Exam DP-100 topic 1 question 33 discussion

sequence of the....? is the question incomplete?

Generative Adversarial Networks (GAN) for training generative AI. Recurrent Neural Networks (RNN) for training text (words sequence) in term of seq2seq, but now it is out of date, use Transformer as alternative solution. Anyway, GAN is incorrect for NLP (translation). https://learn.microsoft.com/en-us/azure/machine-learning/concept-deep-learning-vs-machine-learning?view=azureml-api-2#generative-adversarial-network-gan https://learn.microsoft.com/en-us/azure/machine-learning/concept-deep-learning-vs-machine-learning?view=azureml-api-2#machine-translation

GAN's are for new data generation.

No, Generative adversarial networks (GANs) are algorithmic architectures that use two neural networks, pitting one against the other (thus the “adversarial”) in order to generate new, synthetic instances of data that can pass for real data. They are used widely in image generation, video generation and voice generation.

GANs used for image translation