Andrew Carr

How to safely work with another company's data

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.
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Teaching large language models to zip their lips

Gretel introduces Reinforcement Learning from Privacy Feedback (RLPF), a novel approach to reduce the likelihood of a language model leaking private information.
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Bringing AI-generated images to enterprise use cases

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!
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Copyright Ā© 2022 Gretel.ai

Diffusion models for document synthesis

Explore state-of-the-art image synthetics for business documents using diffusion models.
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Downstream ML classification with Gretel ACTGAN and PyCaret

Learn about downstream machine learning tasks and synthetic data with Gretelā€™s new ACTGAN model and the PyCaret library
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Synthetic Image Models for Smart Agriculture

Learn how synthetic image models can address data drift and improve a computer vision model's accuracy in unexpected conditions.
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Evaluating Data Sampling Methods with a Synthetic Quality Score

An evaluation of the effect of sampling procedures on the quality of synthetic tabular data using Gretel.ai's Synthetic Quality Score (SQS).
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Copyright Ā© 2022 Gretel.ai

What is Model Soup?

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