Which component tries to distinguish between the real data in the training set and the generated data?

• A. Generator in GAN
• B. Discriminator in GAN
• C. Transformer
• D. Cloud Platforms

Answer: (B)

In a Generative Adversarial Network, two parts compete: a generator and a discriminator. The discriminator’s job is to tell apart real data from the data produced by the generator. It learns to assign a probability that any given sample is real, effectively drawing a boundary between authentic data and fakes. This feedback guides the generator to improve, as its goal is to produce data that the discriminator is increasingly likely to classify as real. The transformer is a different model type used for sequence tasks, not specifically for distinguishing real versus generated data, and cloud platforms are just infrastructure, not part of the learning process.