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Code for computing on data
you do not own and cannot see

Syft + Grid provides secure and private Deep Learning in Python

Syft decouples private data from model training, using Federated Learning, Differential Privacy, and Encrypted Computation (like Multi-Party Computation (MPC) and Homomorphic Encryption (HE)) within the main Deep Learning frameworks like PyTorch and TensorFlow. Join the movement on Slack.

Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data without first putting it all in one (central) place.

The Syft ecosystem seeks to change this system, allowing you to write software which can compute over information you do not own on machines you do not have (total) control over. This not only includes servers in the cloud, but also personal desktops, laptops, mobile phones, websites, and edge devices. Wherever your data wants to live in your ownership, the Syft ecosystem exists to help keep it there while allowing it to be used privately for computation.

Stable Release

The current stable release is 0.6.0 which is available on:

• PyPI
• Docker Hub

For many use cases you can simply use:

$ pip install syft

If you are doing the Private AI Series or you are an external party developing against Syft and Grid please use the syft_0.6.0 branch.

Development Branch

This is the dev branch and to accommodate our need to experiment with new ideas and implementations we will be moving a few things around during the early stages of 0.7.0 beta. Currently the core syft library and code will remain fairly stable, while we do some much needed quality improvements and refactors to the grid codebase and its tooling for deployment and orchestration of nodes. During the process of development we will be moving examples from the /packages/syft/examples folder down to the /notebooks folder and ensuring they are working and tested with the latest dev code.

Mono Repo