Generative Models and Applications By A Staff Writer / July 10, 2025 Welcome to your Generative Models and Applications Level: Expert What is the primary purpose of a Generative Adversarial Network (GAN)? To analyze large datasets To generate new data similar to the training set To optimize neural networks To label data automatically None Which component in GANs generates new data? Generator Discriminator Encoder Feature Extractor None What is the role of the discriminator in a GAN? To compress the dataset To distinguish between real and generated data To evaluate the loss function To optimize gradients None Which generative model uses a sequence-to-sequence approach? GANs Variational Autoencoders (VAEs) Transformers K-Nearest Neighbors None What is a major challenge in training GANs? Limited computational resources The generator overpowering the discriminator Insufficient data storage High inference latency None Time's up
