Generative AI Architectures and Applications: Navigating the Evolution

Trace generative AI from GPT through transformer architectures and beyond

Large Language Models (LLMs) have evolved rapidly from general-purpose architectures to sophisticated transformer-based systems, yet technical references mapping this progression across domains remain scarce. Generative AI Architectures and Applications: Navigating the Evolution addresses this directly, covering LLM fundamentals alongside applications in image processing, speech recognition, natural language processing, and multimodal learning. The book examines both the technical advancements and ongoing challenges shaping these architectures.

Beyond core model architectures, the book explores the integration of generative AI with blockchain and IoT analytics, revealing convergence points that drive new capabilities. Detailed coverage traces the path from GPT to modern transformer designs, analyzing trade-offs and limitations at each stage. Readers gain structured insight into future directions, technical obstacles, and practical implications of deploying generative models across industries.

The book also covers: Generative adversarial networks (GANs) and their role in realistic content generation spanning text, image, music, and video production workflows and applications Multimodal learning frameworks that combine vision, language, and audio processing capabilities within unified generative model architectures Technical challenges associated with scaling LLMs, including computational demands, data requirements, and fundamental architectural constraints across deployments Applications of generative AI across healthcare, education, content production, design, and software development contexts and use cases Emerging convergence patterns between generative models and distributed technologies such as blockchain-based verification and IoT analytics systems

Designed for data scientists, professors, government officials, researchers, and software engineers, this volume provides the architectural depth and cross-domain perspective needed to evaluate generative AI systems critically. Whether assessing deployment feasibility or advancing research agendas, readers will find a structured, technically grounded reference for navigating the generative AI landscape.

• Format: Hardcover
• Language: English
• ISBN: 1394420048
• ISBN13: 9781394420049
• Release Date: July 2027
• Publisher: Wiley-IEEE Press
• Length: 240 Pages