Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/306304 
Year of Publication: 
2023
Citation: 
[Journal:] Electronic Markets [ISSN:] 1422-8890 [Volume:] 33 [Issue:] 1 [Article No.:] 63 [Publisher:] Springer [Place:] Berlin, Heidelberg [Year:] 2023
Publisher: 
Springer, Berlin, Heidelberg
Abstract: 
Recent developments in the field of artificial intelligence (AI) have enabled new paradigms of machine processing, shifting from data-driven, discriminative AI tasks toward sophisticated, creative tasks through generative AI. Leveraging deep generative models, generative AI is capable of producing novel and realistic content across a broad spectrum (e.g., texts, images, or programming code) for various domains based on basic user prompts. In this article, we offer a comprehensive overview of the fundamentals of generative AI with its underpinning concepts and prospects. We provide a conceptual introduction to relevant terms and techniques, outline the inherent properties that constitute generative AI, and elaborate on the potentials and challenges. We underline the necessity for researchers and practitioners to comprehend the distinctive characteristics of generative artificial intelligence in order to harness its potential while mitigating its risks and to contribute to a principal understanding.
Subjects: 
Generative AI
Artificial intelligence
Deep learning
Deep generative models
Large language models
JEL: 
C8
M21
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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