Collecting Sufficient Amount of Data: How to Improve Model Performance (2)
This article is about collecting data needed to introduce AI models.
This article is about collecting data needed to introduce AI models.
In the rapidly advancing landscape of artificial intelligence (AI), securing quality training data has become a paramount concern. The axiom “To build a good AI model, you need good training data” holds truer ever. The results produced by AI models are heavily influenced by the quality and characteristics of the training data. One significant challenge […]
To build a good AI model, you need good data. Good data is hard to come by, and Cubig can solve that problem.
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 […]