Top
Best
New

Posted by u1hcw9nx 2 hours ago

Google is making private AI practical with homomorphic encryption(blog.google)
68 points | 51 comments
sabretooth1405 56 minutes ago|
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.
clayhacks 1 minute ago||
Do you think that’s like a fundamental limit or something that will improve with time and new algorithms?
jerf 13 minutes ago|||
The article conspicuously fails to go into much detail about that. I poked around with an AI a bit (to rapidly cover all the linked pages) and it seems the best numbers we can get are from this arxiv paper: https://arxiv.org/html/2506.18150v4 Which says:

"We evaluate HE-LRM on UCI (health prediction) and Criteo (click prediction), achieving inference latencies of 24 seconds on UCI and 228 to 489 seconds, respectively, on a single-threaded CPU."

There don't seem to be any direct comparisons available, probably because nobody else has any reason to limit themselves to one single-threaded CPU with normal techniques, but for reference the AI seems to expect that normal times for conventional setups are in the milliseconds range, fairly comfortably, even on CPU. I didn't find a clean primary source to link to for this claim, but clicking through various things that don't cleanly state the situation it did seem plausible. So we seem to still be in the range of single-digit orders of magnitude slower, possibly as much as 5 or 6, which is to say, we're still talking the range where we need to take the log of the difference to get sensible numbers, we're not using percentages.

(To run it yourself, I basically just fed the URL from the HN link, mentioned that FHE is known to be slow, and asked if anything linked in the blog post gave concrete times.)

u1hcw9nx 11 minutes ago|||
That's the reason for HEIR like optimization and parameter selection.

It narrows the 10^3 - 10^6 penalty to 10x - 100x.

abetusk 15 minutes ago|||
1000x slowdown is bad but not a complete deal breaker. Do you have a sense of what a reasonable achievable factor is? Do you have sense for how long before we get to that achievable factor?
dietr1ch 18 minutes ago||
Exactly my concern, and worse overhead that what I recalled.

Cost-wise the only viable private compute is local compute. It's more expensive than cloud, but true private compute in the cloud is definitely pricier.

Cider9986 51 minutes ago||
This is the same Google that doesn't have e2ee on their password manager by default. Like WTF, it's a password manager.
bitpush 16 minutes ago||
F. Scott Fitzgerald's test of top-tier intelligence -

> Holding two opposing views in the mind means accepting two contradictory ideas at the same time without needing to pick one side or rush to a simple answer

I continue to use Apple products because they are top class even though everytime I think of Tim Cook in the Oval Office presenting the gold plaque to the current president, it makes me wanna puke. World isnt black or white.

amazingamazing 37 minutes ago||
If you think about it for a moment you will realize the average user does not want that.
rexpop 21 minutes ago||
I suspect that your one moment of thought follows many years of contemplation. Maybe you can fill us in on some of that background.
giovannibonetti 19 minutes ago|||
E2E encryption means that if the user loses the keys, there is no way to recover that even if they contact support and prove the data belongs to them.
amazingamazing 21 minutes ago|||
How do you make e2e password management work on multiple devices as convenient as not? You cannot.

Most people who use Google trust them. And if you do not trust them then why are you using their password manager? You see? Hence why they do not bother.

Of course one might read this and say, multi device e2ee is possible! Sure, but can you allow for recovery when people inevitably lose their recovery codes at scale? If you really care about this it is not necessary to go with Google.

I stand by my original comment:

The average user does not want it.

bmenrigh 32 minutes ago||
Has FHE really progressed so far that it's now so efficient that doing computation on an encrypted prompt is feasible? I thought even basic operations like FHE addition were still thousands of times more complex. The only mention in the article I see is:

> But while homomorphic encryption has a nontrivial cost overhead, it shifts the capability/privacy trade-off to a question of cost. And the cost of homomorphic encryption is rapidly decreasing.

Which doesn't spell out exactly hon "nontrivial" the cost overhead still is.

traceroute66 18 minutes ago||
Quoted from the blog post:

> user-data can be protected from data breaches, but then the service provider cannot provide features that depend on the data, such as spam or virus detection

I think they forgot "or advertising" at the end.

