Data Science without seeing the data - A homomorphic encryption-based system
Intuit is investing in adopting the new techniques of Fully Homomorphic Encryption, which are just now moving from the theoretical and purely academic sphere into the realm of practitioners, a transition that will take many years. FHE means arithmetic operations can be calculated on the encrypted data, which opens up new possibilities for privacy-safe machine learning. We will be showing some of the progress we have made in solving the many technical problems that still plague FHE, including performance, support for different types of models and AI techniques, and the related system design.
Tzvika Barenholtz works at Intuit’s Data Science org and Intuit Futures, leading a team dedicated to advanced machine learning out Intuit’s office in Israel. Before joining Intuit he lead product teams at Facebook, Google and EMC.
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