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006 Running Numpy programs homomorphically w/ Rand Hindi, Ayoub Benaissa, and Samuel Tap
Автор: FHE_org
Загружено: 2021-10-06
Просмотров: 1798
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About the video:
Making FHE mainstream requires tools that make it easy to use for non-cryptographers. Being able to take regular Numpy programs and run them on encrypted data would enable data scientists to integrate FHE into their models, however complex they might be.
In this talk, the team at Zama will introduce a homomorphic numpy compiler, demonstrate how it can be used to run a recurrent neural network on encrypted data, and share their thoughts on homomorphic compiling.
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