Generative Artificial Intelligence: Exploring the Power and Potential of Generative AI

This book explains the field of Generative Artificial Intelligence (AI), focusing on its potential and applications, and aims to provide you with an understanding of the underlying principles, techniques, and practical use cases of Generative AI models.

The book begins with an introduction to the foundations of Generative AI, including an overview of the field, its evolution, and its significance in today's AI landscape. It focuses on generative visual models, exploring the exciting field of transforming text into images and videos. A chapter covering text-to-video generation provides insights into synthesizing videos from textual descriptions, opening up new possibilities for creative content generation. A chapter covers generative audio models and prompt-to-audio synthesis using Text-to-Speech (TTS) techniques. Then the book switch gears to dive into generative text models, exploring the concepts of Large Language Models (LLMs), natural language generation (NLG), fine-tuning, prompt tuning, and reinforcement learning. The book explores techniques for fixing LLMs and making them grounded and indestructible, along with practical applications in enterprise-grade applications such as question answering, summarization, and knowledge-based generation.

By the end of this book, you will understand Generative text, and audio and visual models, and have the knowledge and tools necessary to harness the creative and transformative capabilities of Generative AI.

What You Will Learn

• What is Generative Artificial Intelligence?
• What are text-to-image synthesis techniques and conditional image generation?
• What is prompt-to-audio synthesis using Text-to-Speech (TTS) techniques?
• What are text-to-video models and how do you tune them?
• What are large language models, and how do you tune them?

Who This Book Is For

Those with intermediate to advanced technical knowledge in artificial intelligence and machine learning

Shivam Solanki is an accomplished Senior Advisory Data Scientist leading the AI team for a worldwide partner ecosystem to solve challenging problems using Artificial Intelligence (AI). Shivam holds a master's degree from Texas A&M University with major coursework in Applied Statistics. Throughout his career, he has delved into various AI fields, including Machine Learning, Deep Learning, and Natural Language Processing (NLP). His expertise extends to Generative AI, where his practical experience and in-depth knowledge empower him to navigate its intricacies. As a researcher in Artificial Intelligence, Shivam has filed two patents for Machine Learning and Natural Language Processing (NLP), co-authored a book on Deep Learning, and published a paper in Generative AI.

Drupad Khublani is a skilled Senior Data Scientist and part of the revenue management team in a real estate company. His leadership in partnering with teams across marketing, call center operations, product management, customer experience, and operations has cultivated a wealth of experience, empowering him to extract actionable insights and co-create innovative solutions Drupad completed his graduate and postgraduate studies from the Indian Institute of Technology (Indian School of Mines) and Texas A&M University. Collaborating with Dr. Jean-Francois Chamberland on the development of technology to identify obstacles and gauge distances using only a monocular camera highlights Drupad's inventive approach and dedication to real-world applications, alongside his accomplishments in both the commercial and academic arenas.