Explore how the UK’s new £100M National Data Library could transform research, public services, and AI. Highlights from OpenMined and UCL’s event on unlocking public sector data through privacy-first technologies like SyftBox and OpenSAFELY.| OpenMined
Access to non-public data is blocked by privacy, security, regulation, and intellectual property concerns.Most commercially available solutions wall off data and take a significant cut of revenue that should belong to data owners.We are solving Attribution-Based Control to fix this problem.| OpenMined
In Part 2 of our Federated Learning series, learn how to submit a machine learning job to real, remote datasites using the SyftBox network—without accessing private data. A practical guide for Data Scientists moving from local simulation to distributed networks.| OpenMined
Join OpenMined on Slack to connect with a global community working on privacy, AI, and secure data collaboration. Get involved, ask questions, and contribute.| OpenMined
Kickstart your federated learning project without the DevOps headache. Syft_flwr simplifies deployment, networking, and security—so you can start training your model across organizations in days, not weeks.| OpenMined
Learn how hospitals used federated learning to collaboratively train a diabetes prediction model without sharing sensitive patient data. Includes code walkthrough.| OpenMined
Welcome to our guide! In this tutorial, we are going to cover the following topics: If you’re already familiar with Differential Privacy, you can dive straight into the details here! Background: What is differential privacy? Imagine you have a dataset D, which is a list of people’s ages. Now, let’s say you want to check […]| OpenMined
Andrew Trask*, Aziz Berkay Yesilyurt*, Bennett Farkas*, Callis Ezenwaka*, Carmen Popa*, Dave Buckley*, Eelco van der Wel*, Francesco Mosconi‡, Grace Han‡, Ionesio Junior*, Irina Bejan*, Ishan Mishra§, Khoa Nguyen*, Koen van der Veen*, Kyoko Eng*, Lacey Strahm*, Logan Graham‡, Madhava Jay*, Matei Simtinica*, Osam Kyemenu-Sarsah*, Peter Smith*, Rasswanth S*, Ronnie Falcon*, Sameer Wagh*, Sandeep Mandala‡, […]| OpenMined
The Christchurch Call Initiative on Algorithmic Outcomes (CCIAO) released their technical report demonstrating how they used privacy-enhancing technologies to enable independent external researchers to study social media recommendation algorithms while protecting user privacy and platform security. The researchers involved in the project were able to conduct audits of recommendation systems at LinkedIn and Dailymotion using […]| OpenMined