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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

#161

My master's thesis is on a topic in this field (Privacy Preserving ML) and from my understanding HE and other techniques have very high overheads(~10^3) on inference tasks and thus aren't very commercially viable.

The one that I'm waiting for is a women's period tracking app that uses FHE on the backend to be fully private.

Why on earth do you need a backend for this? The backend only exists because it leaks the data.

Re: Google is making private AI practical with homomorphic encryption

#162

Great, private AI, at the cost of >1000x the resource usage. Because apparently AI companies weren't already using quite enough energy to cook the planet. The most private AI is the one running on my own hardware, not in some giant data center.

> The most private AI is the one running on my own hardware, not in some giant data center. I want that too, but you gotta ask yourself the question how efficient that is compared to running it in a datacenter shared with everybody else.

It doesn't matter how efficient it is because the user base for that workflow is microscopic

Re: Google is making private AI practical with homomorphic encryption

#163
post #63

Earlier quoted context omitted.

To throw out some real and up-to-date numbers from [1] for FHE at "128-bit security level", to sort 8x 8-bit unsigned integers on the most ordinary of desktop PCs, wait 3 seconds for the result. Want to sort 32x 8-bit unsigned integers instead? Come back 34 seconds later for the result. update: also see [2] for some primitive unsigned 64-bit integer operation benchmarks with the TFHE-rs library (winner in the sorting…

This seems a fine tradeoff to me, depending on the context. There are datasets and operations on them where speed being sacrificed for privacy/security seems appropriate. Ideally, give me a dial, to ask for encrypted intelligence when I need it. Kind of like a private chat, but with deeper privacy protections.

Except that's for pathetically small datasets.

What real datasets exist where this would be a worthwhile trade off versus simply owning the hardware?

The numbers are so bad that underpowered local hardware would still beat it.

Re: Google is making private AI practical with homomorphic encryption

#167

Funny to read this, but google is currently number one anti-privacy big tech company. No other company makes it as difficult for its users using anonymization/privacy software to access their services

Pure hyperbole. I can’t even browse Facebook or Instagram anonymously for 15 seconds; I get a hard login popup that would require me to be identified in order to continue. Same with X. I’m also starting to see this with Reddit. Google is the tamest of the bunch; I still do all my Google searches while logged out. Occasionally I get a CAPTCHA but that’s about it.

Re: Google is making private AI practical with homomorphic encryption

#169
post #167

Funny to read this, but google is currently number one anti-privacy big tech company. No other company makes it as difficult for its users using anonymization/privacy software to access their services

Pure hyperbole. I can’t even browse Facebook or Instagram anonymously for 15 seconds; I get a hard login popup that would require me to be identified in order to continue. Same with X. I’m also starting to see this with Reddit. Google is the tamest of the bunch; I still do all my Google searches while logged out. Occasionally I get a CAPTCHA but that’s about it.

Google generally doesn't need you logged in unless you are doing heavy privacy cleaning.

Even in that case, they see data they are getting to be worthwhile enough for their other lines of business.

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