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This page documents ideas and techniques related to using ML techniques in the RIC/xApps (under O-RAN).

There are many ways ML could be used in the RIC and how the ML techniques could be embedded in the xApps. Therefore, the following are just examples

  • Goal is to support ML models in non-real time and near-real time RIC usecases.
    • quickly import an Acumos model into RIC and adapt it into as an xApp (near-real time).
    • deploy Acumos models as is into non-real time (mostly on ONAP side).
  • Priority is to get something working with minimal changes possible on ML models
    • focus on performance in the later releases, since many ML models take some time to execute anyway.
  • Build a standard xApp/Acumos microservice adapter
    • deployed along with the Acumos ML model in one Kubernetes pod.
  • Adapter speaks RMR protocol to RIC
    • communicates with the Acumos ML model in the standard http / GRPC manner.
  • Configuration needed for each deployment
    • to tell adapter how to speak with Acumos ML model.
    • can be auto generated using ML model protobuf definition.
  • Consider writing custom RMR model runner
    • for performance in near-real time RIC xApps in the following releases.

Slide deck with Acumos intro and ML based xApp design for Amber release


Gerrit Repo 

https://gerrit.o-ran-sc.org/r/admin/repos/ric-app/ml


Why Acumos? 

In short, the unique features are 1) Distributed AI Marketplace, 2) Interoperable ML Microservices, and 3) Common Open Source Framework to AI. 

To expand more on advantages:

  1. Standardized platform and easy export and Docker-file deployment to any environment, including major public clouds, make stand-up and maintenance a breeze.
  2. Simplified toolkit and model onboarding helps data scientists focus on building great AI rather than maintaining infrastructure.
  3. Visual design editor and drag-and-drop application design and chaining lets trainers and other end users deploy normally complicated AI apps for training and testing in minutes.

https://www.acumos.org/

How-to onboard ML model into Acumos - demo video for AI/ML experts

soup-to-nuts wiki page

Is there any company currently using Acumos? 

Yes, Ericcson, Huawei, Orange, AI4EU, AT&T, and TechM successfully deployed and using Acumos instances. For reference LF public instance - http://marketplace.acumos.org

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