Google is making private AI practical with homomorphic encryption
u1hcw9nx · 476 points · 277 comments · yesterday · Open original
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SAsabretooth1405yesterday
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.
SNsnovv_crash12 hours ago
So much inefficiency just to run it on someone else's untrusted hardware. Private AI is already possible today with local open-weight models running on hardware you control.
Homomorphic encryption is cool technology, but I'm really not sure what problem it solves.
NEnever_inline17 hours ago
I think you folks are reading too much into it. I think the people working on FHE need to publish an AI-oriented pitch to retain funding from AI-pilled execs. Must be the same case with the golang post few days ago.
MEmeindnochyesterday
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.
CICider9986yesterday
This is the same Google that doesn't have e2ee on their password manager by default. Like WTF, it's a password manager.
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5 preview comments · loading full threadLog in to h4cker, then connect Hacker News to publish comments.
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.
So much inefficiency just to run it on someone else's untrusted hardware. Private AI is already possible today with local open-weight models running on hardware you control. Homomorphic encryption is cool technology, but I'm really not sure what problem it solves.
I think you folks are reading too much into it. I think the people working on FHE need to publish an AI-oriented pitch to retain funding from AI-pilled execs. Must be the same case with the golang post few days ago.
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.
This is the same Google that doesn't have e2ee on their password manager by default. Like WTF, it's a password manager.