GENERATING SYNTHETIC DATA FOR TRAINING ARTIFICIAL INTELLIGENCE

This scientific article provides a comprehensive analysis of the generation ofsynthetic (artificially created) data for training artificial intelligence (AI) systems and the prospectsof this direction. Modern AI models require enormous amounts of data for training, but collectingreal data is often expensive, time-consuming, or impossible due to privacy concerns. The researchscientifically substantiates the methods of creating artificial data that resembles real data (generativemodels, simulations), its advantages, and its limitations. The article examines the use of syntheticdata in solving privacy problems, eliminating data shortages, and balancing datasets. The scientificnovelty of the article lies in demonstrating that synthetic data is becoming an important tool for thedevelopment of AI. As a result of the analyses, recommendations are developed regarding theapplication of these technologies and their reliability