Volume 2 - Issue 2, March - April 2026

Generative and Multimodal Artificial Intelligence (AI) represents a significant shift in the evolution of intelligent systems, moving beyond traditional rulebased and single-modality approaches. Modern AI systems are expected not only to analyze data but also to generate new, meaningful, and contextaware content across multiple data modalities such as text, images, audio, and video. Traditional artificial intelligence techniques were limited in their ability to model real-world complexity, as they typically relied on isolated data sources and predefined logic. In contrast, generative AI models learn underlying data distributions and produce novel outputs, while multimodal AI integrates diverse data types to achieve a richer and more holistic understanding.The convergence of generative and multimodal AI has been driven by advancements in deep learning, transformer architectures, large-scale datasets, and increased computational power. These systems enable natural human–computer interaction, automate creative processes, and support complex decision-making tasks.

Manoj P, Srinath R, Ranjana C, Gowri.K,"Intelligent Generative Models and Multimodal AI Integration" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(399-404) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.