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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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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1:Integrating Cloud Power with Language Breakthroughs
2. Chapter 1: Cloud Computing Meets Generative AI: Bridging Infinite Impossibilities FREE CHAPTER 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

Copilots and agents

Traditional chatbots have undergone significant evolution, transitioning into more sophisticated forms such as copilots, agents, and autonomous agents. In this section, we aim to compare and contrast these advanced chatbot types, exploring their roles and utilization in contemporary applications.

Figure 6.2 – Evolution from chatbots to autonomous agents

Figure 6.2 – Evolution from chatbots to autonomous agents

Agents are skilled assistants and, in the context described, are pieces of code equipped with AI capabilities. They are designed to complete tasks by interacting with users through applications or other interfaces. Initially, they gather information from users and subsequently utilize this data to execute actions, which may include feeding it into LLMs or a sequence of LLMs, among other possibilities.

For example, a data analyst agent can analyze your Excel sheets by asking for your raw Excel file and any other questions it may have; then, it will generate its own plan of action...

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