awesome-vector-database
paranoid_crypto
awesome-vector-database | paranoid_crypto | |
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1 | 6 | |
141 | 783 | |
- | 0.0% | |
9.0 | 5.7 | |
4 days ago | about 1 month ago | |
Python | ||
Creative Commons Zero v1.0 Universal | Apache License 2.0 |
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awesome-vector-database
paranoid_crypto
- Scientists Destroy Illusion That Coin Toss Flips Are 50–50
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Show HN: SimSIMD vs. SciPy: How AVX-512 and SVE make SIMD cleaner and ML faster
numpy-feedstock: https://github.com/conda-forge/numpy-feedstock/blob/main/rec...
scipy-feedstock: https://github.com/conda-forge/scipy-feedstock/blob/main/rec...
pysimdjson-feedstock: https://github.com/conda-forge/pysimdjson-feedstock/blob/mai...
simdjson-feedstock: https://github.com/conda-forge/simdjson-feedstock/blob/main/...
mkl_random-feedstock: https://github.com/conda-forge/mkl_random-feedstock https://github.com/google/paranoid_crypto/tree/main/paranoid... :
> NumPy-based implementation of random number generation sampling using Intel (R) Math Kernel Library, mirroring numpy.random, but exposing all choices of sampling algorithms available in MKL
blas: https://github.com/conda-forge/blas-feedstock/blob/main/reci...
xtensor-blas-feedstock: https://github.com/conda-forge/xtensor-blas-feedstock
xtensor-fftw (FFT with xtensor (c++)) could probably be AVX-512 and SVE -optimized as well?
- Paranoid project by Google Security Team checks for cryptography weaknesses
- Paranoid project checks for well known weaknesses on cryptographic artifacts such as public keys, digital signatures and general pseudorandom numbers.
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Paranoid project checks for well known weaknesses on cryptographic artifacts such as public keys, digital signatures and general pseudorandom numbers
I was trying to figure out from the docs on how you provide the input keys to this library, but the docs are not yet written. Then I looked at some example code, and in there they put the keys into the source code itself. Looks like this library is still in its early phases.