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Google is making private AI practical with homomorphic encryption

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Re: Google is making private AI practical with homomorphic encryption

#3

Encryption or not, if it's on somebody else's server, it isn't yours. I don't believe Google has my best interest.

With Fully Homomorphic Encryption it's nobody elses.

The basic idea of of the project is to remove the need for trust.

Re: Google is making private AI practical with homomorphic encryption

#4
post #3

Encryption or not, if it's on somebody else's server, it isn't yours. I don't believe Google has my best interest.

With Fully Homomorphic Encryption it's nobody elses. The basic idea of of the project is to remove the need for trust.

It's google. They are good at engineering. Not at creating trust. After the bizillionth time they have broken trust, there is no need for benefit of the doubt.

Re: Google is making private AI practical with homomorphic encryption

#5

Encryption or not, if it's on somebody else's server, it isn't yours. I don't believe Google has my best interest.

It's FHE for "cryptographically-secure private AI inference" not for every other service where they snoop into your behavioral information.

Re: Google is making private AI practical with homomorphic encryption

#7
post #3

Encryption or not, if it's on somebody else's server, it isn't yours. I don't believe Google has my best interest.

With Fully Homomorphic Encryption it's nobody elses. The basic idea of of the project is to remove the need for trust.

To what end?

Re: Google is making private AI practical with homomorphic encryption

#8
post #6

Does this rely on the Trust Me Bro model, or is there some way for the client to verify that the provider actually isn't able to see your inputs? I want to read a whitepaper but all I can find is the tl;dw conference presentation

The linked project page [1] claims to be fully homomorphic. Assuming the claim holds (I haven't verified it), then there is provably no way for Google or anyone else to obtain any information from the encrypted data or computation performed on them.

FHE is traditionally horrifically slow, so it's hard to imagine running anything beyond toy models with it. They list some applications on the original article page, but (presumably) they must be dramatically stripped down in order to run within any reasonable time budget. This is not going to run anything like a Sol/Opus any time soon.

[1]: https://heir.dev/

Re: Google is making private AI practical with homomorphic encryption

#9
One flaw with FHE is that it guarantees only that you need the key to see the inputs or outputs of the computation, but not necessarily that the computation is the one you want. For example, the computation could be adversarial for certain inputs, or an adversary could insert their own computation first (or last).
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