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Generative AI for Cloud Solutions

You're reading from   Generative AI for Cloud Solutions Architect modern AI LLMs in secure, scalable, and ethical cloud environments

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Product type Paperback
Published in Apr 2024
Publisher Packt
ISBN-13 9781835084786
Length 300 pages
Edition 1st Edition
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Authors (2):
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Paul Singh Paul Singh
Author Profile Icon Paul Singh
Paul Singh
Anurag Karuparti Anurag Karuparti
Author Profile Icon Anurag Karuparti
Anurag Karuparti
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Integrating Cloud Power with Language Breakthroughs FREE CHAPTER
2. Chapter 1: Cloud Computing Meets Generative AI: Bridging Infinite Impossibilities 3. Chapter 2: NLP Evolution and Transformers: Exploring NLPs and LLMs 4. Part 2: Techniques for Tailoring LLMs
5. Chapter 3: Fine-Tuning – Building Domain-Specific LLM Applications 6. Chapter 4: RAGs to Riches: Elevating AI with External Data 7. Chapter 5: Effective Prompt Engineering Techniques: Unlocking Wisdom Through AI 8. Part 3: Developing, Operationalizing, and Scaling Generative AI Applications
9. Chapter 6: Developing and Operationalizing LLM-based Apps: Exploring Dev Frameworks and LLMOps 10. Chapter 7: Deploying ChatGPT in the Cloud: Architecture Design and Scaling Strategies 11. Part 4: Building Safe and Secure AI – Security and Ethical Considerations
12. Chapter 8: Security and Privacy Considerations for Gen AI – Building Safe and Secure LLMs 13. Chapter 9: Responsible Development of AI Solutions: Building with Integrity and Care 14. Part 5: Generative AI – What’s Next?
15. Chapter 10: The Future of Generative AI – Trends and Emerging Use Cases 16. Index 17. Other Books You May Enjoy

Effective Prompt Engineering Techniques: Unlocking Wisdom Through AI

Prompt engineering emerged as a standout profession in 2023, captivating the tech industry with its profound impact on AI interactions and applications. But what sparked this surge in popularity? The answer lies in the nuanced and intricate nature of the discipline. Understanding the essentials of prompt engineering is crucial; it’s not just about communicating with the model; it’s about crafting prompts that guide the AI to understand the context and nuances of the task at hand. In the previous chapter, we learned about how we can add relevant context through RAG by searching through vector DB. Finally, a prompt needs to be crafted and sent to the LLMs. This leads to more accurate and relevant responses, turning a simple interaction into a robust tool for a variety of cloud-based applications. Whether it’s automating customer support, generating content, or analyzing data, the ability to fine...

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