Published : Apr 03, 2024
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar
Understand more
Apr 2024
Assess
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.
