They have a bit more info on their announcement blog post[0] > Belfort today released the "so far" CIFAR demo, an encrypted implementation of ResNet-20, a popular model for image classification. It outperforms recent SOTA by 3x with a total latency of less than 200ms Not many details on how they've done this, so I'm a bit skeptical. Fast HE is a holy grail. > Belfort's image classification is built on top of its upco…
Homomorphically encrypted CIFAR-10 inference in 200ms
21–30 of 45 posts
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#22I think they only trained on dogs with floppy ears, because it is very confident the German Shepherd is a cat.
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#23I think they only trained on dogs with floppy ears, because it is very confident the German Shepherd is a cat.
did they remove a German Shepherd from the sample images since your comment? I cannot see a German Shepard. Only a black dog with floppy ears.
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#24Earlier quoted context omitted.
did they remove a German Shepherd from the sample images since your comment? I cannot see a German Shepard. Only a black dog with floppy ears.
Nothing is removed. I am not good with dog breeds, but with "German Shepherd", they probably meant the image #27; the black dog. It is indeed classified as a cat :(
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#25Earlier quoted context omitted.
I think calculator is not part of the labels in cifar-10. Pretty normal as it has ‘only’ 90% accuracy. Things could improve quickly though
That 90% only measures images already known to be one of CIFAR-10’s ten classes. There is no “none of the above,” so even a perfect benchmark score would still force a calculator into one of those labels.
"The 10 different classes represent airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks."
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#26Looked at the network logs and the JS, did some testing, there's a caveat here. For an encryption demo you might expect your secrets to be generated locally, they do the compute on something they can't read, you compare their results to your original plaintext; (imo at least) the point would be that it isn't physically possible for them to cheat. Here, you literally download client_secret.bin from their server, so th…
Thanks for taking the time and test it. Key management is a critical part of the story, as j2kun has pointed out before. In this demo, we're intentionally caching the same key material for every visitor so we can showcase the actual FHE computation without making everyone wait through client-side key generation and upload. Even as a one-time cost, having each user generate their own keys in the browser and transfer t…
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#27Earlier quoted context omitted.
Thanks for taking the time and test it. Key management is a critical part of the story, as j2kun has pointed out before. In this demo, we're intentionally caching the same key material for every visitor so we can showcase the actual FHE computation without making everyone wait through client-side key generation and upload. Even as a one-time cost, having each user generate their own keys in the browser and transfer t…
You could add a toggle, so that if someone's happy to wait for the key setup, they can try the full end-to-end process
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#28Earlier quoted context omitted.
> gaining any sort of insight The server providing the FHE-based service does not gain any sort of insight. This is a key point: only the client can see the output of the computation.
Interesting. I have some homework to do then. Do we have to close our eyes and look away for it to be true or does it really not gain any insight? Where can I find out more about how this could be possible?
Re: Homomorphically encrypted CIFAR-10 inference in 200ms
#29Earlier quoted context omitted.
> gaining any sort of insight The server providing the FHE-based service does not gain any sort of insight. This is a key point: only the client can see the output of the computation.
Interesting. I have some homework to do then. Do we have to close our eyes and look away for it to be true or does it really not gain any insight? Where can I find out more about how this could be possible?