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+.. ===============LICENSE_START=======================================================
+.. O-RAN SC CC-BY-4.0
+.. %%
+.. Copyright (C) 2019 AT&T Intellectual Property
+.. %%
+.. Licensed under the Apache License, Version 2.0 (the "License");
+.. you may not use this file except in compliance with the License.
+.. You may obtain a copy of the License at
+..
+..      http://www.apache.org/licenses/LICENSE-2.0
+..
+.. Unless required by applicable law or agreed to in writing, software
+.. distributed under the License is distributed on an "AS IS" BASIS,
+.. WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+.. See the License for the specific language governing permissions and
+.. limitations under the License.
+.. ===============LICENSE_END=========================================================
+
+RIC APP ML Overview
+======================
+
+The O-RAN SC Machine Learning (ML) Common Services provides ML tools, adapters to integrate with a radio access network (RAN) controller.
+
+Using Acumos ML models in the RIC:
+
+* 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.
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