This book is a comprehensive guide for business leaders, CXOs, and technical architects looking to adopt Generative AI technologies to create innovative applications for their organizations and clients.

The book is divided into three parts. In Part 1, readers will learn the fundamental concepts of Generative AI, such as foundational models and large language models like ChatGPT. It provides an overview of various Generative AI techniques, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). This section helps leaders understand the benefits and risks associated with Generative AI, supported by industry case studies showcasing real-world applications. Part 2 focuses on developing a winning strategy for implementing Generative AI. It discusses choosing the right approach, building the necessary architecture and infrastructure, and ensuring data quality for training models. It also addresses technical challenges like computing power and offers best practices for execution. In Part 3, the book explores best practices for adopting Generative AI, emphasizing governance, talent development, and continuous improvement. It also discusses emerging trends and the societal impact of Generative AI, particularly concerning sustainability.

By the end, readers will be equipped with the knowledge and strategies to effectively harness Generative AI, paving the way for innovation in their organizations.

What you will learn:

• What are the various Generative AI technologies – Foundational models, LLM, Auto encoders, GANs, VAEs, RAG, prompt engineering and more.
• How to build a successful strategy for architecting and implementing Generative AI
• Understand Preprocessing and setting up quality data for training generative AI models
• What are the future trends in generative AI to build sustainable and trustworthy solutions

Who this book is for:

Individuals in leadership positions, such as CEOs, CTOs, CIOs, and other senior executives, who are responsible for driving innovation and strategy. decision-making in their organizations and interested in adopting Gen AI for that purpose. Professionals who design and implement technical solutions and infrastructure using Generative AI and machine learning systems.