Genius Machines Unlocking the Power of AI
商品資訊
ISBN13:9798282232806
出版社:Independently published
作者:Anshuman Mishra
出版日:2025/05/02
裝訂:平裝
規格:27.9cm*21.6cm*2.2cm (高/寬/厚)
商品簡介
商品簡介
In an era where artificial intelligence is reshaping every industry, "GENIUS MACHINES: Unlocking the Power of Generative AI" serves as your ultimate guide to understanding, applying, and mastering one of the most transformative technologies of our time. This comprehensive book is designed for students, educators, developers, researchers, business leaders, and curious minds eager to delve into the expansive universe of generative AI. Covering foundational theories, cutting-edge models, practical applications, and real-world deployment strategies, this book empowers readers with the knowledge and tools to not only understand but also innovate with generative AI.
A Transformative Journey Through Generative AI
This book begins with a foundational understanding of generative artificial intelligence, laying down the core principles and mathematical underpinnings essential to grasp the working of modern AI systems. With a thorough introduction to neural networks, machine learning basics, and the evolution of AI from traditional paradigms to generative models, the reader is equipped with a strong conceptual framework.
The journey then takes a deep dive into key generative models, including Autoencoders, Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers, and Diffusion Models. Each model is dissected with clarity, supported by illustrations, real-life use cases, and code snippets where applicable. Whether it's understanding the latent space in VAEs, the adversarial play in GANs, or the attention mechanisms in transformers, this book makes complex ideas accessible.
Applications Across Industries
The applications of generative AI are vast and varied. This book showcases how generative AI is revolutionizing text generation, image creation, music and voice synthesis, video generation, software development, and gaming. From content creators using tools like DALL-E and MidJourney, to developers harnessing the power of GitHub Copilot, to educators using AI-generated lessons-every chapter illustrates how generative AI is being used to create, assist, and inspire.
Readers will learn how large language models like GPT-4, Claude, and LLaMA work under the hood and how these models are employed in writing assistants, virtual tutors, customer support bots, and more. The book also explores the rise of diffusion models in image generation and the promising use of generative models in domains like drug discovery, architecture, virtual reality, and filmmaking.
Hands-On Implementation
One of the unique features of this book is its practical orientation. Along with theoretical foundations, the book walks you through tools, libraries, and frameworks such as TensorFlow, PyTorch, Hugging Face, and Streamlit. By following guided tutorials, readers can build their own generative AI models-from a simple text generator to a fully functional AI artist.
Detailed walkthroughs on integrating APIs like OpenAI and Stability AI enable the reader to deploy applications in real-world environments. Prompt engineering, fine-tuning, and evaluation techniques are thoroughly covered to ensure that readers can not only generate content but do so meaningfully and ethically.
Ethics, Future Outlook, and Career Opportunities
No book on AI is complete without addressing its societal implications. This book dedicates chapters to ethical considerations, responsible AI development, the prevention of AI misuse, and regulatory frameworks being considered globally. It discusses deepfakes, misinformation, and intellectual property concerns with a balanced and practical viewpoint.
The concluding chapters project the future of generative AI, examining trends such as Artificial General Intelligence (AGI), multimodal AI systems, and the co-evolution of humans and machines. The reader is also presented with career pathways, academic routes, and entrepreneurial opportunities in the generative AI
A Transformative Journey Through Generative AI
This book begins with a foundational understanding of generative artificial intelligence, laying down the core principles and mathematical underpinnings essential to grasp the working of modern AI systems. With a thorough introduction to neural networks, machine learning basics, and the evolution of AI from traditional paradigms to generative models, the reader is equipped with a strong conceptual framework.
The journey then takes a deep dive into key generative models, including Autoencoders, Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), Transformers, and Diffusion Models. Each model is dissected with clarity, supported by illustrations, real-life use cases, and code snippets where applicable. Whether it's understanding the latent space in VAEs, the adversarial play in GANs, or the attention mechanisms in transformers, this book makes complex ideas accessible.
Applications Across Industries
The applications of generative AI are vast and varied. This book showcases how generative AI is revolutionizing text generation, image creation, music and voice synthesis, video generation, software development, and gaming. From content creators using tools like DALL-E and MidJourney, to developers harnessing the power of GitHub Copilot, to educators using AI-generated lessons-every chapter illustrates how generative AI is being used to create, assist, and inspire.
Readers will learn how large language models like GPT-4, Claude, and LLaMA work under the hood and how these models are employed in writing assistants, virtual tutors, customer support bots, and more. The book also explores the rise of diffusion models in image generation and the promising use of generative models in domains like drug discovery, architecture, virtual reality, and filmmaking.
Hands-On Implementation
One of the unique features of this book is its practical orientation. Along with theoretical foundations, the book walks you through tools, libraries, and frameworks such as TensorFlow, PyTorch, Hugging Face, and Streamlit. By following guided tutorials, readers can build their own generative AI models-from a simple text generator to a fully functional AI artist.
Detailed walkthroughs on integrating APIs like OpenAI and Stability AI enable the reader to deploy applications in real-world environments. Prompt engineering, fine-tuning, and evaluation techniques are thoroughly covered to ensure that readers can not only generate content but do so meaningfully and ethically.
Ethics, Future Outlook, and Career Opportunities
No book on AI is complete without addressing its societal implications. This book dedicates chapters to ethical considerations, responsible AI development, the prevention of AI misuse, and regulatory frameworks being considered globally. It discusses deepfakes, misinformation, and intellectual property concerns with a balanced and practical viewpoint.
The concluding chapters project the future of generative AI, examining trends such as Artificial General Intelligence (AGI), multimodal AI systems, and the co-evolution of humans and machines. The reader is also presented with career pathways, academic routes, and entrepreneurial opportunities in the generative AI
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