Merge pull request #928 from MicrosoftDocs/main

10/21/2024 AM Publish

Author: Taojunshen

articles/ai-services/computer-vision/how-to/identity-access-token.md

@@ -57,7 +57,7 @@ To call the **issueLimitedAccessToken** API, copy the following cURL command to
 
 ```bash
 curl -X POST 'https://<isv-endpoint>/sts/v1.0/issueLimitedAccessToken?expiredTime=3600' \  
--H 'Ocp-Apim-Subscription-Key: <client-face-key>' \  
+-H 'Ocp-Apim-Subscription-Key: <isv-face-key>' \  
 -H 'Content-Type: application/json' \  
 -d '{  
     "resourceId": "/subscriptions/<subscription-id>/resourceGroups/<resource-group-name>/providers/Microsoft.CognitiveServices/accounts/<face-resource-name>",  
@@ -68,7 +68,7 @@ curl -X POST 'https://<isv-endpoint>/sts/v1.0/issueLimitedAccessToken?expiredTim
 Then, make the following changes:
 1. Replace `<isv-endpoint>` with the endpoint of the ISV's resource. For example, **westus.api.cognitive.microsoft.com**.
 1. Optionally set the `expiredTime` parameter to set the expiration time of the token in seconds. It must be between 60 and 86400. The default value is 3600 (one hour).
-1. Replace `<client-face-key>` with the key of the client's Face resource.
+1. Replace `<isv-face-key>` with the key of the ISV's Face resource.
 1. Replace `<subscription-id>` with the subscription ID of the client's Azure subscription.
 1. Replace `<resource-group-name>` with the name of the client's resource group.
 1. Replace `<face-resource-name>` with the name of the client's Face resource.

articles/ai-services/computer-vision/how-to/specify-detection-model.md

@@ -143,10 +143,10 @@ This code creates a **FaceList** called `My face collection` and adds a Face to
 
 In this article, you learned how to specify the detection model to use with different Face APIs. Next, follow a quickstart to get started with face detection and analysis.
 
-* [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp%253fpivots%253dprogramming-language-csharp)
-* [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python%253fpivots%253dprogramming-language-python)
-* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java%253fpivots%253dprogramming-language-java)
-* [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript%253fpivots%253dprogramming-language-javascript)
+* [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp)
+* [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python)
+* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java)
+* [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript)
 
 [Detect]: /rest/api/face/face-detection-operations/detect
 [Identify From Person Group]: /rest/api/face/face-recognition-operations/identify-from-person-group

articles/ai-services/computer-vision/how-to/specify-recognition-model.md

@@ -130,10 +130,10 @@ If you normally specify a confidence threshold (a value between zero and one tha
 
 In this article, you learned how to specify the recognition model to use with different Face service APIs. Next, follow a quickstart to get started with face detection.
 
-* [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp%253fpivots%253dprogramming-language-csharp)
-* [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python%253fpivots%253dprogramming-language-python)
-* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java%253fpivots%253dprogramming-language-java)
-* [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript%253fpivots%253dprogramming-language-javascript)
+* [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp)
+* [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python)
+* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java)
+* [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript)
 
 [Detect]: /rest/api/face/face-detection-operations/detect
 [Verify Face To Face]: /rest/api/face/face-recognition-operations/verify-face-to-face

articles/ai-services/computer-vision/includes/identity-gate-notice.md

@@ -11,4 +11,4 @@ ms.author: pafarley
 ---
 
 > [!CAUTION]
-> Face service access is limited based on eligibility and usage criteria in order to support our Responsible AI principles. Face service is only available to Microsoft managed customers and partners. Use the [Face Recognition intake form](https://aka.ms/facerecognition) to apply for access. For more information, see the [Face limited access](/legal/cognitive-services/computer-vision/limited-access-identity?context=%2Fazure%2Fcognitive-services%2Fcomputer-vision%2Fcontext%2Fcontext) page.
+> Face service access is limited based on eligibility and usage criteria in order to support our Responsible AI principles. Face service is only available to Microsoft managed customers and partners. Use the [Face Recognition intake form](https://aka.ms/facerecognition) to apply for access. For more information, see the [Face limited access](/legal/cognitive-services/computer-vision/limited-access-identity?context=%2Fazure%2Fai-services%2Fcomputer-vision%2Fcontext%2Fcontext) page.

