Digital Generative Multimedia Tool Theory (DGMTT): A Theoretical Postulation in the Era of Artificial Intelligence

Abstract

Timothy Ekeledirichukwu Onyejelem and Eric Msughter Aondover

The advent of Artificial Intelligence (AI) has revolutionized the way multimedia content is created, processed, and consumed. The Digital Generative Multimedia Tool Theory (DGMTT) aims to provide a theoretical framework for understanding the implications, mechanics, and potential of AI-driven tools in the realm of multimedia. The theory addresses the convergence of AI with digital media creation, exploring how generative models influence artistic expression, content generation, and the broader cultural landscape. The use of generative technologies to produce digital multimedia material is one of the newer developments in this field. DGMTT is therefore presented as a theoretical foothold to address new innovation in the 21st century dominated AI. In this logic framework, it is argued that AI tools provide users with interactive capabilities to generate and modify multimedia content, offering new dimensions of creative freedom and flexibility. Interactive AI tools deepen user engagement by allowing personalized content creation and real-time feedback during the creative process. Thus, DGMTT offers an all-encompassing structure for comprehending and evaluating the fundamentals and consequences of generative tools in the production of multimedia content. It provides information about the creation and use of these instruments, thereby promoting developments in the digital media industry. These tools create dynamic and interactive multimedia content by utilizing machine learning, artificial intelligence, and algorithms. This theory emphasizes how crucial it is to comprehend the fundamental ideas and principles of generative tools in order to use them efficiently when creating digital media content.

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