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  • Book Overview & Buying Generative AI for Cloud Solutions
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Generative AI for Cloud Solutions

Generative AI for Cloud Solutions

By : Paul Singh, Anurag Karuparti
4.9 (9)
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Generative AI for Cloud Solutions

Generative AI for Cloud Solutions

4.9 (9)
By: Paul Singh, Anurag Karuparti

Overview of this book

Generative artificial intelligence technologies and services, including ChatGPT, are transforming our work, life, and communication landscapes. To thrive in this new era, harnessing the full potential of these technologies is crucial. Generative AI for Cloud Solutions is a comprehensive guide to understanding and using Generative AI within cloud platforms. This book covers the basics of cloud computing and Generative AI/ChatGPT, addressing scaling strategies and security concerns. With its help, you’ll be able to apply responsible AI practices and other methods such as fine-tuning, RAG, autonomous agents, LLMOps, and Assistants APIs. As you progress, you’ll learn how to design and implement secure and scalable ChatGPT solutions on the cloud, while also gaining insights into the foundations of building conversational AI, such as chatbots. This process will help you customize your AI applications to suit your specific requirements. By the end of this book, you’ll have gained a solid understanding of the capabilities of Generative AI and cloud computing, empowering you to develop efficient and ethical AI solutions for a variety of applications and services.
Table of Contents (18 chapters)
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1
Part 1:Integrating Cloud Power with Language Breakthroughs
4
Part 2: Techniques for Tailoring LLMs
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8
Part 3: Developing, Operationalizing, and Scaling Generative AI Applications
11
Part 4: Building Safe and Secure AI – Security and Ethical Considerations
14
Part 5: Generative AI – What’s Next?

Part 2: Techniques for Tailoring LLMs

This section highlights key techniques that have emerged in recent years to customize Large Language Models (LLMs) for specific business needs, such as fine-tuning. It also addresses current challenges, including mitigating hallucinations and extending training cut-off dates, to incorporate up-to-date information through methods such as Retrieval Augmented Generation (RAG). Additionally, we will explore prompt engineering techniques to enhance effective communication with AI.

This part contains the following chapters:

  • Chapter 3, Fine Tuning: Building Domain-Specific LLM Applications
  • Chapter 4, RAGs to Riches: Elevating AI with External Data
  • Chapter 5, Effective Prompt Engineering Strategies: Unlocking Wisdom Through AI
CONTINUE READING
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Tech Concepts
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Programming languages
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Generative AI for Cloud Solutions
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