articles/ai-services/computer-vision/reference-face-error-codes.md

@@ -37,6 +37,7 @@ These error codes can be returned by any Face API calls.
 |Bad Request (400)|InvalidImageSize|Image size is too small.|The valid image file size should be larger than or equal to 1 KB.|
 |Bad Request (400)|InvalidImageSize|Image size is too big.|The valid image file size should be no larger than 6 MB.|
 |Unauthorized (401)|401|Access denied due to invalid subscription key or wrong API endpoint. Make sure to provide a valid key for an active subscription and use a correct regional API endpoint for your resource.||
+|Forbidden (403)|UnsupportedFeature|Feature is not supported, missing approval for one or more of the following features: Identification, Verification.|Register for access by submitting a [registration form](https://aka.ms/facerecognition).|
 |Conflict (409)|ConcurrentOperationConflict|There is a conflict operation on resource `<resourceName>`, please try later.||
 |Too Many Requests (429)|429|Rate limit is exceeded.||
 
@@ -50,6 +51,7 @@ These error codes can be returned by Face Detection operation.
 |Bad Request (400)|BadArgument|Invalid argument returnFaceAttributes.||
 |Bad Request (400)|BadArgument|'returnFaceAttributes' is not supported by detection_02.||
 |Bad Request (400)|BadArgument|'returnLandmarks' is not supported by detection_02.||
+|Forbidden (403)|UnsupportedFeature|Return Attributes (emotion, gender, age, smile, facial hair, hair and makeup) have been deprecated and are no longer supported.|Read more about this decision [here](https://azure.microsoft.com/blog/responsible-ai-investments-and-safeguards-for-facial-recognition/).|
 
 ## Face Liveness Session error codes
 
@@ -243,4 +245,4 @@ These error codes can be returned by Person Directory operations.
 
 Next steps
 
-- [Face API reference](/rest/api/face/operation-groups)
+- [Face API reference](/rest/api/face/operation-groups)

articles/ai-services/computer-vision/tutorials/liveness.md

@@ -55,8 +55,8 @@ We provide SDKs in different languages for frontend applications and app servers
 
 Once you have access to the SDK, follow instructions in the [azure-ai-vision-sdk](https://github.com/Azure-Samples/azure-ai-vision-sdk) GitHub repository to integrate the UI and the code into your native mobile application. The liveness SDK supports Java/Kotlin for Android mobile applications, Swift for iOS mobile applications and JavaScript for web applications:
 - For Swift iOS, follow the instructions in the [iOS sample](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-ios-readme) 
-- For Kotlin/Java Android, follow the instructions in the [Android sample](https://aka.ms/liveness-sample-java) 
-- For JavaScript Web, follow the instructions in the [Web sample](https://aka.ms/liveness-sample-web) 
+- For Kotlin/Java Android, follow the instructions in the [Android sample](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-android-readme) 
+- For JavaScript Web, follow the instructions in the [Web sample](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-web-readme) 
 
 Once you've added the code into your application, the SDK handles starting the camera, guiding the end-user in adjusting their position, composing the liveness payload, and calling the Azure AI Face cloud service to process the liveness payload.
 
@@ -808,7 +808,7 @@ If you want to clean up and remove an Azure AI services subscription, you can de
 
 To learn about other options in the liveness APIs, see the Azure AI Vision SDK reference.
 
-- [Kotlin (Android)](https://aka.ms/liveness-sample-java)
+- [Kotlin (Android)](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-android-readme)
 - [Swift (iOS)](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-ios-readme)
 - [JavaScript (Web)](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-web-readme)
 

articles/ai-services/language-service/question-answering/tutorials/active-learning.md

@@ -20,9 +20,9 @@ In this tutorial, you learn how to:
 > * Accept/reject active learning suggestions
 > * Add alternate questions
 
-This tutorial shows you how to enhance your custom question answering project with active learning. If you notice that customers are asking questions, which are not part of your project. There are often variations of questions that are paraphrased differently.
