Definition and Concept
Synthetic data refers to artificially generated information that mimics the characteristics of real-world data. It's created using algorithms and AI models rather than being collected from real-world sources.
Perceived Benefits
- Scalability: Theoretically unlimited generation of training examples.
- Customization: Ability to create data for specific scenarios or edge cases.
- Privacy preservation: Can generate data without using sensitive real-world information.
- Cost-effectiveness: Potentially cheaper than acquiring and annotating real-world data.
- Bias reduction: opportunity to create more balanced and diverse datasets.