Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into vnet-encryption-ga

Author: asudbring

articles/ai-services/computer-vision/how-to/blob-storage-search.md

@@ -22,14 +22,19 @@ To get started with the **Search photos with image retrieval** scenario in Visio
 >
 > :::image type="content" source="../media/storage-instructions/subscription.png" alt-text="Screenshot of resource selection.":::
 
+
 ## Create a new storage account
 
 To get started, <a href="https://ms.portal.azure.com/#create/Microsoft.StorageAccount"  title="create a new storage account"  target="_blank">create a new storage account</a>.
 
 :::image type="content" source="../media/storage-instructions/create-storage.png" alt-text="Screenshot of Blob storage creation.":::
 
+Fill in the required parameters to configure your storage account, then select **Review** and **Create**.
 
-Fill in the required parameters to configure your storage account, then select **Review** and **Create**. 
+> [!IMPORTANT]
+> Your storage account must be publicly accessible to be used with Vision Studio. Configure this in the **Networking** tab of the resource creation page.
+>
+> :::image type="content" source="../media/storage-instructions/public-access.png" alt-text="Screenshot of network setting.":::
 
 Once your storage account has been deployed, select **Go to resource** to open the storage account overview. 
 

articles/ai-services/computer-vision/media/storage-instructions/public-access.png

@@ -50,7 +50,7 @@ One Azure resource is defined in the Bicep file: [Microsoft.CognitiveServices/ac
 
 1. Select the **Deploy to Azure** button.
 
-    [![Deploy to Azure](../media/template-deployments/deploy-to-azure.svg)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.cognitiveservices%2Fcognitive-services-universalkey%2Fazuredeploy.json)
+    :::image type="content" source="~/articles/reusable-content/ce-skilling/azure/media/template-deployments/deploy-to-azure-button.svg" alt-text="Button to deploy the Resource Manager template to Azure." border="false" link="https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.cognitiveservices%2Fcognitive-services-universalkey%2Fazuredeploy.json":::
 
 2. Enter the following values.
 

articles/ai-services/create-account-resource-manager-template.md

@@ -5,7 +5,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 02/29/2024
+ms.date: 03/07/2024
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -21,11 +21,12 @@ This article is to help you understand the support lifecycle for the Azure OpenA
 
 ## Latest preview API release
 
-Azure OpenAI API version [2024-02-15-preview](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2024-02-15-preview/inference.json)
+Azure OpenAI API version [2024-03-01-preview](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2024-03-01-preview/inference.json)
 is currently the latest preview release.
 
 This version contains support for all the latest Azure OpenAI features including:
 
+- [Embeddings `encoding_format` and `dimensions` parameters] [**Added in 2024-03-01-preview**]
 - [Assistants API](./assistants-reference.md). [**Added in 2024-02-15-preview**]
 - [DALL-E 3](./dall-e-quickstart.md). [**Added in 2023-12-01-preview**]
 - [Text to speech](./text-to-speech-quickstart.md). [**Added in 2024-02-15-preview**]

articles/ai-services/openai/api-version-deprecation.md

@@ -13,7 +13,7 @@ manager: nitinme
 
 # Abuse Monitoring
 
-Azure OpenAI Service detects and mitigates instances of recurring content and/or behaviors that suggest use of the service in a manner that may violate the [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=/azure/ai-services/openai/context/context) or other applicable product terms. Details on how data is handled can be found on the [Data, Privacy and Security page](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context).
+Azure OpenAI Service detects and mitigates instances of recurring content and/or behaviors that suggest use of the service in a manner that may violate the [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=/azure/ai-services/openai/context/context) or other applicable product terms. Details on how data is handled can be found on the [Data, Privacy and Security page](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context). Apply for modified abuse monitoring using this form: [Azure OpenAI Limited Access Review: Modified Abuse Monitoring](https://ncv.microsoft.com/3a140V2W0l).
 
