Название: Understanding Generative AI Business Applications: A Guide to Technical Principles and Real-World Applications
Автор: Irena Cronin
Издательство: Apress
Год: 2024
Страниц: 262
Язык: английский
Формат: pdf, epub
Размер: 36.2 MB

This guide covers the fundamental technical principles and various business applications of Generative AI for planning, developing, and evaluating AI-driven products. It equips you with the knowledge you need to harness the potential of Generative AI for enhancing business creativity and productivity.

The book is organized into three sections: text-based, senses-based, and rationale-based. Each section provides an in-depth exploration of the specific methods and applications of Generative AI. In the text-based section, you will find detailed discussions on designing algorithms to automate and enhance written communication, including insights into the technical aspects of transformer-based Natural Language Processing (NLP) and chatbot architecture, such as GPT-4, Claude 2, Google Bard, and others. The senses-based section offers a glimpse into the algorithms and data structures that underpin visual, auditory, and multisensory experiences, including NeRF, 3D Gaussian Splatting,Stable Diffusion, AR and VR technologies, and more. The rationale-based section illuminates the decision-making capabilities of AI, with a focus on machine learning and data analytics techniques that empower applications such as simulation models, agents, and autonomous systems.

In summary, this book serves as a guide for those seeking to navigate the dynamic landscape of Generative AI. Whether you’re a seasoned AI professional or a business leader looking to harness the power of creative automation, these pages offer a roadmap to leverage Generative AI for your organization’s success.

Chapter 1 introduces readers to the realm of Generative AI, setting the stage for a journey through its capabilities and promise. Chapter 2 delves into the core technical concepts that form the backbone of these systems, elucidating the algorithms and architectures that enable machines to generate new, original content.
In Chapter 3, the focus shifts to the commercial implications of Generative AI, demonstrating its potential to revolutionize business models and value chains. Chapter 4 zooms in on text-based applications, revealing how Generative AI is powering a new generation of language models.
Chapter 5 unpacks the intricacies of transformer-based natural language processing (NLP), the architecture driving the most advanced language models today. Chapter 6 ventures into the chatbot technology landscape, showing how conversational agents are becoming more nuanced and context-aware.
Chapter 7 presents advanced applications of text-based AI, highlighting innovative use cases and the expansion of AI's linguistic prowess. Chapter 8 demystifies senses-based Generative AI, extending the discussion to how AI is interpreting and synthesizing sensory data.
Chapter 9 provides an in-depth look at supportive visual algorithms and computer vision, essential for understanding how AI perceives and processes visual information. Chapter 10 discusses auditory and multisensory experiences, showcasing AI's ability to engage with the world in a holistic, human-like manner.
Chapter 11 examines autonomous AI agents, diving into the decision-making processes, data analysis, and algorithms that enable autonomy. Chapter 12 expands on Text-Based Generative Intelligent Agents, exploring the evolution beyond traditional chatbots to more sophisticated virtual assistants.
Real-world applications and case studies come to the forefront in Chapter 13, illustrating the tangible impacts of Generative AI across sectors. Chapter 14 summarizes key insights, distilling the lessons learned into actionable knowledge. Finally, Chapter 15 reflects on the evolving landscape of Generative AI, contemplating future directions and the ethical considerations of this powerful technology.

Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub.

What You Will Learn:
What are the technical elements that constitute the makeup of Generative AI products?
What are the practical applications of Generative AI?
How can algorithms be designed to automate and improve written communication?
What are the latest Generative AI architectures and algorithms?

Who This Book Is For:
Data scientists, data analysts, decision makers, and business executives interested in gaining an understanding of Generative AI products








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