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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More important emerging trends and 2024–2025 predictions

The following trends and predictions are derived from our comprehensive research and experience, as well as insights shared by leading industry experts:

LLMs optimized for structured data: LLMs excel in comprehending and generating natural language text, benefiting from extensive training on diverse textual sources, such as books and web pages. Yet, their proficiency in interpreting structured, tabular data remains less developed. Nevertheless, this domain is witnessing burgeoning research, with promising advancements anticipated in 2024 and beyond. A notable initiative in this trajectory is Table-GPT by Microsoft, which signifies a concerted effort to enhance LLMs’ capabilities in processing tabular data by specifically fine-tuning them on such datasets (https://arxiv.org/abs/2310.09263).
Maturity of LLMOps: In 2023, the focus was predominantly on developing and transitioning Proof of Concepts (PoCs...