2. Hybrid Approaches
- Combine synthetic data with fresh, real-world data to maintain diversity and accuracy.
- Use synthetic data to augment rather than replace traditional datasets entirely.
3. Continuous Monitoring
- Implement systems to track model performance and detect signs of quality degradation or collapse.
- Regularly assess the diversity and relevance of model outputs when trained on synthetic data.