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Author: ssalgadodev

articles/ai-studio/how-to/concept-data-privacy.md

@@ -36,7 +36,7 @@ Although containers for models "Curated by Azure AI" are scanned for vulnerabili
 
 When you deploy a model from the Model Catalog (base or fine-tuned) using serverless APIs with pay-as-you-go billing for inferencing, an API is provisioned giving you access to the model hosted and managed by the Azure Machine Learning Service. Learn more about serverless APIs in [Model catalog and collections](./model-catalog-overview.md). The model processes your input prompts and generates outputs based on the functionality of the model, as described in the model details provided for the model. While the model is provided by the model provider, and your use of the model (and the model provider's accountability for the model and its outputs) is subject to the license terms provided with the model, Microsoft provides and manages the hosting infrastructure and API endpoint. The models hosted in Models-as-a-Service are subject to Azure's data, privacy, and security commitments. Learn more about Azure compliance offerings applicable to Azure AI Studio [here](https://servicetrust.microsoft.com/DocumentPage/7adf2d9e-d7b5-4e71-bad8-713e6a183cf3). 
 
-[!INCLUDE [Feature preview](../includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/preview-ai-studio.md)]
 
 Microsoft acts as the data processor for prompts and outputs sent to and generated by a model deployed for pay-as-you-go inferencing (MaaS). Microsoft does not share these prompts and outputs with the model provider, and Microsoft does not use these prompts and outputs to train or improve Microsoft's, the model provider's, or any third party's models. Models are stateless and no prompts or outputs are stored in the model. If content filtering (preview) is enabled, prompts and outputs are screened for certain categories of harmful content by the Azure AI Content Safety service in real time; learn more about how Azure AI Content Safety processes data [here](/legal/cognitive-services/content-safety/data-privacy). Prompts and outputs are processed within the geography specified during deployment but may be processed between regions within the geography for operational purposes (including performance and capacity management).
 

articles/ai-studio/how-to/model-catalog-overview.md

@@ -130,7 +130,7 @@ Cohere-command-r-plus <br> Cohere-command-r <br> Cohere-embed-v3-english <br> Co
 
 ### Content safety for models deployed via Serverless API
 
-[!INCLUDE [Feature preview](../includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/preview-ai-studio.md)]
 
 Azure AI Studio implements a default configuration of [Azure AI Content Safety](../../ai-services/content-safety/overview.md) text moderation filters for harmful content (sexual, violence, hate, and self-harm) in language models deployed with MaaS. To learn more about content filtering (preview), see [Harm categories](../../ai-services/content-safety/concepts/harm-categories.md). Content filtering (preview) occurs synchronously as the service processes prompts to generate content, and you may be billed separately as per [AACS pricing](https://azure.microsoft.com/pricing/details/cognitive-services/content-safety/) for such use. Complete this form to disable content filtering (preview) for [models deployed as a service](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR2WTn-w_72hGvfUv1OcrZVVUM05MQ1JLQ0xTUlBRVENQQlpQQzVBODNEUiQlQCN0PWcu). Submitting the form disables content filtering (preview) for all active serverless endpoints, and you'll have to resubmit the form to disable content filtering for any newly created endpoints.