+This tutorial shows you how to enhance your custom question answering project with active learning. If you notice that customers are asking questions that are not covered in your project, they may be paraphrased variations of questions.
 
-These variations when added as alternate questions to the relevant question answer pair, help to optimize the project to answer real world user queries. You can manually add alternate questions to question answer pairs through the editor. At the same time, you can also use the active learning feature to generate active learning suggestions based on user queries. The active learning feature, however, requires that the project receives regular user traffic to generate suggestions.
+These variations, when added as alternate questions to the relevant question answer pair, help to optimize the project to answer real world user queries. You can manually add alternate questions to question answer pairs through the editor. At the same time, you can also use the active learning feature to generate active learning suggestions based on user queries. The active learning feature, however, requires that the project receives regular user traffic to generate suggestions.
 
 ## Use active learning
 

articles/ai-services/openai/azure-government.md

@@ -25,7 +25,7 @@ The following sections show model availability by region and deployment type.
 
 |   **Region**  | **gpt-35-turbo**, **1106** | **gpt-35-turbo**, **0125** | **gpt-4**, **1106-Preview** | **gpt-4o**, **2024-05-13** | **text-embedding-ada-002** |
 |:--------------|:--------------------------:|:--------------------------:|:---------------------------:|:--------------------------:|:--------------------------:|
-| usgovarizona  | ✅ | ✅ | ✅ | ✅ | ✅ |
+| usgovarizona  | - | ✅ | ✅ | ✅ | ✅ |
 | usgovvirginia | ✅ | ✅ | ✅ | - | ✅ |
 
 To request quota increases for the pay-as-you-go consumption model, apply at [https://aka.ms/AOAIGovQuota](https://aka.ms/AOAIGovQuota)

articles/ai-services/openai/concepts/provisioned-throughput.md

@@ -37,7 +37,7 @@ An Azure OpenAI Deployment is a unit of management for a specific OpenAI Model.
 | Estimating size | Provided calculator in the studio & benchmarking script. |
 
 
-## How much thoughput per PTU you get for each model
+## How much throughput per PTU you get for each model
 The amount of throughput (tokens per minute or TPM) a deployment gets per PTU is a function of the input and output tokens in the minute. Generating output tokens requires more processing than input tokens and so the more output tokens generated the lower your overall TPM. The service dynamically balances the input & output costs, so users do not have to set specific input and output limits. This approach means your deployment is resilient to fluctuations in the workload shape. 
 
 To help with simplifying the sizing effort, the following table outlines the TPM per PTU for the `gpt-4o` and `gpt-4o-mini` models
@@ -109,7 +109,7 @@ Azure OpenAI is a highly sought-after service where customer demand might exceed
 
 To find the capacity needed for their deployments, use the capacity  API or the Studio deployment experience to provide real-time information on capacity availability.
 
-In Azure OpenAI Studio, the deployment experience identifies when a region lacks the capacity needed to deploy the model. This looks at the desired model, version and number of PTUs. If cpacity is unavailable, the experience direct  users to a select an alternative region.
+In Azure OpenAI Studio, the deployment experience identifies when a region lacks the capacity needed to deploy the model. This looks at the desired model, version and number of PTUs. If capacity is unavailable, the experience direct  users to a select an alternative region.
 
 Details on the new deployment experience can be found in the Azure OpenAI [Provisioned get started guide](../how-to/provisioned-get-started.md).
 

articles/ai-studio/concepts/encryption-keys-portal.md

@@ -87,7 +87,7 @@ Customer-managed key encryption is configured via Azure portal in a similar way
 
 Alternatively, use infrastructure-as-code options for automation. Example Bicep templates for Azure AI Studio are available on the Azure Quickstart repo:
 1. [CMK encryption for hub](https://github.com/Azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices/aistudio-cmk).
-1. [Service-side CMK encryption preview for hub](https://github.com/azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices/machine-learning-workspace-cmk-service-side-encryption).
+1. [Service-side CMK encryption preview for hub](https://github.com/azure/azure-quickstart-templates/tree/master/quickstarts/microsoft.machinelearningservices/aistudio-cmk-service-side-encryption).
 
 ## Limitations