Let’s advanced AI
with Synthetic Data!
Synthetic data refers to data generated in a digital environment rather than collected in the physical environment. By constructing a situation or environment that cannot exist in reality, it is possible to mass produce new data from various domains. The value of synthetic data is becoming higher because it contributes to the enhancement of accuracy in the training of AI models and enables the development of Advanced AI with less amount of real data.
Why IS synthetic data IMPORTANT?
- Enhancing AI performance
- Privacy issues that need to be addressed ethically
- Identify and eliminate data imbalances and biases
- Create sparse data
- Collect large amounts of training data
- Reduce training time for AI processes
*Source: Gartner, “Maverick Research: Forget About Your Real Data – Synthetic Data Is the Future of AI,” Leinar Ramos, Jitendra Subramanyam, 24 June 2021.
AI research
AI research is being carried out across various fields such as Image classification, Object detection, and Pose estimation. AI models are becoming more advanced day by day, and synthetic data is also gaining popularity as the need for high-quality training data has emerged. Therefore, it will be possible to improve the accuracy of AI models that have already been developed and provide optimal synthetic data for AI models that have limitations in collecting real data, thereby providing more accurate and faster results to AI model developers.