### Q1: What does a high Inception Score indicate about the quality of generated images?  
### Q2: How does the Fréchet Inception Distance provide a more nuanced evaluation compared to the Inception Score?  
### Q3: Why might a model with a low Fréchet Inception Distance score be considered superior in terms of output quality?  
### Q4: How can human evaluation techniques complement quantitative metrics like IS and FID in assessing generative models?  
### Q5: What is the purpose of comparison testing in human evaluation, and how does it enhance feedback on generative models?  
### Q6: How can the Likert scale assessment improve the granularity of feedback received on generated outputs?  
### Q7: What are the implications of not evaluating generative AI models regularly for a business like No Name?  
### Q8: How can continuous evaluation of generative models align with changing market needs and user expectations?  
### Q9: In what ways can rigorous evaluation metrics foster transparency and trust with stakeholders in AI development?