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EGregyesterday at 4:56 PM1 replyview on HN

I heard that homomorphic encryption can actually preserve all the operations in neural networks, since they are differentiable. Is this true? What is the slowdown in practice?


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crackalamooyesterday at 5:22 PM

This is true in principle, yes. In practice, the way this usually works is by converting inputs to bits and bytes, and then computing the result as a digital circuit (AND, OR, XOR).

Doing this encrypted is very slow: without hardware acceleration or special tricks, running the circuit is 1 million times slower than unencrypted, or about 1ms for a single gate. (https://www.jeremykun.com/2024/05/04/fhe-overview/)

When you think about all the individual logic gates involved in just a matrix multiplication, and scale it up to a diffusion model or large transformer, it gets infeasible very quickly.

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