How can PPC protect a proprietary Machine Learning model from being reverse-engineered when used by a third party?
Answer
By ensuring computation occurs within an enclave to protect executing code and weights.
When proprietary algorithms are executed within a Trusted Execution Environment (TEE) or secure enclave, the model's weights and architecture are protected from inspection, even by the third party hosting the computation.
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