AI-Generated Content (AIGC): A Survey
Jiayang Wu, Wensheng Gan, Zefeng Chen, Shicheng Wan, Hong Lin

TL;DR
This survey comprehensively reviews AI-generated content (AIGC), highlighting its capabilities, technological advancements, applications, challenges, and future prospects, especially in relation to large models and integration with the Metaverse.
Contribution
It provides an extensive overview of AIGC, including definitions, capabilities, industry chain, and future directions, offering a valuable resource for understanding this emerging technology.
Findings
AIGC leverages large-scale pre-trained models for diverse content generation.
AIGC supports various downstream applications and has significant industrial potential.
Challenges include current limitations and issues needing future research.
Abstract
To address the challenges of digital intelligence in the digital economy, artificial intelligence-generated content (AIGC) has emerged. AIGC uses artificial intelligence to assist or replace manual content generation by generating content based on user-inputted keywords or requirements. The development of large model algorithms has significantly strengthened the capabilities of AIGC, which makes AIGC products a promising generative tool and adds convenience to our lives. As an upstream technology, AIGC has unlimited potential to support different downstream applications. It is important to analyze AIGC's current capabilities and shortcomings to understand how it can be best utilized in future applications. Therefore, this paper provides an extensive overview of AIGC, covering its definition, essential conditions, cutting-edge capabilities, and advanced features. Moreover, it discusses…
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Taxonomy
TopicsTopic Modeling
