Generative AI Services

Generative AI models are modern machine learning models. They build a set of insights by parsing through the data they are fed, and thus the quality directly impacts their output quality.

Errors in your real data will result in those errors being propagated and repeated in the synthetic data produced by generative AI models.

The GIGO result in generative AI underlines the demand for systematic data management processes. Ensuring great quality, clean, and accurate data is most important. The GIGO principle summarizes the process that the quality of output data is right away connected with the quality of input data.

The GIGO formula highlights that if the input data is imperfect, the output of AI will imitate those, possibly resulting in inaccurate results.

Generative AI is converting the view of data quality and providing modern solutions to beat the garbage in and garbage out problem. Let’s see how:

Data validation: The goal of this AI-enabled validation process is to ensure valid and high-quality data enters your system.

Data preprocessing: Generative AI can correct irregularities in the input data.

Data synthesis for quality improvement: Generate AI can generate good-quality synthetic data with improved quality. The use of good-quality synthetic data minimizes the dependence on possible inaccurate real-world data, thereby preventing the occurrence of garbage in the system.