Daeil discusses the critical role of synthetic data in addressing societal biases present in real-world data. By allowing for greater control over the data used to train algorithms, it shifts the focus from architectural adjustments to data modification. Additionally, he highlights how synthetic data can provide annotations that are impossible for humans to achieve, enhancing the efficiency and accuracy of machine learning processes.
