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Answer :
Generative AI models like GANs generate new data samples, while discriminative AI models like SVMs classify data based on learned decision boundaries.
An example of a generative AI model is a Generative Adversarial Network (GAN). GANs are used to generate new data samples that have similar characteristics to the training data. They consist of two parts: a generator network that creates new samples and a discriminator network that tries to differentiate between real and generated samples.
An example of a discriminative AI model is a Support Vector Machine (SVM). SVMs are used for classification tasks and aim to find the best hyperplane that separates different classes in the input data. They focus on learning the decision boundary between classes rather than generating new data.
Generative AI models, such as GANs, focus on generating new data samples based on training data, while discriminative AI models, like SVMs, aim to classify and separate data into different classes based on learned decision boundaries.
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