Generative AI for Cloud Solutions: Architect modern AI LLMs in secure, scalable, and ethical cloud environments

Generative AI for Cloud Solutions: Architect modern AI LLMs in secure, scalable, and ethical cloud environments book cover

Generative AI for Cloud Solutions: Architect modern AI LLMs in secure, scalable, and ethical cloud environments

Author(s): Paul Singh (Author), Anurag Karuparti (Author)

  • Publisher: Packt Publishing
  • Publication Date: 22 April 2024
  • Language: English
  • Print length: 300 pages
  • ISBN-10: 1835084788
  • ISBN-13: 9781835084786

Book Description

Explore Generative AI, the engine behind ChatGPT, and delve into topics like LLM-infused frameworks, autonomous agents, and responsible innovation, to gain valuable insights into the future of AI

Key Features

  • Gain foundational GenAI knowledge and understand how to scale GenAI/ChatGPT in the cloud
  • Understand advanced techniques for customizing LLMs for organizations via fine-tuning, prompt engineering, and responsible AI
  • Peek into the future to explore emerging trends like multimodal AI and autonomous agents
  • Purchase of the print or Kindle book includes a free PDF eBook

Book Description

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.

What you will learn

  • Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together
  • Understand how we started applying NLP to concepts like transformers
  • Grasp the process of fine-tuning and developing apps based on RAG
  • Explore effective prompt engineering strategies
  • Acquire insights into the app development frameworks and lifecycles of LLMs, including important aspects of LLMOps, autonomous agents, and Assistants APIs
  • Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI

Who this book is for

This artificial intelligence book is for aspiring cloud architects, data analysts, cloud developers, data scientists, AI researchers, technical business leaders, and technology evangelists looking to understanding the interplay between GenAI and cloud computing. Some chapters provide a broad overview of GenAI, which are suitable for readers with basic to no prior AI experience, aspiring to harness AI’s potential. Other chapters delve into technical concepts that require intermediate data and AI skills. A basic understanding of a cloud ecosystem is required to get the most out of this book.

Table of Contents

  1. Cloud Computing Meets Generative AI: Bridging Infinite Impossibilities
  2. NLP Evolution and Transformers: Exploring NLPs and LLMs
  3. Fine Tuning: Building Domain Specific LLM Applications
  4. RAGs to Riches: Elevating AI with External Data
  5. Effective Prompt Engineering Strategies: Unlocking Wisdom Through AI
  6. Developing and Operationalizing LLM-Based Cloud Applications: Exploring Dev Frameworks and LLMOps
  7. Deploying ChatGPT in the Cloud: Architecture Design and Scaling Strategies
  8. Security and Privacy Considerations for Gen AI: Building Safe and Secure LLMs

(N.B. Please use the Read Sample option to see further chapters)

Editorial Reviews

Review

“[…] I feel that we’re all better equipped to navigate the AI and cloud computing revolution with Paul and Anurag’s 10,000 hours of practice as our convenient guide. Their book promises not just a deep dive into technical mastery but also an inspiring journey toward embracing change, reminiscent of Eric Shinseki’s words: ‘If you don’t like change, you’re going to like irrelevance even less.

As you venture through the many fun-filled chapters of this book, try to embrace the challenges and opportunities with the same open-hearted adaptability my mother showed toward autocorrect. This isn’t just about keeping pace with technology—it’s about thriving in a future where our human creativity and AI’s capabilities are inextricably linked. There’s an entire emergent chain of tooling and processes that are wonderfully demystified within this book, and I, for one, feel better prepared for what comes next. I wish this feeling of confidence for you, as a fellow practitioner on the path to becoming an AI engineer.”

John Maeda, Vice President, Design and AI, Microsoft

“An exceptionally well-crafted resource that dives deep into the complexities of generative AI and its integration with cloud solutions. Key takeaways include an in-depth understanding of Retrieval Augmented Generation (RAG) and its role in enhancing AI reliability, the pivotal role of vector databases in optimizing AI search performance, effective chunking strategies for handling diverse data types, and the importance of evaluation metrics for ensuring model accuracy. The book also showcases real-world applications and case studies across various industries, illustrating the tangible benefits and scalability of RAG-based solutions. It is a valuable asset for AI professionals and cloud solution architects looking to leverage generative AI technologies effectively. As a product manager for Azure AI Search, I can attest that the authors have expert-level knowledge in these technologies!”

Farzad Sunavala, Senior Product Manager at Microsoft

About the Author

Paul Singh is currently a Principal Cloud Solution Architect (CSA), working at Microsoft for over 10 years. Having been selected as the very first ten CSA’s the role was first created, Paul helped shape the role ever since, including being on the national hiring committee(s) as well as helping create the very first Azure Architecture Exam. Paul has earned many honors and awards along the way, while also gaining over 30 different technical certifications, and helping some of the largest Cloud customers with complex scenarios and solutions.

Anurag Karuparti is a seasoned Senior Cloud Solution Architect specializing in AI at Microsoft’s Azure practice. Anurag holds a Master’s degree in Information Management(Data Science) from Syracuse University, and has a background in Computer Engineering. With over 10 years of experience in the industry, Anurag has become a trusted expert in the fields of Cloud, data, and advanced analytics. Anurag holds multiple Azure Certifications and is certified across major cloud platforms. Throughout his career, he has successfully designed and implemented cutting-edge solutions, leveraging the power of artificial intelligence to drive innovation and transform businesses. Prior to joining Microsoft, Anurag gained valuable experience working as a manager in the Emerging Technologies practices of renowned consulting firms such as EY and PwC.

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