### Q1: What are the two components of Generative Adversarial Networks (GANs) and their roles?
### Q2: How do Variational Autoencoders (VAEs) generate new data instances from a latent space representation?
### Q3: Explain the self-attention mechanism in Transformers and its significance in generative modeling.

### Q4: How can GANs be utilized in the fashion industry to assist designers?
### Q5: What is a potential application of VAEs in e-commerce to enhance user engagement?
### Q6: Describe a scenario where Transformers could improve customer service automation.

### Q7: How would you approach using a low-code method to implement GANs for generating images?
### Q8: What challenges might arise in a hands-on coding approach when developing applications with VAEs?
### Q9: In the context of mixed approaches, how can you effectively communicate the benefits of using Transformers in business applications?