I don't trust Google. I would much prefer to use on-prem or - at most - one of the secure-enclave providers like Tinfoil[1] or Private Mode[2]

[1] https://tinfoil.sh/ [2] https://www.privatemode.ai/

flambo 10 minutes ago|
Secure Enclaves are broken all the time though [1]. They’re also not secure against attacks from a quantum computer (including store now decrypt later attacks). At least with symmetric FHE, anything that happens after encryption requires zero trust.

[1] https://sgx.fail/

lsb 27 minutes ago||
Google is making private AI practical with Gemma4 something that you can run without an Internet connection.

All of the proofs of privacy rely on us getting the math right. All of the privacy from unplugging your internet cable is there by default.

NyxWulf 25 minutes ago||
Maybe I'm not understanding this, but how is it that you can know enough about the data to process it without undermining the fundamental concept of encryption? Isn't encrypted data supposed to be just random noise without the key? The more you know about the underlying data the easier it gets to decrypt? Does this mean someone can just steal your encrypted data and use that to steal your identity without even needing to decrypt it anymore?
sheesdev 23 minutes ago||
I've published two papers on using HE for ML and it's nice, but also alarming, to see big players like Google and Microsoft making decent tools for performing HE. Although the technology is still much farther out from being commercially viable, it does pose an interesting problem about how these data aggregation companies will utilise a tech that is inherently private.
tolugenius 19 minutes ago|
I guess I'm curious from your perspective what and why makes the tech from being commercially viable, and the concerns of big players adopting this (which was always going to happen I imagine, but when shapes a lot of the future of the field).
Deukhoofd 1 hour ago||
It sounds neat, but I do wonder how viable this is commercially. How high do we rate the chances that governments around the world will step in before another kind of E2E is rolled out.
mohamedkoubaa 17 minutes ago||
Anything to keep people from running local models
FloatArtifact 2 hours ago|
Encryption or not, if it's on somebody else's server, it isn't yours. I don't believe Google has my best interest.
kccqzy 53 minutes ago||
This kind of attitude is really disrespectful of decades of progress in cryptography. Without even considering homomorphic encryption, classic encryption is specifically designed to make intermediate nodes such as ISP dumb pipes that do not know the contents of communication. The ISP can store your communications on their server however they want.

If you don’t agree with this model, I’m afraid modern cryptography doesn’t have anything to offer.

jewel 34 minutes ago||
Even if your files are properly encrypted, if you keep them on, say, Google Drive, then you might lose access to them if your account gets inadvertently blocked.

I think GP is trying to say something along those lines. Not that encryption isn't trustworthy, but that even with homomorphic encryption you still give up autonomy.

u1hcw9nx 2 hours ago|||
With Fully Homomorphic Encryption it's nobody elses.

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

unsungNovelty 1 hour ago|||
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.
Plont 58 minutes ago|||
Yeah. Google is an ad business. Their entire motive for getting invested in AI is ad revenue. We're supposed to believe they just... won't turn on the money fountain? After going into the red for their data center investments? Hell nah.

I'd expect this to be something like the Google Ad ID: technically separated from what Google considers personal information, but trivially easy to tie back to an individual person and to other information about that person.

They're continually breaking trust by illegally scraping up the internet to feed to their plagiarism machine, which they are now asking us to trust with more data. It's not a compelling arguement.

throwaway27448 59 minutes ago||||
There's more to life than branding.
tonyhart7 58 minutes ago|||
so what's the option ??? Meta ?? xAi ?? or OpenAI ???
unsungNovelty 50 minutes ago|||
Why should there by any reason to look at the above ones? We are talking about this B2C company which effects a lot of our lives. The discussion isn't about that or this. The discussion is about JUST this specific company.
thih9 1 hour ago|||
To what end?
yjftsjthsd-h 16 minutes ago|||
It can give you confidentiality without availability. Not sure about integrity? Anyways, still useful.
krunck 1 hour ago||
It's FHE for "cryptographically-secure private AI inference" not for every other service where they snoop into your behavioral information.
More comments...