What is synthetic data?
Synthetic data is created by Generative AI models trained on real world data samples. The algorithms first learn the patterns, correlations and statistical properties of the sample data. Once trained, the Generator can create statistically identical, synthetic data. The synthetic data looks and feels the same as the original data the algorithms were trained on.
What is AI powered synthetic data generation and how does it work?
Synthetic data generation is powered by deep generative algorithms. These algorithms use data samples as training data, in order to learn the correlations, statistical properties and data structures. Once trained, the algorithms can generate data, that is statistically and structurally identical to the original training data, however, all of the data points are synthetic.
Synthetic data subjects look real, but they are AI-generated and are completely artificial. When generating synthetic data, it’s extremely important to prevent the algorithm from overfitting to the original data. Overfitting means the AI could potentially learn “too well”, memorize original data and then accidentally leak original data points during the inference phase.
Not all synthetic data generators perform well and that’s why you want to make sure to work with synthetic data generators of highest quality.