### Q1: What are training datasets and why are they important in developing a Generative AI model?  
### Q2: How can the quality of a training dataset impact the performance of a Generative AI model?  
### Q3: What are some advanced techniques to ensure that a Generative AI model does not overfit the training data?  
### Q4: How can a finance professional effectively utilize the concept of neural networks to enhance predictive analytics in their organization?  
### Q5: In what ways can understanding overfitting improve a finance professional's model selection process?  
### Q6: How can familiarity with Generative AI terms contribute to more effective decision-making in finance?  
### Q7: How would you explain the concept of a loss function to a non-technical stakeholder in your organization?  
### Q8: What are some effective strategies for communicating complex Generative AI concepts to colleagues who may not have a technical background?  
### Q9: How can enhancing your communication skills help you collaborate with technical teams when implementing Generative AI solutions?