Generative AI: Exploring Models, Mechanisms, and Emerging Applications

Generative       AI        represents        a foundational shift from analytical to creative machine intelligence. As GANs, VAEs,       Transformers, and      Diffusion models mature,   their     responsible deployment will depend on transparency, efficiency, and governance. •    Multimodal generative systems, combining text, image, audio, and video generation within a single model. •    Agentic and autonomous AI workflows, where generative models plan and execute multi-step tasks. •    Explainable and sustainable model design, balancing capability with interpretability and energy efficiency. Generative Artificial Intelligence has emerged as a transformative technology capable of creating new content, including text, images, audio, video, and computer code. This study examined the fundamental models, mechanisms, architectures, applications, and emerging challenges associated with Generative AI. Overall, Generative AI represents a major advancement in artificial intelligence. Its continued development has the potential to transform numerous industries, but achieving sustainable benefits requires responsible design, appropriate regulation, human oversight, and careful consideration of ethical and societal impacts.

1.                Dhamani, N., & Engler, M. Introduction to Generative AI, Second Edition: Reliable, Responsible, and Real-World Applications. Manning Publications, 2025. — Covers Generative AI fundamentals, multimodal models, AI agents, reasoning models, RAG, risks, limitations, and realworld applications.  2.                Gupta, R., Tiwari, S., & Chaudhary, P. Generative AI: Techniques, Models and Applications. Springer Nature, 2025. — Particularly relevant to your thesis because it covers foundation models, large-scale architectures, Transformers, prompt engineering, and applications.  3.                Nidhya, R., Pavithra, D., Kumar, M., Kumar, A. D., & Balamurugan, S. (Eds.). Generative Artificial Intelligence: Concepts and Applications. Wiley, 2025. — Provides an overview of Generative AI fundamentals, applications, creativity, innovation, and industry transformation.  4.                Gayathri, N., Rakesh Kumar, S., Chandran, R., Chelliah, P. R., & Pelusi, D. (Eds.). Generative AI: Disruptive Technologies for Innovative Applications. Wiley, 2025. — Focuses on recent Generative AI technologies and their applications across different domains.  5.                Raza, K., Ahmad, N., & Singh, D. (Eds.). Generative AI: Current Trends and Applications.   Springer,             2024. — Covers GANs, AI image generation, AI text generation, Transformers, selfattention, NLP, and emerging applications. This is especially suitable for your architecture and applications chapters.  6.                Solanki, S. R., & Khublani, D. K. Generative Artificial Intelligence: Exploring the Power and Potential of Generative AI. Apress, 2024. — Covers text, image, video, and audio generation, LLMs, fine-tuning, prompt tuning, and enterprise applications.  7.Geetha, T. V. Generative AI. Pearson India,   2025.— Covers the fundamentals of Generative AI, deep generative models, generative modeling, applications, benefits, trends, and future directions.  8.  Ramamurthy, K., Kulanthaivelu, S., Anand, S., & Murugan, T. (Eds.). Generative AI Unleashed: Advancements, Transformative Applications and Future Frontiers. Institution of Engineering and Technology, 2025. — Focuses on recent advances, transformative applications, computational challenges, and future directions