Merge branch 'main' into release-scommi

Author: v-alje

articles/ai-services/computer-vision/how-to/find-similar-faces.md

@@ -46,17 +46,6 @@ The following code uses the above method to get face data from a series of image
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_loadfaces)]
 
 
-#### [JavaScript](#tab/javascript)
-
-The following face detection method is optimized for comparison operations. It doesn't extract detailed face attributes, and it uses an optimized recognition model.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="recognize":::
-
-The following code uses the above method to get face data from a series of images.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="snippet_loadfaces":::
-
-
 #### [REST API](#tab/rest)
 
 Copy the following cURL command and insert your key and endpoint where appropriate. Then run the command to detect one of the target faces.
@@ -89,12 +78,6 @@ The following code prints the match details to the console:
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_find_similar_print)]
 
-#### [JavaScript](#tab/javascript)
-
-The following method takes a set of target faces and a single source face. Then, it compares them and finds all the target faces that are similar to the source face. Finally, it prints the match details to the console.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="find_similar":::
-
 
 #### [REST API](#tab/rest)
 

articles/ai-services/computer-vision/includes/quickstarts-sdk/identity-javascript-sdk.md

@@ -15,7 +15,7 @@ ms.author: pafarley
 
 Get started with facial recognition using the Face client library for JavaScript. Follow these steps to install the package and try out the example code for basic tasks. The Face service provides you with access to advanced algorithms for detecting and recognizing human faces in images. Follow these steps to install the package and try out the example code for basic face identification using remote images.
 
-[Reference documentation](/javascript/api/overview/azure/cognitiveservices-face-readme) | [Package (npm)](https://www.npmjs.com/package/@azure/cognitiveservices-face) | [Samples](/samples/browse/?products=azure&term=face&languages=javascript)
+[Reference documentation](https://aka.ms/azsdk-javascript-face-ref) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest) | [Package (npm)](https://www.npmjs.com/package/@azure-rest/ai-vision-face) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples)
 
 ## Prerequisites
 
@@ -47,10 +47,10 @@ Get started with facial recognition using the Face client library for JavaScript
     npm init
     ```
 
-1. Install the `ms-rest-azure` and `azure-cognitiveservices-face` npm packages:
+1. Install the `@azure-rest/ai-vision-face` npm packages:
 
     ```console
-    npm install @azure/cognitiveservices-face @azure/ms-rest-js uuid
+    npm install @azure-rest/ai-vision-face
     ```
 
     Your app's `package.json` file is updated with the dependencies.
@@ -96,12 +96,18 @@ Add face to the person group person: (Family2-Lady) from image: Family2-Lady1.jp
 Done adding faces to person group.
 
