Concrete ML

Previously, we blipped the Homomorphic Encryption technique that allows computations to be performed directly on encrypted data. Concrete ML is one such open-source tool that allows for privacy-preserving machine learning. Built on top of Concrete, it simplifies the use of fully homomorphic encryption (FHE) for data scientists to help them automatically turn machine learning models into their homomorphic equivalent. Concrete ML's built-in models have APIs that are almost identical to their scikit-learn counterparts. You can also convert PyTorch networks to FHE with Concrete ML's conversion APIs. Note, however, that FHE with Concrete ML could be slow without tuned hardware.