Synthetic Data Generation, Technological Aspects and Challenges - Satseradze, David; Zedginidze, Gocha (International Scientific-practical Conference: „Modern Challenges and Achievements in Information and Communication Technologies“ Transactions, 2026)
The increasing complexity of machine learning models and stricter data protection regulations are driving a growing demand for large and diverse datasets. Synthetic data, artificially generated by algorithms, represents a powerful solution to this problem and are becoming an essential tool in modern data science and artificial intelligence. Their use addresses challenges related to data scarcity, privacy protection, and ensuring sample balance. This paper provides an overview of modern synthetic data generation techniques, their applications in artificial intelligence and computer science, and discusses key challenges and directions for future research.