 Training person group: c08484e0-044b-4610-8b7e-c957584e5d2d.
-Waiting 10 seconds...
 Training status: succeeded.
-
+No persons identified for face with ID 259dd648-be70-499c-9942-3512594e21eb
 Person: Family1-Mom is identified for face in: identification1.jpg with ID: b7f7f542-c338-4a40-ad52-e61772bc6e14. Confidence: 0.96921.
 Person: Family1-Son is identified for face in: identification1.jpg with ID: 600dc1b4-b2c4-4516-87de-edbbdd8d7632. Confidence: 0.92886.
 Person: Family1-Dad is identified for face in: identification1.jpg with ID: e83b494f-9ad2-473f-9d86-3de79c01e345. Confidence: 0.96725.
+Verification result between face bb7f7f542-c338-4a40-ad52-e61772bc6e14 and person de1d7dea-a393-4f69-9062-10cb66d4cf17: true with confidence: 0.96921
+Verification result between face 600dc1b4-b2c4-4516-87de-edbbdd8d7632 and person 05fd84e4-41b0-4716-b767-4376e33fa207: true with confidence: 0.92886
+Verification result between face e83b494f-9ad2-473f-9d86-3de79c01e345 and person c5124fe2-39dd-47ba-9163-1ed2998fdeb2: true with confidence: 0.96725
+
+Deleting person group: c08484e0-044b-4610-8b7e-c957584e5d2d
+
+Done.
 ```
 
 
@@ -120,4 +126,4 @@ In this quickstart, you learned how to use the Face client library for JavaScrip
 > [Specify a face detection model version](../../how-to/specify-detection-model.md)
 
 * [What is the Face service?](../../overview-identity.md)
-* More extensive sample code can be found on [GitHub](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/javascript/Face/sdk_quickstart.js).
+* More extensive sample code can be found on [GitHub](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples).

articles/ai-services/openai/includes/on-your-data-authentication.md

@@ -9,7 +9,7 @@ ms.date: 03/27/2024
 
 ## Data connection
 
-You need to select how you want to authenticate the connection from Azure OpenAI, Azure AI Search, and Azure blob storage. You can choose a *System assigned managed identity* or an *API key*. By selecting *API key* as the authentication type, the system will automatically populate the API key for you to connect with your Azure AI Search resource. By selecting *System assigned managed identity*, the authentication will be based on the [role assignment](../how-to/use-your-data-securely.md#role-assignments) you have. *System assigned managed identity* is selected by default for security. 
+You need to select how you want to authenticate the connection from Azure OpenAI, Azure AI Search, and Azure blob storage. You can choose a *System assigned managed identity* or an *API key*. By selecting *API key* as the authentication type, the system will automatically populate the API key for you to connect with your Azure AI Search, Azure OpenAI, and Azure Blob Storage resources. By selecting *System assigned managed identity*, the authentication will be based on the [role assignment](../how-to/use-your-data-securely.md#role-assignments) you have. *System assigned managed identity* is selected by default for security. 
 
 
 :::image type="content" source="../media/use-your-data/data-connection-authentication.png" alt-text="A screenshot showing the managed identity option in Azure OpenAI Studio." lightbox="../media/use-your-data/data-connection-authentication.png":::

articles/ai-studio/concepts/ai-resources.md

@@ -18,18 +18,27 @@ author: Blackmist
 
 [!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
 
-The Azure AI Studio hub is the top-level Azure resource for AI Studio and provides the working environment for a team to build and manage AI applications. In Azure, resources enable access to Azure services for individuals and teams. Resources also provide a container for billing, security configuration, and monitoring. The hub also connects to Azure and third party resources, bringing the resources you need together in Azure AI Studio.
+Hubs are the primary top-level Azure resource for AI studio and provide a central way for a team to govern security, connectivity, and computing resources across playgrounds and projects. Once a hub is created, it is enables developers to self-service create projects and access shared company resources without needing an IT administrator's repeated help.
+
+Project workspaces that are created using a hub inherit the same security settings and shared resource access. Teams can create project workspaces as needed to organize their work, isolate data, and/or restrict access. 
 
 In this article, you learn more about hub capabilities, and how to set up a hub for your organization. You can see the resources created in the [Azure portal](https://portal.azure.com/) and in [Azure AI Studio](https://ai.azure.com).
 
-## Collaboration environment for a team
+## Rapid AI use case exploration without IT bottlenecks
+
+Successful AI applications and models typically start as prototypes, with developers testing the feasibility of an idea or assessing the quality of data or a model for a particular task. This is a steppingstone towards project funding or a full-scale implementation.
+
+The transition from proving the feasibility of an idea to a funded project is where many organizations encounter a bottleneck in productivity, because a single platform team is responsible for the setup of cloud resources. Such a team may be the only one authorized to configure security, connectivity or other resources that may incur costs. This can cause a huge backlog, resulting in development teams getting blocked on innovating with a new idea. In Azure AI Studio, hubs help mitigate this bottleneck. IT can set up a pre-configured, reusable environment, or hub, for a team one time, and a team can use that hub to create their own projects for prototyping, building, and operating AI applications.
+
+## Set up and secure a hub for your team
+
+Get started by [creating your first hub in Azure AI Studio](../how-to/create-azure-ai-resource.md), or use [Azure Portal](../how-to/create-secure-ai-hub.md) or [templates](../how-to/create-azure-ai-hub-template.md) for advanced configuration options. You can customize networking, identity, encryption, monitoring or tags, to meet compliance with your organization’s requirements.
 
-The hub provides the collaboration environment for a team to build and manage AI applications, catering to two personas:
+Often, projects in a business domain require access to the same company resources such as vector indices, model endpoints or repos. As a team lead, you can pre-configure connectivity with these resources within a hub, so developers can access them from any new project workspace without delay on IT.
 
-* To AI developers, the hub provides the working environment for building AI applications granting access to various tools for AI model building. Tools can be used together, and lets you use and produce shareable components including datasets, indexes, models. A hub allows you to configure connections to external resources, provide compute resources used by tools and [endpoints, and access keys to prebuilt AI models](#azure-ai-services-api-access-keys). When you use an Azure AI Studio project to customize AI capabilities, a hub hosts the project and can access the same shared resources.
-* To IT administrators, team leads and risk officers, the hub provides a single pane of glass on projects created by a team. The team can audit connections that are in use to external resources and other governance controls to help meet cost and compliance requirements. Security settings are configured on the hub, and once set up apply to all projects created under it, allowing administrators to enable developers to self-serve create projects to organize work.
+[Connections](connections.md) let you access objects in AI Studio that are managed outside of your hub. For example, uploaded data on an Azure storage account, or model deployments on an existing Azure OpenAI resource. A connection can be shared with every project or made accessible to one specific project, with the option to configure key-based access or EntraID-passthrough to authorize access to users on the connected resource. Plus, as an administrator, you can track, audit, and manage connections across projects using your hub.
 
-## Central setup and management concepts
+## Shared Azure resources and configurations
 
 Various management concepts are available on hubs to support team leads and admins to centrally manage a team's environment. 
 
@@ -98,7 +107,7 @@ When you create a new hub, a set of dependent Azure resources are required to st
 
 ## Managing cost
 
-Azure AI costs accrue by [various Azure resources](#central-setup-and-management-concepts). 
+Azure AI costs accrue by [various Azure resources](#azure-ai-dependencies). 
 
 In general, a hub and project don't have a fixed monthly cost, and you're only charged for usage in terms of compute hours and tokens used. Azure Key Vault, Storage, and Application Insights charge transaction and volume-based, dependent on the amount of data stored with your projects.