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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

NLP evolution and the rise of transformers

NLP, or natural language processing, is the field of artificial intelligence that gives computers the ability to understand and manipulate human language using common spoken (or otherwise) language instead of what was traditionally given as input to computers in the past: computer programming language. Over the past several decades, these computer programming languages became more “natural” with fluency:

Figure 2.2 – Brief timeline of NLP evolution

Figure 2.2 – Brief timeline of NLP evolution

Over time, there has been significant advancement in the field of NLP, with computers increasingly improving in their ability for text generation due to the emergence of neural networks. Text generation itself isn’t a novel idea, but earlier language models before 2017 predominantly utilized ML architectures known as recurrent neural networks (RNNs) and convolutional neural networks (CNNs).

RNNs are a type of neural network architecture...

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