Building Safe Artificial Intelligence

OpenMined is an open-source community focused on researching, developing, and elevating tools for secure, privacy-preserving, value-aligned artificial intelligence.

V 0.3.0 - “Lithium”

[open-minercurl -Ls git.io/openmined | docker-compose -f - up

Vision & Mission

It is commonly believed that individuals must provide a copy of their personal information in order for AI to train or predict over it. This belief creates a tension between developers and consumers. Developers want the ability to create innovative products and services, while consumers want to avoid sending developers a copy of their data.

With OpenMined, an AI can be trained in environments that are not secure on data it never has access to.

The mission of the OpenMined community is to make Private & Secure Deep Learning technology accessible to consumers, who supply data, and machine learning practitioners, who train models on that data. Given recent developments in cryptography, AI-based products and services do not need a copy of a dataset in order to create value from it.

Our Blueprint for Safe, Narrow AI

The OpenMined ecosystem incorporates a number of technologies including federated learning, differential privacy, multi-party computation, homomorphic encryption, peer-to-peer networking, and open marketplace tools such as blockchain. Click on the sections below to learn more about each step in the process.

Project Timeline

  • Project Launched

    July 2017

  • Hydrogen Release

    September 2017

  • Helium Release

    February 2018

  • Lithium Release

    March 2018

Grid

Grid

A Peer-to-Peer On-Demand Compute Grid

UnityWorker

UnityWorker

The OpenMined Unity Application

PySyft

PySyft

A Library for Private, Secure Deep Learning

syft.js

syft.js

Private Deep Learning in JavaScript

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