[michwill]

That's a seriously cool thing to have in the toolbox!

Does it produce only encrypted output, or can it optionally produce unencrypted results also? Can it optionally use public data as an input?

Also I am guessing if it could be accelerated on GPUs. I worked with a guy who accelerated a standard FFT on CUDA 100..1000 times for scientific computations (and later NVidia copied his code, lol). I wonder if something similar can be done here

[hmottestad]

The point is to be able to give encrypted data to a third party and have them do operations on that data (ex. sum all the values) and give you an encrypted result back.

tldr. computations in the cloud with encrypted, private data

[michwill]

Yes, I understand. I was thinking about:

a) smart contracts controlling something within the encrypted data based on publicly available data;

b) encrypted key-value store where you traverse the tree structure based on encrypted query and encrypted tree buckets, but get a publicly available result about which bucket is next (similarly to how it was done in Arx paper using garbled circuits).

[mSparks43]

because, obviously, summing all the values is something you couldnt do yourself?

[proofofstake]

> This work leaves much room for improvement, however. For example, the throughput and latency can be significantly improved by using GPUs and FPGAs to accelerate the computation.

https://www.microsoft.com/en-us/research/wp-content/uploads/...

> 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.

[michwill]

Oh wow! I didn't ask for the last one, but this is insanely interesting also!