Table of Contents
Blueprint overview/Introduction
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<use case 2:Federated Learning in Data Gathering>
Deep learning is a promising way in aiding medical treatment and diagnosis, but an effective model requires quite large amounts of different data to converge. And the lack of sufficient training data is the biggest obstacle to developing AI models for medical applications.
Federated learning provides a safe tunnel across different medical institutions like hospitals and clinics, so that they can use train their own AI model with the data from multi-sources and without worry about the law issues and privacy problem with the help of Federated learning.
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Many cloud native monitoring applications are used to collect container/node resource usage and running log, like prometheus, elasticsearch.
The below image shows the overall architecture for using IEC as edge infrastructure in AI Edge.
Platform Architecture
The detailed platform architecture of AI Edge blueprint is shown in the below diagram.
In the current release the components released are
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Software Management: Gerrit Repo
Licensing
Apache 2.0 license