Harnessing Synthetic Data Value for AI Applications

Harnessing Synthetic Data Value for AI Applications

This IDC Market Perspective examines artificial data solutions for AI applications. It also discusses categories of synthetic data generation, use cases, benefits, and challenges. The use of synthetic data helps preserve the confidentiality of the original data set while enhancing the accuracy of the trained model. Synthetic data can be generated rapidly, and users can train models with a minimal initial data set, which can help eliminate some of the bias that results from training on a small quantity of data. Furthermore, the generation of synthetic data is less expensive. This enables organizations to rapidly construct and test AI models without the need for large amounts of actual data. This can assist in reducing costs and accelerating the development process."Synthetic data is emerging as a solution to data scarcity and privacy concerns as the need for data-driven decision making increases," Raghunandhan Kuppuswamy, research manager for AI Software and Strategies, stated. "Organizations have begun experimenting with their AI applications more than ever. Organizations can enhance the accuracy and efficacy of AI models by utilizing synthetic data. This can lead to enhanced decision making, more efficient processes, and better results."

Please Note: Extended description available upon request.