn the essential role of prompts in interacting with ChatGPT, understand the anatomy of a well-constructed prompt, and explore different prompt styles. The book also shows how to set constraints and guidelines to steer AI responses toward desired outcomes and ensure ethical and responsible interactions. Whether you're a novice of generative AI or seeking advanced insights, this book is your companion for mastering prompt engineering and building innovative GPT applications.
Our journey is for a diverse audience, encompassing everyone from AI novices to seasoned practitioners. The world of GPT-based models can be complex and intimidating, especially for those without a background in data or computer science. Our mission is to make this world accessible to all. Through a blend of clear, natural language and practical, real-world examples, we aim to demystify the nuances of prompt engineering, equipping you with the tools and confidence to communicate effectively with AI systems.
Although there are so many AI innovations, like Gemini, Bing Chat, Claude, and Llamas, our focus is on ChatGPT and its iterations. This choice was driven by our goal to introduce you to the foundational principles of prompt engineering and empower you to fully leverage the capabilities of ChatGPT and similar advanced models. We want you to understand all the possibilities within the field of AI, relevant to prompt engineering.
This book is not just a theoretical exploration; it is a practical guide. We directly apply the principles of prompt engineering using ChatGPT-3.5 and GPT-4. Through these applications, we demonstrate the creation of prompts that lead to clear, effective communication. The content generated using these models has been thoroughly reviewed and refined for clarity and effectiveness, throughout this book’s content. However, as AI technology evolves, so do its responses. The examples in this book serve as a snapshot of current capabilities, with the understanding that AI’s language and responses will continue to advance.
In November 2023, OpenAI introduced a new tool for building customized GPT models or GPTs (openai.com), a significant advancement in the field of artificial intelligence and natural language processing. In this chapter, we examine this ground-breaking development. This chapter is designed to guide both novice and experienced users through the versatile capabilities of the GPTS framework and the GPT Builder tool.
We shift our focus to the API-GPT Builder, an intuitive interface that empowers developers to create bespoke GPT models. This section goes through the step-by-step process of model creation, from defining parameters and training datasets to fine-tuning models for specific tasks or industry requirements. Practical examples and case studies are provided to illustrate how customized models can significantly enhance performance in tasks such as content generation, data analysis, and customer service automation.
Features:
Discusses the fundamental groundwork for understanding prompts, their role in guiding AI models, and their impact on the quality of generated responses
Provides real-world applications demonstrating how prompt engineering is applied across various domains, from customer support and education to business and technical fields
Includes a chapter on GPT-4 Plugins showing how to extend the capabilities of GPT-4 and create more versatile AI-powered applications
Describes techniques for formulating clear and direct questions to obtain precise answers from AI models
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