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Unlocking the Secrets of Prompt Engineering

You're reading from   Unlocking the Secrets of Prompt Engineering Master the art of creative language generation to accelerate your journey from novice to pro

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835083833
Length 316 pages
Edition 1st Edition
Concepts
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Author (1):
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Gilbert Mizrahi Gilbert Mizrahi
Author Profile Icon Gilbert Mizrahi
Gilbert Mizrahi
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Introduction to Prompt Engineering FREE CHAPTER
2. Chapter 1: Understanding Prompting and Prompt Techniques 3. Chapter 2: Generating Text with AI for Content Creation 4. Part 2:Basic Prompt Engineering Techniques
5. Chapter 3: Creating and Promoting a Podcast Using ChatGPT and Other Practical Examples 6. Chapter 4: LLMs for Creative Writing 7. Chapter 5: Unlocking Insights from Unstructured Text – AI Techniques for Text Analysis 8. Part 3: Advanced Use Cases for Different Industries
9. Chapter 6: Applications of LLMs in Education and Law 10. Chapter 7: The Rise of AI Pair Programmers – Teaming Up with Intelligent Assistants for Better Code 11. Chapter 8: AI for Chatbots 12. Chapter 9: Building Smarter Systems – Advanced LLM Integrations 13. Part 4:Ethics, Limitations, and Future Developments
14. Chapter 10: Generative AI – Emerging Issues at the Intersection of Ethics and Innovation 15. Chapter 11: Conclusion 16. Index 17. Other Books You May Enjoy

How LLM prompts work

Large-scale LLMs are a form of AI that focuses on understanding and generating human language. They use sophisticated machine learning algorithms, primarily neural networks, to process and analyze a massive amount of textual data. The main objective of LLMs is to produce coherent, contextually relevant, and human-like responses to given input prompts. To comprehend how LLMs function, it’s crucial to discuss their underlying architecture and the training process. Using some analogies to explain these concepts will make them easier to understand.

Architecture

LLMs, such as OpenAI’s GPT-4, are made using a special type of neural network called the Transformer. Transformers have a special structure that helps them work well with text.

One important thing in Transformers is self-attention. This means that the model can focus on different parts of a sentence and decide which words are more important in a particular context. It’s like giving...

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