Generative AI

Abstract

Recent advancements in generative artificial intelligence (AI) have made it possible for machines to independently produce avariety of creative content. In the context of producing creative content, this essay examines the developments, difficulties, and ethical issues relating to generative AI. It looks into how generative models, such Generative Adversarial Networks (GANs) and Variational Auto encoders (VAEs), can produce realistic artwork like music, literature, and visuals. However, it is frequently discovered that GAN training is extremely unstable and frequently experiences non-convergence, mode collapse, and hyperparameter sensitivity [1]. The technical details of developing and optimizing generative models to produce desired results are covered in detail in this work. It also looks at the difficulties in guaranteeing the variety, creativity, and coherence of generated content. Additionally, the use of generative AI in the creation of original material raises ethical questions. Included in this are concerns about intellectual property, plagiarism, and possible effects on the creative industries. In specifically, the article explores the consequences of employing generative AI for content production in terms of authorship, human creativity, and the possible disruption of traditional creative practices. It also covers issues with fairness, bias, and appropriate application of generative models.