Andrew Carr

Gretel introduces Reinforcement Learning from Privacy Feedback (RLPF), a novel approach to reduce the likelihood of a language model leaking private information.

An evaluation of the effect of sampling procedures on the quality of synthetic tabular data using Gretel.ai's Synthetic Quality Score (SQS).

A brief exploration of model soup, the new ensembling technique that takes the average weights of multiple models to improve overall performance.

Data sharing is central to modern business but entails risks. Synthetic data can enable data sharing while reducing the risk of privacy-compromising linkage attacks.

Explore state-of-the-art image synthetics for business documents using diffusion models.

Learn about downstream machine learning tasks and synthetic data with Gretel’s new ACTGAN model and the PyCaret library

Learn how synthetic image models can address data drift and improve a computer vision model's accuracy in unexpected conditions.

Gretel's new image synthetics enable you to generate high-quality images at scale. Get started today with our free public preview and let us know what you think!