Parfait
Welcome to Google Parfait! The goal of this organization is to host repositories for defining and executing machine learning and analytics computations and workflows that enable strong privacy claims consistent with users’ privacy expectations, including:
- Libraries and frameworks used in research simulation
- Libraries and system components used in Google's production federated compute infrastructure
- Reference architectures for production systems
Our repositories support privacy-preserving technologies, including:
- Federated Learning
- Federated Analytics
- Differential Privacy
- TEE-enabled privacy architectures
- Personalization & Local Computation
- Privacy preserving aggregation, including approaches based on differential private and secure multiparty computation
- Private Information Retrieval (PIR)
Our technology and research has been used widely across Google, deployed by other tech companies, and referenced by many others. Some examples include analytics for Live Translate in Android’s Protected Compute Core, and Gboard’s Next Word Prediction and Out-of-Vocabulary discovery.
For those interested in production cross-silo or cross-device federated learning architectures that run on Google Cloud, please refer to the architecture in the Google Cloud Architecture center and their associated GitHub repository.
We are a team of researchers and engineers at Google that develop foundational technologies that enable strong privacy guarantees for AI and analytics systems, and maintain these repositories, which are used in production across various Google platforms. We believe that strong privacy guarantees are essential to the future of tech, and are committed to driving innovation in this space. We encourage engineers and researchers to actively engage with these repositories and use the code with confidence to build private-by-default systems and publish papers.
Want to learn more about us or get in contact? Visit http://federated.withgoogle.com.
Popular repositories Loading
-
tensorflow-federated tensorflow-federated Public
An open-source framework for machine learning and other computations on decentralized data.
-
federated-compute federated-compute Public
Libraries for executing federated programs and computations.
-
confidential-federated-compute confidential-federated-compute Public
TEE-hosted binaries for verifiable server-side computation.
-
dataset_grouper dataset_grouper Public
Libraries for efficient and scalable group-structured dataset pipelines.
-
-
Repositories
- federated-language-jax Public
- federated-language Public
A framework for implementing federated algorithms and computations on privacy-sensitive data.
- tensorflow-federated Public
An open-source framework for machine learning and other computations on decentralized data.
- bazel-central-registry Public Forked from bazelbuild/bazel-central-registry
The central registry of Bazel modules for the Bzlmod external dependency system.
- cvm-side-channel-analysis Public
People
This organization has no public members. You must be a member to see who’s a part of this organization.
Top languages
Loading…
Most used topics
Loading…