Announcing Portuguese PySyft Tutorial Translations

Today we are pleased to announce the translation of our PySyft tutorials into Portuguese!

Introduction to Federated Learning and Privacy Preservation using PySyft and PyTorch

Federated Learning and Additive Secret Sharing using the PySyft framework

OpenMined Featured Contributor: January 2020

Interview with Karl Higley, OpenMined's Featured Contributor for January 2020!

Split Neural Networks on PySyft and PyTorch

Summary: In this blog we are going to provide an introduction into a new decentralised learning methodology called, ‘Split Neural Networks’.

Announcing Chinese Tutorial Translations

Happy Chinese New Year!  As we welcome in the year of the rat, we are excited to announce that our tutorials have been translated into Chi

OpenMined Featured Contributor: December 2019

Interview with Patrick Cason, OpenMined's Featured Contributor for December 2019!

Meet OpenMined's new PyTorch-OpenMined Fellows

We’re very excited to announce the recipients of the latest round of open-source software development grants in the OpenMined community, gen

OpenMined Featured Contributor: November 2019

Interview with Yemissi Kifouly, OpenMined's Featured Contributor for November 2019!

Announcing the OpenMined-PyTorch Federated Learning Fellowships

We’re very excited to announce the next round of grants sponsored by the PyTorch team! This grant will focus on developing “worker libraries”, allowing PySyft code to be executed in other environments like a mobile phone or web browser.

Announcing the OpenMined-PyTorch Development Challenges

We’re very excited to announce the next round of open-source software development grants in the OpenMined community, generously sponsored by

Announcing the OpenMined-PyTorch for Crypten Integration Fellowships

We’re very excited to announce the next round of open-source software development grants in the OpenMined community, generously sponsored by

OpenMined Featured Contributor: October 2019

Interview with Daniele Gadler, OpenMined's Featured Contributor for October 2019!

Introducing PySyft TensorFlow

Support for TensorFlow in PySyft!

Asynchronous Federated Learning in PySyft

In this post, we provide a showcase of applying federated learning using PySyft. PySyft is an open source python library for secure and priv

OpenMined Featured Contributor: September 2019

Interview with Marianne Monteiro, OpenMined's Featured Contributor for September 2019!

OpenMined Featured Contributor: August 2019

Interview with Nick Duddy, OpenMined's Featured Contributor for August 2019!

Privacy-Preserving AI in Medical Imaging: Federated Learning, Differential Privacy, and Encrypted Computation

In medical imaging, necessary privacy concerns limit us from fully maximizing the benefits of AI in our research. These modern privacy techniques could allow us to train our models on encrypted data from multiple institutions, hospitals, and clinics without sharing the patient data.

OpenMined Featured Contributor: July 2019

Interview with Théo Ryffel, OpenMined's Featured Contributor for July 2019!

Encrypted Training with PyTorch + PySyft

Encrypted Training of Deep Learning models with PyTorch + PySyft on MNIST

RAAIS Grant Announcement

Announcing the very first round of RAAIS OpenMined Scholarships, sponsored by very generous support from The RAAIS Foundation

Federated Learning of a Recurrent Neural Network on Raspberry PIs

In this article, you are going to learn how to setup PySyft on a Raspberry PI and how to train a Recurrent Neural Network in a federated way.

Encrypted Deep Learning Classification with PyTorch & PySyft

Encrypted Deep Learning Classification with PyTorch & PySyft in < 33ms on MNIST

Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft

Deep Learning -> Federated Learning in 10 Lines of PyTorch + PySyft

Training a CNN using SPDZ

An implementation of Convolutional Neural Networks (CNNs) using secure Multi-Party Computation (MPC).