Which of the following is a well-known model used in Generative AI for generating text?

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The model recognized for its significant impact in the field of Generative AI for text generation is GPT, which stands for Generative Pre-trained Transformer. This model employs a transformer architecture that allows it to effectively understand and generate human-like text by learning from vast amounts of data. Its ability to generate coherent and contextually relevant text stems from its pre-training on diverse datasets, followed by fine-tuning for specific tasks. This adaptability makes it particularly powerful for various natural language processing tasks, including text completion, translation, and more.

In contrast, while BERT (Bidirectional Encoder Representations from Transformers) is designed primarily for understanding language rather than generating text, LSTM (Long Short-Term Memory) and RNN (Recurrent Neural Networks) are older architectures that can generate text but are generally less effective than transformer-based models like GPT in handling complex dependencies in text due to issues like vanishing gradients. Therefore, GPT stands out as the most suitable choice for text generation in the context of Generative AI.

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