Abstract
This essay explores the integration of Generative Artificial Intelligence (AI) models, including Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), in graphical big data analysis. Generative AI offers the generation of synthetic graphical data, improves data visualizations, and aids in pattern recognition within complex datasets. It presents innovative solutions to the challenges posed by large and intricate graphical datasets, enhancing the depth and accuracy of data analysis.
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