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1.Blogs

Akraino Edge Stack Use Cases: WeBank’s End User Story

By LF Edge February 18, 2020

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3. Original Content

WeBank has deployed The AI Edge: Federated ML application at edge blueprint. With this blueprint, researchers and developers could use the data stored in different entities like hospitals and banks to build a model without actually transfer data. Moreover, our platform can help the engineer use more data and features to train their model so that their model can have a better performance in real tasks. And the Federated Ml Application at Edge blueprint has been deployed in a warehouse monitoring task and helps the whole team get a good performance.

To make the Federated ML Application easier to use, our team build a tool called FATE. FATE (Federated AI Technology Enabler) is an open-source project initiated by Webank’s AI Department to provide a secure computing framework to support the federated AI ecosystem. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). It supports federated learning architectures and secure computation of various machine learning algorithms, including logistic regression, tree-based algorithms, deep learning and transfer learning.

A picture of the architecture

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