Title: AI, Innovation and Global Transformation: Interdisciplinary Perspectives on Technology, Business and Society
Editors: Dr. J. Preetha, and Dr. Siddhartha Mehrotra
ISBN: 978-81-69857-64-2
Chapter: 2
DOI: https://doi.org/10.59646/809/02
Author: Deva Kirupa Dani D
Abstract
Generative Artificial Intelligence (GenAI) has emerged as a transformative technology capable of autonomously creating text, images, audio, video, software code, and multimodal content. Built upon deep learning architectures, large language models, diffusion models, generative adversarial networks, and multimodal foundation models, GenAI is changing conventional approaches to content production and human–computer collaboration. This chapter examines the technological foundations, mathematical modelling, algorithms, applications, and performance characteristics of autonomous content creation systems. A structured methodology is employed to analyze content quality, generation time, semantic relevance, originality, user satisfaction, and computational efficiency across different generative approaches. The chapter develops a mathematical framework representing content generation as a probabilistic optimization process involving prompts, latent representations, model parameters, and quality constraints. Synthesized experimental results indicate that transformer-based and multimodal systems provide strong performance in semantic coherence and content diversity, while diffusion-based models demonstrate high visual quality. The chapter also addresses hallucination, copyright, bias, privacy, misinformation, evaluation, and human oversight.
Keywords: Generative AI, Autonomous Content Creation, Large Language Models, Diffusion Models, Multimodal AI, Foundation Models