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

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

Startup ecosystem in RAI

In this section, we will discuss a few notable startups emerging in the responsible AI space and building products that keep RAI at their core.

Parity AI: Founded by Rumman Chowdhury, Parity AI focuses on AI risk management and offers tools for auditing AI models for bias or legal compliance and provides recommendations for addressing these issues (https://www.get-parity.com/).
Fiddler: Founded by Krishna Gade, Fiddler focuses on explainability in AI, helping to make AI model decisions more transparent. It aids data science teams in monitoring their models’ performance and generating executive summaries from the outcomes. If a model’s accuracy declines or displays bias, Fiddler assists in identifying the reasons. Gade views model monitoring and enhancing clarity as key initial steps for more deliberate AI development and deployment (https://www.fiddler.ai/ai-observability).
Arthur: Founded in 2019, Arthur is a company specializing...

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