Measure the utility and quality of GPT-generated text using Gretel’s new text report

Gretel has introduced a Synthetic Text Data Quality Report that measures semantic and structural similarity between AI-generated text and training text in 50 languages. The report includes the Text SQS, which estimates how well the generated synthetic data maintains the same semantic and structural properties as the original dataset. This score can be viewed as a utility or confidence score for drawing scientific conclusions from the synthetic dataset. The report compares Amazon product reviews with synthetic text from Gretel's GPT-x model. It provides recommendations based on the Text SQS, helping users understand its implications and how to improve it if necessary.

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