HackerTrans
トップ新着トレンドコメント過去質問紹介求人

rhindi

no profile record

投稿

A solution to A16Z Nakamoto challenge on "Compliant Programmable Privacy"

zama.ai
43 ポイント·投稿者 rhindi·3 年前·3 コメント

FhEVM whitepaper (homomorphic encryption for blockchain) [pdf]

github.com
3 ポイント·投稿者 rhindi·3 年前·0 コメント

コメント

rhindi
·2 年前·議論
They use BFV, which is an FHE scheme allowing a limited number of fast additions and multiplications (enough for their use case).

Zama uses TFHE, which allows any operation (eg comparisons) with unlimited depth.

So if you only need add/mul, BFV, BGV and CKKS are good options. For anything else, you better use TFHE
rhindi
·2 年前·議論
There are some non-ML based approaches for ultra low field MRI that are starting to work: https://drive.google.com/file/d/1m7K1W--UOUecDPlm7KqFYzfkoew... . You can still add AI on top of course, but at least you get a better signal to noise ratio to start with!
rhindi
·3 年前·議論
FHE in general is efficient enough for many applications now. You can see some benchmarks here: https://docs.zama.ai/tfhe-rs/getting-started/benchmarks