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Generative transformers have revolutionized the realm of artificial intelligence, particularly in the domain of natural language processing. This paper embarks on a historical journey, tracing the roots of computational theory with Alan Turing and culminating in the sophisticated generative transformer architectures of today. Through a blend of review, history, and tutorial, we aim to provide a holistic understanding of these models, emphasizing their significance, underlying mechanisms, and vast applications. The tutorial segment offers a hands-on approach, guiding readers through the intricacies of building a basic generative transformer model. As we navigate this transformative landscape, we also shed light on challenges, ethical considerations, and future prospects in the world of generative models.
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Cheok et al. (2023) studied this question.
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