 ## Components of abuse monitoring
 

articles/ai-services/openai/concepts/abuse-monitoring.md

@@ -102,7 +102,7 @@ GPT-4 version 0125-preview is an updated version of the GPT-4 Turbo preview prev
 
 > [!IMPORTANT]
 >
-> - `gpt-4` version 0125-preview replaces version 1106-preview. Deployments of `gpt-4` version 1106-preview set to "Auto-update to default" and "Upgrade when expired" will start to be upgraded on March 8th, 2024 and will complete upgrades within 2 weeks. Deployments of `gpt-4` version 1106-preview set to "No autoupgrade" will stop working starting March 8th, 2024. If you have a deployment of `gpt-4` version 1106-preview, you can test version `0125-preview` in the available regions below.
+> - `gpt-4` versions 1106-Preview and 0125-Preview will be upgraded with a stable version of `gpt-4` in the future. The deployment upgrade of `gpt-4` 1106-Preview to `gpt-4` 0125-Preview scheduled for March 8, 2024 is no longer taking place.  Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "Auto-update to default" and "Upgrade when expired" will start to be upgraded after the stable version is released.  For each deployment, a model version upgrade takes place with no interruption in service for API calls.  Upgrades are staged by region and the full upgrade process is expected to take 2 weeks. Deployments of `gpt-4` versions 1106-Preview and 0125-Preview set to "No autoupgrade" will not be upgraded and will stop operating when the preview version is upgraded in the region.
 
 |  Model ID  | Max Request (tokens) | Training Data (up to)  |
 |  --- |  :--- | :---: |

articles/ai-services/openai/concepts/models.md

@@ -1,7 +1,7 @@
 ---
 title: 'How to use content filters (preview) with Azure OpenAI Service'
 titleSuffix: Azure OpenAI
-description: Learn how to use content filters (preview) with Azure OpenAI Service
+description: Learn how to use content filters (preview) with Azure OpenAI Service.
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
@@ -15,29 +15,29 @@ recommendations: false
 # How to configure content filters with Azure OpenAI Service
 
 > [!NOTE]
-> All customers have the ability to modify the content filters to be stricter (for example, to filter content at lower severity levels than the default). Approval is required for turning the content filters partially or fully off. Managed customers only may apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters and Abuse Monitoring (microsoft.com)](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xURE01NDY1OUhBRzQ3MkQxMUhZSE1ZUlJKTiQlQCN0PWcu).
+> All customers have the ability to modify the content filters to be stricter (for example, to filter content at lower severity levels than the default). Approval is required for turning the content filters partially or fully off. Managed customers only may apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR).
 
-The content filtering system integrated into Azure OpenAI Service runs alongside the core models and uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories. The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe  is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md). Jailbreak risk detection and protected text and code models are optional and off by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default off and can be turned on per your scenario. Note that some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
+The content filtering system integrated into Azure OpenAI Service runs alongside the core models and uses an ensemble of multi-class classification models to detect four categories of harmful content (violence, hate, sexual, and self-harm) at four severity levels respectively (safe, low, medium, and high), and optional binary classifiers for detecting jailbreak risk, existing text, and code in public repositories. The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md). Jailbreak risk detection and protected text and code models are optional and off by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default off and can be turned on per your scenario. Some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
 
 Content filters can be configured at resource level. Once a new configuration is created, it can be associated with one or more deployments. For more information about model deployment, see the [resource deployment guide](create-resource.md).
 
-The configurability feature is available in preview and allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below. Content detected at the 'safe' severity level is labeled in annotations but is not subject to filtering and is not configurable.
+The configurability feature is available in preview and allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below. Content detected at the 'safe' severity level is labeled in annotations but is not subject to filtering and isn't configurable.
 
 | Severity filtered | Configurable for prompts | Configurable for completions | Descriptions |
 |-------------------|--------------------------|------------------------------|--------------|
-| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium and high is filtered.|
-| Medium, high      | Yes | Yes | Default setting. Content detected at severity level low is not filtered, content at medium and high is filtered.|
-| High              | Yes| Yes | Content detected at severity levels low and medium is not filtered. Only content at severity level high is filtered. |
+| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium, and high is filtered.|
+| Medium, high      | Yes | Yes | Default setting. Content detected at severity level low isn't filtered, content at medium and high is filtered.|
+| High              | Yes| Yes | Content detected at severity levels low and medium isn't filtered. Only content at severity level high is filtered. |
 | No filters | If approved<sup>\*</sup>| If approved<sup>\*</sup>| No content is filtered regardless of severity level detected. Requires approval<sup>\*</sup>.|
 
-<sup>\*</sup> Only approved customers have full content filtering control and can turn the content filters partially or fully off. Managed customers only can apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters and Abuse Monitoring (microsoft.com)](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xURE01NDY1OUhBRzQ3MkQxMUhZSE1ZUlJKTiQlQCN0PWcu)
+<sup>\*</sup> Only approved customers have full content filtering control and can turn the content filters partially or fully off. Managed customers only can apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR)
 
 Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext). 
 
 
 |Filter category  |Default setting  |Applied to prompt or completion?  |Description  |
 |---------|---------|---------|---------|
-|Jailbreak risk detection     |    Off     |   Prompt      |   Can be turned on to filter or annotate user prompts that may present a Jailbreak Risk. For more information about consuming annotations visit [Azure OpenAI Service content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=python#annotations-preview) |
+|Jailbreak risk detection     |    Off     |   Prompt      |   Can be turned on to filter or annotate user prompts that might present a Jailbreak Risk. For more information about consuming annotations, visit [Azure OpenAI Service content filtering](/azure/ai-services/openai/concepts/content-filter?tabs=python#annotations-preview) |
 | Protected material - code | off | Completion | Can be turned on to get the example citation and license information in annotations for code snippets that match any public code sources. For more information about consuming annotations, see the [content filtering concepts guide](/azure/ai-services/openai/concepts/content-filter#annotations-preview) |
 | Protected material - text | off | Completion | Can be turned on to identify and block known text content from being displayed in the model output (for example, song lyrics, recipes, and selected web content).  |
 
@@ -66,15 +66,15 @@ The following steps show how to set up a customized content filtering configurat
 
     :::image type="content" source="../media/content-filters/settings.jpg" alt-text="Screenshot of the content filtering configuration with low, medium, high, highlighted." lightbox="../media/content-filters/settings.jpg":::
 
-1. If your use case was approved for modified content filters as outlined above, you will receive full control over content filtering configurations and can can choose to turn filtering partially or fully off. In the image below, filtering is turned off for violence (green box below), while default configurations are retained for other categories. While this disabled the filter functionality for violence, content will still be annotated. To turn all filters and annotations off, toggle off Filters and annotations (red box below).
+1. If your use case was approved for modified content filters as outlined above, you receive full control over content filtering configurations and can choose to turn filtering partially or fully off. In the image below, filtering is turned off for violence (green box below), while default configurations are retained for other categories. While this disabled the filter functionality for violence, content will still be annotated. To turn off all filters and annotations, toggle off Filters and annotations (red box below).
 
     :::image type="content" source="../media/content-filters/off.jpg" alt-text="Screenshot of the content filtering configuration with self harm and violence set to off." lightbox="../media/content-filters/off.jpg":::
 
     You can create multiple content filtering configurations as per your requirements.
 
-1. To turn the optional models on, you can select any of the checkboxes at the left hand side. When each of the optional models is turned on, you can indicate whether the model should Annotate or Filter.
+1. To turn on the optional models, you can select any of the checkboxes at the left hand side. When each of the optional models is turned on, you can indicate whether the model should Annotate or Filter.
 
-1. Selecting Annotate will run the respective model and return annotations via API response, but it will not filter content. In addition to annotations, you can also choose to filter content by switching the Filter toggle to on. 
+1. Selecting Annotate runs the respective model and return annotations via API response, but it will not filter content. In addition to annotations, you can also choose to filter content by switching the Filter toggle to on. 
 
 1. You can create multiple content filtering configurations as per your requirements.
 
@@ -101,7 +101,7 @@ The following steps show how to set up a customized content filtering configurat
 
 ## Best practices
 
-We recommend informing your content filtering configuration decisions through an iterative identification (for example, red team testing, stress-testing, and analysis) and measurement process to address the potential harms that are relevant for a specific model, application, and deployment scenario. After implementing mitigations such as content filtering, repeat measurement to test effectiveness. Recommendations and best practices for Responsible AI for Azure OpenAI, grounded in the [Microsoft Responsible AI Standard](https://aka.ms/RAI) can be found in the [Responsible AI Overview for Azure OpenAI](/legal/cognitive-services/openai/overview?context=/azure/ai-services/openai/context/context).
+We recommend informing your content filtering configuration decisions through an iterative identification (for example, red team testing, stress-testing, and analysis) and measurement process to address the potential harms that are relevant for a specific model, application, and deployment scenario. After you implement mitigations such as content filtering, repeat measurement to test effectiveness. Recommendations and best practices for Responsible AI for Azure OpenAI, grounded in the [Microsoft Responsible AI Standard](https://aka.ms/RAI) can be found in the [Responsible AI Overview for Azure OpenAI](/legal/cognitive-services/openai/overview?context=/azure/ai-services/openai/context/context).
 
 ## Next steps