The Generative AI Practitioner’s Guide


Book Description

Generative AI is revolutionizing the way organizations leverage technology to gain a competitive edge. However, as more companies experiment with and adopt AI systems, it becomes challenging for data and analytics professionals, AI practitioners, executives, technologists, and business leaders to look beyond the buzz and focus on the essential questions: Where should we begin? How do we initiate the process? What potential pitfalls should we be aware of? This TinyTechGuide offers valuable insights and practical recommendations on constructing a business case, calculating ROI, exploring real-life applications, and considering ethical implications. Crucially, it introduces five LLM patterns—author, retriever, extractor, agent, and experimental—to effectively implement GenAI systems within an organization. The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications bridges critical knowledge gaps for business leaders and practitioners, equipping them with a comprehensive toolkit to define a business case and successfully deploy GenAI. In today’s rapidly evolving world, staying ahead of the competition requires a deep understanding of these five implementation patterns and the potential benefits and risks associated with GenAI. Designed for business leaders, tech experts, and IT teams, this book provides real-life examples and actionable insights into GenAI’s transformative impact on various industries. Empower your organization with a competitive edge in today’s marketplace using The Generative AI Practitioner’s Guide: How to Apply LLM Patterns for Enterprise Applications. Remember, it’s not the tech that’s tiny, just the book!™




Generative AI Business Applications


Book Description

Within the past year, generative AI has broken barriers and transformed how we think about what computers are truly capable of. But, with the marketing hype and generative AI washing of content, it’s increasingly difficult for business leaders and practitioners to go beyond the art of the possible and answer that critical question–how is generative AI actually being used in organizations? With over 70 real-world case studies and applications across 12 different industries and 11 departments, Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies fills a critical knowledge gap for business leaders and practitioners by providing examples of generative AI in action. Diving into the case studies, this TinyTechGuide discusses AI risks, implementation considerations, generative AI operations, AI ethics, and trustworthy AI. The world is transforming before our very eyes. Don’t get left behind—while understanding the powers and perils of generative AI. Full of use cases and real-world applications, this book is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI's transformative power. Gain a competitive edge in today's marketplace with Generative AI Business Applications: An Executive Guide with Real-Life Examples and Case Studies. Remember, it's not the tech that's tiny, just the book!™




Applied Generative AI for Beginners


Book Description

This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard. It serves as a one-stop resource for anyone interested in understanding and applying this transformative technology and is particularly aimed at those just getting started with generative AI. Applied Generative AI for Beginners is structured around detailed chapters that will guide you from foundational knowledge to practical implementation. It starts with an introduction to generative AI and its current landscape, followed by an exploration of how the evolution of neural networks led to the development of large language models. The book then delves into specific architectures like ChatGPT and Google Bard, offering hands-on demonstrations for implementation using tools like Sklearn. You’ll also gain insight into the strategic aspects of implementing generative AI in an enterprise setting, with the authors covering crucial topics such as LLMOps, technology stack selection, and in-context learning. The latter part of the book explores generative AI for images and provides industry-specific use cases, making it a comprehensive guide for practical application in various domains. Whether you're a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights. What You Will Learn Gain a solid understanding of generative AI, starting from the basics of neural networks and progressing to complex architectures like ChatGPT and Google Bard Implement large language models using Sklearn, complete with code examples and best practices for real-world application Learn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selection Understand how generative AI can be applied across various industries, from healthcare and marketing to legal compliance through detailed use cases and actionable insights Who This Book Is For Data scientists, AI practitioners, Researchers and software engineers interested in generative AI and LLMs.




The CIO’s Guide to Adopting Generative AI: Five Keys to Success


Book Description

In a world full of generative AI hoopla, it's easy to get lost in the maze of options and marketing hype. Don't get distracted by the vendor hype; instead, focus on building resilient, high-value platforms that will set you apart from the competition. The CIO’s Guide to Adopting Generative AI: Five Keys to Success fills a critical knowledge gap for CIOs and business leaders by succinctly offering five success factors that need to be met before an organization can successfully incorporate generative AI. To unlock the transformative business value of generative AI, business leaders must: 1) identify enterprise use cases, 2) apply context to large language models (LLMs) using their organization's data, 3) take special precautions to ensure data security and privacy, 4) implement an artificial intelligence (AI) governance framework, and 5) build manageable AI applications for business users. This report provides the keys to unlocking the true potential of generative AI. Full of use cases and real-world applications, this report is designed for business leaders, tech professionals, and IT teams. We provide practical, jargon-free explanations of generative AI's transformative power. Gain a competitive edge in today's marketplace with The CIO’s Guide to Adopting Generative AI: Five Keys to Success. Remember, it's not the tech that's tiny, it's the book!™




