### Q1: What is the primary metric used to assess the overall correctness of a Generative AI model's predictions?  
### Q2: How can high precision in a credit scoring model minimize financial risks?  
### Q3: In the context of evaluating AI models, what is the significance of the F1 Score when dealing with class imbalance?  
### Q4: Why might a product manager at Test_Company prefer K-Fold Cross-Validation over a simple train-test split?  
### Q5: Can you provide an example of when to apply hyperparameter tuning to improve model performance?  
### Q6: How does cross-validation contribute to reducing overfitting in AI models?  
### Q7: What strategies can be used to effectively communicate the importance of performance metrics to stakeholders at Test_Company?  
### Q8: How can a product manager articulate the need for continuous performance monitoring of AI models to their team?  
### Q9: What are some best practices for conveying complex technical concepts related to AI model evaluation to a non-technical audience?