Worth reading · 12 November 2025

Differentially private machine learning at scale with JAX-Privacy

A toolkit for training and auditing differentially private models in JAX, with the gradient clipping and noise machinery built in, so large models can be trained with a mathematical privacy guarantee.

Read the full story