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

Product type Paperback

Published in Apr 2024

Publisher Packt

ISBN-13 9781835084786

Length 300 pages

Edition 1st Edition

Languages

Python

Tools

ChatGPT

Concepts

GPT/LLMs

Authors (2):

Paul Singh

Anurag Karuparti

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Table of Contents (18) Chapters

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

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17. Other Books You May Enjoy

Part 3: Developing, Operationalizing, and Scaling Generative AI Applications

In this section, we will explore important concepts such as agents, copilots, and autonomous agents, alongside discussing prominent application development frameworks such as Semantic Kernel and LangChain, as well as the agent collaboration framework AutoGen, which are currently very popular. This discussion aims to guide you in creating strong autonomous generative AI applications. We will also concentrate on strategies for deploying these generative AI applications in a live production environment and scaling them efficiently for a large enterprise-wide scenario, considering the existing rate limits of Large Language Model (LLM) APIs.

This part contains the following chapters:

Chapter 6, Developing and Operationalizing LLM-Based Cloud Applications: Exploring Dev Frameworks and LLMOps
- Chapter 7, Deploying ChatGPT in the Cloud: Architecture Design and Scaling Strategies

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

Table of Contents (18) Chapters

Part 3: Developing, Operationalizing, and Scaling Generative AI Applications

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Authors (2)

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