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In today's digital age, the power of artificial intelligence (AI) is continually expanding its reach, revolutionizing various aspects of our lives. AI has brought innovation to the world of image generation, making it easier and more accessible than ever before, but here we would like to focus on some historical mistakes that is not been considered in the current audit stages so we can be able to help improving the accurate final result. In recent years, the field of artificial intelligence has witnessed significant advancements in generating and manipulating visual content. One prominent area of development within this domain is AI image generators, These generators hold immense potential across diverse applications, revolutionizing industries such as advertising, entertainment, and digital art creation. As artificial intelligence continues to evolve, its ability to generate and manipulate images has reached remarkable levels of sophistication. However, alongside their impressive capabilities, AI image generators are also prone to making intriguing and sometimes puzzling mistakes. These errors can range from minor imperfections to profound distortions, raising important questions about the limitations and ethical implications of AI in visual content creation. Understanding these mistakes not only sheds light on the underlying algorithms and processes but also prompts critical reflections on the broader implications of relying on AI for creative and practical applications. This research aims to explore and analyze the nature, causes, and consequences of mistakes made by AI image generators, offering insights into their development, usability, societal impact, and how can ideas be proposed to support artificial intelligence thinking to extract historically correct images through an open source of information for experts everywhere, regardless of their specializations.
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