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Generative AI

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Generative AI

By: Ajit Singh
Narrated by: Virtual Voice
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About this listen

 Generative Artificial Intelligence (Generative AI) is not just a frontier of technology—it's a paradigm shift in how we think about creativity, automation, and intelligence itself. When I first encountered the idea that a machine could write poetry, compose music, or even generate original research, it felt like science fiction. Today, it's an undeniable reality, transforming industries and inspiring new forms of human expression.

This book is the culmination of my academic journey, research, and reflective exploration into this fascinating and sometimes controversial domain. I have attempted to construct this book not just as a technical guide, but as a thoughtful and comprehensive account of what Generative AI is, what it can do, and what it means for humanity.

Generative AI encompasses a range of technologies, from language models like GPT and BERT to image-generation tools such as DALL·E and Stable Diffusion, and even musical and coding assistants. These systems are redefining the boundaries of what machines can create and how they collaborate with humans. In the following chapters, I discuss foundational theories, key architectures, real-world applications, ethical dilemmas, academic contributions, tools, and the future outlook. I have intentionally chosen to write in the first person, reflecting my personal experience as an academician and researcher. This is not merely a summary of existing knowledge, but a narrative woven from my own learning, experimentation, and reflections.

Whether you are a fellow researcher, a student, an industry professional, or simply someone curious about the future of AI, I hope this book serves as both a comprehensive guide and a source of inspiration. It is written with the conviction that knowledge should be accessible, actionable, and open to critique.

Let this be not the final word on Generative AI, but a conversation starter—an invitation to engage, explore, question, and innovate. Computer Science Mathematics Artificial Intelligence Data Science Robotics Technology Machine Learning
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