[doctorpangloss]

The technology for all this progress was a huge discovery in 2009. But what if it is a dead end, that nothing originating from that discovery will ever be practical?

Like wouldn't it be preposterous if someone said, "Here Craig Gentry, take $1 billion to run enough computers for the current FHE schemes. What is the snazziest demo you can run?"

[UncleMeat]

FHE isn't the only option. Somewhat Homomorphic Encryption can be fast and stupendously valuable for a lot of statistical operations where you can figure out how to compute your function off only a small number of multiplications.

[rhindi]

Some of the newer schemes are much faster. The recent progress feels like deep learning in 2010, right before everyone realized it worked

[poz]

> The recent progress feels like deep learning in 2010, right before everyone realized it worked

Does it work, though?

[throwawaywego]

https://www.microsoft.com/en-us/research/publication/crypton... (2016)

> We demonstrate CryptoNets on the MNIST optical character recognition tasks. CryptoNets achieve 99% accuracy and can make more than 51000 predictions per hour on a single PC. Therefore, they allow high throughput, accurate, and private predictions.

[rhindi]

It’s starting to, yes, in particular for machine learning. There is a yearly competition called iDash where people show the performances of their homomorphic schemes. This year should be very interesting

[rhacker]

If they keep that name it will be a dead end.

[rolltiide]

That’s life

It will join the graveyard of technologies was that rhetorical?