Comprehensive Guide to Generative AI with Keras


Book Description

Comprehensive Guide to Generative AI with Keras: Concepts, Implementations, and Applications" provides an in-depth exploration of generative artificial intelligence (AI) using the Keras framework. Authored as a comprehensive resource, this book is tailored for both beginners and experienced practitioners seeking to delve into the exciting field of generative AI. The book begins with an introduction to generative AI, elucidating its fundamental principles and distinguishing it from discriminative models. It then offers an overview of Keras, a user-friendly deep learning library widely favored for its intuitive design and powerful capabilities. Practicality is central to this guide, as each chapter unfolds with hands-on examples, case studies, and complete coding tutorials. Starting with the basics of generative models like autoencoders and GANs, readers are equipped with the skills to build and deploy these models using Keras. Applications ranging from image denoising to text generation illustrate the versatility and real-world impact of generative AI. Special emphasis is placed on advanced techniques such as transformer-based models, pivotal for natural language processing tasks like text generation and translation. Readers learn to construct and fine-tune transformer architectures using Keras, facilitating the creation of sophisticated language models. Evaluation and metrics receive comprehensive coverage, offering insights into assessing model performance across diverse generative tasks. The book also addresses ethical considerations inherent in AI development, ensuring readers grasp the implications and responsibilities associated with generative technologies. Projects featured in the latter chapters provide practical avenues for applying generative AI in creative domains such as art, music, and interactive installations. These projects not only reinforce theoretical knowledge but also encourage experimentation and innovation. In conclusion, "Comprehensive Guide to Generative AI with Keras" serves as an indispensable resource for aspiring AI practitioners and researchers. Its blend of theoretical foundations, practical implementation, and ethical awareness equips readers with the tools and insights needed to navigate and contribute to the evolving landscape of generative AI.




Generative AI Explained: Your Essential Guide


Book Description

"Generative AI Explained: Your Essential Guide" offers a clear and concise introduction to the world of generative artificial intelligence (AI). Authored by experts in the field, this handbook provides readers with a comprehensive understanding of the principles, applications, and implications of generative AI technology. The book begins by demystifying the concept of generative AI, explaining how it differs from other forms of AI and detailing its underlying mechanisms. Readers are guided through key concepts such as neural networks, machine learning, and deep learning, gaining insights into how these technologies enable machines to generate new content autonomously. From there, the handbook delves into practical applications of generative AI across various industries. Through real-world examples and case studies, readers discover how generative AI is being used to create art, music, literature, and even video games. Additionally, the book explores its applications in fields like healthcare, finance, and marketing, highlighting the transformative impact it is having on society. Furthermore, the handbook addresses important ethical and societal considerations surrounding generative AI. Readers are encouraged to critically examine issues such as bias, privacy, and the implications of AI-generated content on human creativity and employment. Throughout the book, complex technical concepts are explained in a clear and accessible manner, making it suitable for readers with varying levels of technical expertise. Whether you're a student, researcher, developer, or simply curious about the future of AI, "Generative AI Explained" serves as an invaluable resource for understanding the fundamentals of this rapidly evolving field. In summary, "Generative AI Explained: Your Essential Guide" offers a comprehensive yet approachable exploration of generative artificial intelligence, equipping readers with the knowledge and insights needed to navigate the increasingly AI-driven world.




