This paper reviews the history and future of Artificial Intelligence Generated Content (AIGC), tracing its evolution from rule-based systems to advanced deep and transfer learning models. The authors provide a framework for understanding AIGC, categorizing its development into four key milestones and illustrating each with a consistent example. The paper also addresses significant challenges, such as data bias, model scalability, and ethical concerns, offering potential solutions and future research directions. A comprehensive literature review supports the analysis, showcasing the breadth of AIGC applications across various domains. Ultimately, the study aims to guide researchers and practitioners in utilizing AIGC effectively and responsibly.

https://arxiv.org/pdf/2412.01948