Название: Generative Artificial Intelligence: Exploring the Power and Potential of Generative AI
Автор: Shivam R Solanki, Drupad K Khublani
Издательство: Apress
Год: 2024
Страниц: 465
Язык: английский
Формат: pdf (true), epub
Размер: 18.4 MB

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.




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