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

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.

Who is this book 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.

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

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Sandip Chakraborty Sep 27, 2024

I have purchased the paperback version , however I have not received the free PDF version of this book . Any Idea , how to get the free PDF version ?

Amazon Verified review

Subhasish Ghosh Aug 27, 2024

Just finished perusing "𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰 𝒇𝒐𝒓 𝑪𝒍𝒐𝒖𝒅 𝑺𝒐𝒍𝒖𝒕𝒊𝒐𝒏𝒔: 𝑨𝒓𝒄𝒉𝒊𝒕𝒆𝒄𝒕 𝒎𝒐𝒅𝒆𝒓𝒏 𝑨𝑰 𝑳𝑳𝑴𝒔 𝒊𝒏 𝒔𝒆𝒄𝒖𝒓𝒆, 𝒔𝒄𝒂𝒍𝒂𝒃𝒍𝒆, 𝒂𝒏𝒅 𝒆𝒕𝒉𝒊𝒄𝒂𝒍 𝒄𝒍𝒐𝒖𝒅 𝒆𝒏𝒗𝒊𝒓𝒐𝒏𝒎𝒆𝒏𝒕𝒔", authored by my Microsoft colleagues, Paul S. & Anurag Karuparti, Packt Publications. An excellent read, this is a nicely detailed book for those looking to start your journey into Generative AI.𝐓𝐚𝐫𝐠𝐞𝐭 𝐚𝐮𝐝𝐢𝐞𝐧𝐜𝐞: Aspiring Cloud Architects, Data Analysts, Cloud Dev, Data Scientists, AI Researchers, Tech Business Leaders, and Tech Evangelists.✅ What this book is: Broad high-level overview of GenAI❎ What this book is not: This is not a technical deep dive into Algorithms, Transformer Model variants or Code for LLMs/LMMs/SLMs etc.5 things that makes this book a good read:1️⃣ Get started with the essentials of generative AI, LLMs, and ChatGPT, and understand how they function together.2️⃣ Understand how we started applying NLP to concepts like transformers. Grasp the process of fine-tuning and developing apps based on RAG.3️⃣ 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.4️⃣ Discover how to scale and secure GenAI systems, while understanding the principles of responsible AI.5️⃣ Loved the chapters #4 & #5, which focuses on Retrieval-Augmented Generation (RAG), Vector DB essentials, role it plays in RAG, chunking strategies, KNNs versus ANNs, Azure Prompt Flow, Essential Prompt Engineering techniques and more. These 2 chapters are excellent for those looking to get a solid grasp on both the theoretical and conceptual aspects & practical aspects of RAG & Prompt Engineering.Overall, highly recommended book.

Farzad Sunavala Aug 05, 2024

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. This eBook 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!I look forward to a part 2. :)

Om S Jun 14, 2024

This book is a brilliant introduction to the integration of cloud computing with generative AI. The chapter 'Cloud Computing Meets Generative AI: Bridging Infinite Impossibilities' really expanded my understanding of the potential in combining these technologies. I found 'NLP Evolution and Transformers' very enlightening, particularly for its deep dive into how NLPs and LLMs are evolving. The 'Fine Tuning' chapter provided practical insights into tailoring AI applications to specific domains. 'RAGs to Riches' introduced an innovative approach to leveraging external data in AI models. The strategies shared in 'Effective Prompt Engineering Strategies' are essential for anyone looking to refine AI outputs. 'Developing and Operationalizing LLM-Based Cloud Applications' was a great guide on the lifecycle of AI apps. The security chapter addressed crucial considerations needed to protect AI systems. 'Responsible Development of AI Solutions' emphasized ethical practices which are vital in AI development. Lastly, 'Future of Generative AI' offered an exciting peek into what the next era of AI might hold.

homePC Jun 10, 2024

I did not set a high expectation when I started reading, but it was extremely good. I like the approach and the concise way of explaining complicated topics in an easy-to-understand way.

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

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