Mastering Generative AI with PyTorch


Book Description

**Mastering Generative AI with PyTorch: From Fundamentals to Advanced Models** Unlock the potential of generative artificial intelligence with "Mastering Generative AI with PyTorch." This comprehensive guide takes you on a journey from the foundational concepts of generative AI to the implementation of advanced models, providing a clear and practical roadmap for mastering this cutting-edge technology. The book begins with an introduction to the core principles of generative AI, explaining its significance and applications in various fields such as art, entertainment, and scientific research. You will explore different types of generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Autoregressive Models, gaining a deep understanding of their architectures and mechanisms. With a focus on hands-on learning, the book introduces you to PyTorch, one of the most popular and powerful deep learning frameworks. Step-by-step instructions guide you through the installation of PyTorch and fundamental operations, setting a strong foundation for building complex models. Each chapter is designed to build on the previous one, gradually increasing in complexity and depth. In the GANs section, you will learn about their architecture, training process, and advanced variations like Conditional GANs and CycleGANs. The book provides detailed code examples and explanations, enabling you to implement and train your own GANs for diverse applications. The VAE section delves into the mathematical foundations and training techniques of VAEs, including practical examples of implementing both standard and conditional VAEs with PyTorch. You'll gain insights into how VAEs can generate high-quality, realistic data and their use in creative and scientific tasks. Autoregressive models, including PixelCNN and PixelRNN, are thoroughly covered, with explanations of their applications in sequential data generation. The book also explores the integration of attention mechanisms and transformers to enhance model performance. By the end of this book, you will have a solid understanding of generative AI and be equipped with the skills to implement and experiment with various generative models using PyTorch. Whether you are a beginner or an experienced practitioner, "Mastering Generative AI with PyTorch" provides the knowledge and tools needed to excel in the exciting field of generative AI.




Generative AI Automation: A Comprehensive Guide -: Notion, Voiceflow, Zapier, Make, Airtable, HighLevel, Apify, Synthflow, Chat GPT, Claude, Gemini Pro, Google Workspace


Book Description

"Generative AI Automation: A Comprehensive Guide" offers a thorough exploration of the burgeoning field of generative artificial intelligence (AI), providing readers with a comprehensive understanding of its principles, applications, and potential impact. This book serves as a roadmap for both beginners and seasoned professionals, breaking down complex concepts into digestible chunks while offering practical insights for implementation. Beginning with an introduction to the fundamentals of AI and machine learning, the book gradually delves into the intricacies of generative models, explaining how they enable machines to create new content, such as images, music, text, and more, autonomously. Readers are guided through various generative AI techniques, including popular models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models, with clear explanations and real-world examples illustrating their capabilities. The book doesn't just stop at theory; it provides hands-on guidance for readers to start experimenting with generative AI themselves. Step-by-step tutorials and coding examples using popular frameworks like TensorFlow and PyTorch empower readers to build their own generative models and understand the practical considerations involved in training and deploying them. Moreover, the book explores the ethical implications and societal impacts of generative AI, addressing concerns such as bias, privacy, and the future of work in an AI-driven world. With its accessible language, practical approach, and comprehensive coverage, "Generative AI Automation: A Comprehensive Guide" equips readers with the knowledge and skills they need to harness the transformative potential of generative AI in their own projects and endeavors. Whether you're a curious novice or an experienced practitioner, this book is your definitive resource for navigating the exciting landscape of generative AI automation.




The Quick Guide to Prompt Engineering


Book Description

Design and use generative AI prompts that get helpful and practical results In The Quick Guide to Prompt Engineering, renowned technology futurist, management consultant, and AI thought leader Ian Khan delivers a practical and insightful discussion on taking the first steps in understanding and learning how to use generative AI. In this concise and quick start guide, you will learn how to design and use prompts to get the most out of Large Language Model generative AI applications like ChatGPT, DALL-E, Google’s Bard, and more. In the book, you’ll explore how to understand generative artificial intelligence and how to engineer prompts in a wide variety of industry use cases. You’ll also find thoughtful and illuminating case studies and hands-on exercises, as well as step-by-step guides, to get you up to speed on prompt engineering in no time at all. The book has been written for the non-technical user to take the first steps in the world of generative AI. Along with a helpful glossary of common terms, lists of useful additional reading and resources, and other resources, you’ll get: Explanations of the basics of generative artificial intelligence that help you to learn what’s going on under the hood of ChatGPT and other LLMs Stepwise guides to creating effective, efficient, and ethical prompts that help you get the most utility possible from these exciting new tools Strategies for generating text, images, video, voice, music, and other audio from various publicly available artificial intelligence tools Perfect for anyone with an interest in one of the newest and most practical technological advancements recently released to the public, The Quick Guide to Prompt Engineering is a must-read for tech enthusiasts, marketers, content creators, technical professionals, data experts, and anyone else expected to understand and use generative AI at work or at home. No previous experience is required.




The Executive Guide to Artificial Intelligence


Book Description

This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.