Announcing Concrete Numpy v0.5

Concrete Numpy, an open-source toolset designed to facilitate the use of fully homomorphic encryption (FHE) for data scientists, has released a new version, v0.5, which introduces several enhancements and changes. This version supports additional numpy operators, including sum, concatenate, 2D convolution, matmul, and transpose, while also offering increased bit precision from 7 bits to 8 bits. An important shift is the removal of some higher-level machine learning features, which are now part of a new package called concrete-ml. The update also includes enhanced support for loop parallelism and a refined workflow featuring explicit encrypt, decrypt, and run functionalities, replacing the previous run command with a new encrypt_run_decrypt process. Built on the Concrete library's foundation of efficiency, usability, and simplicity, this version aims to improve the experience of training and deploying machine learning models using FHE, with a separate API for key generation, encryption, decryption, and execution.

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