Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

Abumalloh, Rabab Ali; Nilashi, Mehrbakhsh; Ooi, Keng Boon; Tan, Garry Wei Han; Chan, Hing Kai

doi:10.1016/j.compind.2024.104128

Computers in Industry

2024

DOI: 10.1016/j.compind.2024.104128

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Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

Rabab Ali Abumalloh,

Mehrbakhsh Nilashi,

Keng Boon Ooi

et al.

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Generative Ai: A Tool for Addressing Data Scarcity in Scientific Research

Miller,

Durlik,

Łobodzińska

et al. 2024

GoS

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Generative AI, a pivotal advancement in data science, addresses data scarcity by producing high-quality synthetic data that mirrors real-world data. This article explores Generative AI's capabilities, including data augmentation, privacy-preserving anonymization, simulation of rare events, and cost-efficient data collection. Techniques such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) are discussed, highlighting their role in creating realistic and diverse synthetic data. The practical applications span healthcare, finance, and climate science, demonstrating Generative AI's transformative potential in enhancing research across various scientific disciplines.

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Generative Ai: A Tool for Addressing Data Scarcity in Scientific Research

Miller,

Durlik,

Łobodzińska

et al. 2024

GoS

View full text Add to dashboard Cite

show abstract

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Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

Cited by 1 publication

References 80 publications

Generative Ai: A Tool for Addressing Data Scarcity in Scientific Research

Generative Ai: A Tool for Addressing Data Scarcity in Scientific Research

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