update intro to be specific to MaaS

Author: msakande

articles/ai-foundry/concepts/models-featured.md

@@ -19,7 +19,7 @@ The Azure AI model catalog offers a large selection of models, from a wide range
 
 [!INCLUDE [models-preview](../includes/models-preview.md)]
 
-You have various options for deploying models from the model catalog. For some models, you need to host them on your infrastructure, as in the case of deployment via managed compute. For others, you can host them on Microsoft's servers, as in the case of deployment via serverless APIs. See [Available models for supported deployment options](../how-to/model-catalog-overview.md#available-models-for-supported-deployment-options) for a list of models in the catalog that are available for deployment via managed compute or serverless API.
+You have various options for deploying models from the model catalog. The models listed in this article can be deployed and hosted on Microsoft's servers via serverless APIs. For some  of these models, you can also host them on your infrastructure for deployment via managed compute. See [Available models for supported deployment options](../how-to/model-catalog-overview.md#available-models-for-supported-deployment-options) for a list of models in the catalog that are available for deployment via managed compute or serverless API.
 
 To perform inferencing with the models, some models such as [Nixtla's TimeGEN-1](#nixtla) and [Cohere rerank](#cohere-rerank) require you to use custom APIs from the model providers. Others that belong to the following model types support inferencing using the [Azure AI model inference](../model-inference/overview.md):