Synthetic data is newly created data that mimics the characteristics of original data, providing an important alternative that replicates the traits of existing datasets while solving issues such as the protection of personal information. The advancement of artificial intelligence and machine learning has enabled the creation of realistic and diverse new data. This contributes to […]
This article is about collecting data needed to introduce AI models.
To build a good AI model, you need good data. Good data is hard to come by, and Cubig can solve that problem.
Today, many industries are striving to integrate AI into their systems and technologies. Business competitiveness increasingly hinges on the ability to predict consumer demand and provide personalized services. A well-trained AI model can achieve this with speed and accuracy, so making AI investment is becoming a key focus for business advancement. However, implementing AI is […]
Leading the way in data innovation, CUBIG utilizes differential privacy to craft synthetic datasets with up to 99% statistical value compared to the original data. This unparalleled statistical value significantly enhances AI engine training performance, resulting in outstanding outcomes. Our sythetic datasets maintain statistica value nearly indistinguishable from original data, enabling customers to effectively train […]
In the ever-evolving landscape of artificial intelligence (AI) and data utilization, the need for robust privacy solution has become increasingly vital. Amidst concerns over legal and ethical ramifications, the challenge lies in striking a balance between leveraging valuable data and protecting individual privacy. This blog explores the innovative realm of differential privacy, focusing on the […]