Exploring Generative AI with Computational Intelligence: Navigating the Uncertainty of Creative Machines

This book demystifies the concept of AI-driven creativity with an in-depth understanding of the underlying principles, algorithms, and applications of generative AI. It begins with a coverage of AI fundamentals, followed by a technical discussion including detailed explanations of model architectures, training processes, and optimisation techniques. It explores case studies showcasing how generative AI is reshaping industries such as entertainment, marketing, design, and healthcare. The book also tackles ethical considerations, addressing issues related to bias, transparency, and responsible AI development. Features: Provides deep understanding of generative AI, including in-depth coverage of various generative models such as GANs, VAEs, and RNNs. Includes practical, real-world examples of how generative AI is applied in different industries. Dedicates significant attention to ethical considerations. Equips readers with the knowledge and tools to build, train, and deploy their own generative AI systems. Offers thorough explanations of AI algorithms, neural network architectures, and training processes. This book is aimed at graduate students and researchers in computer engineering, AI and ML.