International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Convergence of Big Data and Generative AI: A Paradigm Shift in Data Analytics

Author(s) Akbar Sharief Shaik
Country United States
Abstract The convergence of big data and generative artificial intelligence represents a transformative paradigm
shift in data analytics and processing capabilities. This comprehensive article review examines the
evolution, current state, and future implications of this technological integration across multiple sectors.
The article explores advanced learning paradigms, including few-shot and zero-shot learning, which have
revolutionized traditional machine learning approaches. The article delves into multimodal integration
capabilities that enable simultaneous processing of diverse data types, enhancing analytical accuracy and
decision-making processes. The article addresses critical technical implementation challenges, focusing
on computational infrastructure demands, environmental impact, and sustainability considerations.
Furthermore, the article examines crucial aspects of data privacy and ethical considerations, including
security protocols, bias mitigation, and regulatory compliance. The article analysis extends to practical
industry applications across healthcare, financial services, and manufacturing sectors, demonstrating
substantial improvements in operational efficiency and decision-making capabilities. This article
synthesizes current developments while providing insights into future directions and opportunities,
emphasizing the increasingly critical role of responsible AI development and implementation strategies.
Keywords Keywords: Generative Artificial Intelligence, Multimodal Integration, Few-Shot Learning, Privacy-Preserving Computing, Sustainable AI Development
Field Computer
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-12-01
Cite This The Convergence of Big Data and Generative AI: A Paradigm Shift in Data Analytics - Akbar Sharief Shaik - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32142
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.32142
Short DOI https://doi.org/g8tgqf
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