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OpenAI and ChatGPT, as state-of-the-art language models driven by cutting-edge artificial intelligence technology, have gained widespread adoption across diverse industries. In the realm of computer vision, these models have been employed for intricate tasks including object recognition, image generation, and image processing, leveraging their advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have found utility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactive player experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providing invaluable insights and support to healthcare professionals in the realm of disease detection. The principal objective of this paper is to offer a comprehensive overview of OpenAI, OpenaiGym, ChatGPT, DALL E, stable diffusion, the pre-trained clip model, and other pertinent models in various domains, encompassing CLIP Text-to-Image, education, medical imaging, computer vision, social influence, natural language processing, software development, coding assistance, and Chatbot, among others. Particular emphasis will be placed on comparative analysis and examination of popular text-to-image and text-to-video models under diverse stimuli, shedding light on the current research landscape, emerging trends, and existing challenges within the domains of OpenAI and ChatGPT. Through a rigorous literature review, this paper aims to deliver a professional and insightful overview of the advancements, potentials, and limitations of these pioneering language models.
Hong et al. (Wed,) studied this question.