Duet & OpenGrid - Infrastructure for Easy Remote Data Science

Learn from data, without sacrificing privacy.

Companies have too much access to our data, while researchers often have too little. Which problem is OpenMined trying to solve?

Companies have too much access to our data, while researchers often have too little. Which problem is OpenMined trying to solve? Both.

A list of Companies, Startups, and Projects in the Privacy Space

The data protection market is estimated to reach $119 billion by 2022 — this projection highlights the pivotal role the field has in societ

GPT-3 is incredible. Privacy will make it truly realizable.

There has been an extraordinary amount of hype attributed to Open AI’s recent GPT-3 API launch —it is very well-deserved. GPT-3 is a rema

Privacy-Preserving Data Science, Explained

In this blog series, we’ll explain common topics in privacy-preserving data science, from a single sentence to code examples. We hope these posts serve as a useful resource for you to figure out the best techniques for your organization.

Genetic data privacy in the dawn of big data forensics

“You would see hundreds and hundreds of unsolved crimes solved overnight,” Detective Michael Fields of the Orlando Police Department, from

PyGrid: A Peer-to-Peer Platform for Private Data Science and Federated Learning

What if you could train on all of the world’s data, without that data leaving the device, and while keeping that data private? PyGrid is a peer-to-peer platform for private data science and federated learning.

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.