Generative AI refers to computing technology that can generate seemingly novel and meaningful content from training data, including text, images, and audio. With the further development of artificial intelligence, artificial intelligence has entered a stage of rapid growth. This paper reviews the historical evolution of generative AI through the research method of literature review, from the introduction of artificial intelligence as a science in 1956 to the development of key technologies such as GAN, VAE, and Transformer in recent years. At the same time, it also analyzes the current technical status of generative AI, including the development of multimodal generative models and diffusion model technologies. While generative AI is developing rapidly, it has also brought a series of problems. This paper also discusses the challenges brought about by development, such as bias, data privacy, and legal supervision. In order to analyze the life cycle of generative AI, the S curve is used to analyze technology, market, and other factors. The results of the study show that generative AI is currently in a stage of rapid growth and will usher in more breakthroughs in the future. At the same time, it emphasizes the establishment of a technical ethics framework and a legal supervision mechanism to ensure the development of generative AI. The research results of this paper help to deepen the understanding of the development of generative AI technology and the evolution of commercial value, and provide a reference for researchers and practitioners in related fields.