Multimodal Generative AI: Integrating Text, Image, Audio, and Video for Seamless Media Synthesis
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Abstract
The fusion of text, image, audio, and video through multimodal Generative AI systems is reshaping how digital content is created and consumed. This paper delves into the architecture of state-of-the-art multimodal models such as GPT-4V, DALL·E, and Make-A-Video, focusing on their training paradigms, capabilities, and applications. We evaluate their use in marketing, education, entertainment, and accessibility. Challenges related to alignment, synchronization, and coherence across modalities are discussed, along with strategies for improving cross-modal generation fidelity.
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References
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