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Key benefits

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

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Colour book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Building Data-Driven Applications with LlamaIndex

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Amazon verified reviews

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.

Amazon Verified review

Steven Fernandes May 07, 2024

An indispensable guide for anyone venturing into the world of generative AI and large language models (LLMs). This book offers a comprehensive exploration, from the basic concepts of natural language processing (NLP) and transformers to the nuanced details of fine-tuning and application development using retrieval-augmented generation (RAG). It includes in-depth discussions on prompt engineering, application frameworks, and the lifecycle of LLMs, along with crucial considerations in LLMOps, autonomous agents, and Assistants APIs. Additionally, the book provides practical advice on scaling and securing GenAI systems and emphasizes the principles of responsible AI. A thorough and enlightening read for both novices and experienced practitioners in the field.

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.

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.

Jose Arias May 16, 2024

This is a very good and clear book that has helped me understand the fundamentals of generative ai. I love how it starts from scratch and builds up going through all the components.

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

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