Merge pull request #1277 from MicrosoftDocs/main

11/5/2024 AM Publish

Author: Taojunshen

articles/ai-services/document-intelligence/quickstarts/includes/csharp-sdk.md

@@ -106,7 +106,7 @@ In this quickstart, use the following features to analyze and extract data and v
 
     :::image type="content" source="../../media/quickstarts/select-doc-intel-nuget-package.png" alt-text="Screenshot of select NuGet prerelease package window in Visual Studio.":::
 
-1. Select the **Browse** tab and type *Azure.AI.FormRecognizer*.
+1. Select the **Browse** tab and type *Azure.AI.DocumentIntelligence*.
 
 1. Select the **`Include prerelease`** checkbox.
 

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

@@ -41,13 +41,14 @@ An Azure OpenAI Deployment is a unit of management for a specific OpenAI 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
+To help with simplifying the sizing effort, the following table outlines the TPM per PTU for the `gpt-4o` and `gpt-4o-mini` models. The table also shows Service Level Agreement (SLA) Latency Target Values per model.  For more information about the SLA for Azure OpenAI Service, see the [Service Level Agreements (SLA) for Online Services page].(https://www.microsoft.com/licensing/docs/view/Service-Level-Agreements-SLA-for-Online-Services?lang=1)
 
-|     | **gpt-4o**, **2024-05-13**   & **gpt-4o**, **2024-08-06**   | **gpt-4o-mini**, **2024-07-18**   | 
+|     | **gpt-4o**, **2024-05-13**   & **gpt-4o**, **2024-08-06**   | **gpt-4o-mini**, **2024-07-18**   |
 | --- | --- | --- |
 | Deployable Increments | 50 | 25|
 | Input TPM per PTU | 2,500 | 37,000  |
-| Output TPM per PTU | 833  | 12,333 |
+| Output TPM per PTU| 833|12,333|
+| Latency Target Value |25 Tokens Per Second* |33 Tokens Per Second*|
 
 For a full list see the [AOAI Studio calculator](https://oai.azure.com/portal/calculator).
 

articles/ai-studio/includes/create-hub.md

@@ -10,17 +10,24 @@ ms.date: 5/21/2024
 ms.custom: include, build-2024
 ---
 
+> [!NOTE]
+> A hub in Azure AI Studio is a one-stop shop where you manage everything your AI project needs, like security and resources, so you can develop and test faster. To learn more about how hubs can help you, see the [Hubs and projects overview](/azure/ai-studio/concepts/ai-resources) article.
+
 To create a hub in [Azure AI Studio](https://ai.azure.com), follow these steps:
 
 1. Go to the **Home** page in [Azure AI Studio](https://ai.azure.com) and sign in with your Azure account.
-1. Select **All hubs** from the left pane and then select **+ New hub**.
+1. Select **All resources** on the left pane. If you cannot see this option, in the top bar select **All resources & projects**. Then select **+ New hub**.
 
     :::image type="content" source="../media/how-to/hubs/hub-new.png" alt-text="Screenshot of the button to create a new hub." lightbox="../media/how-to/hubs/hub-new.png":::
 
-1. In the **Create a new hub** dialog, enter a name for your hub (such as *contoso-hub*) and select **Next**. Leave the default **Connect Azure AI Services** option selected. A new AI services connection is created for the hub.
+1. In the **Create a new hub** dialog, enter a name for your hub (such as *contoso-hub*). If you don't have a resource group, a new **Resource group** will be created linked to the **Subscription** provided. Leave the default **Connect Azure AI Services** option selected. 
+1. Select **Next**. If you didn't reuse an existing resource group, a new resource group (*rg-contoso*) is created.  Also an Azure AI service (*ai-contoso-hub*) is created for the hub.
 
     :::image type="content" source="../media/how-to/hubs/hub-new-connect-services.png" alt-text="Screenshot of the dialog to connect services while creating a new hub." lightbox="../media/how-to/hubs/hub-new-connect-services.png":::
 
+    > [!NOTE]
+    > If you don't see (new) before the **Resource group** and **Connect Azure AI Services** entries then an existing resource is being used. For the purposes of this tutorial, create a seperate entity via **Create new resource group** and **Create new AI Services**. This will allow you to prevent any unexpected charges by deleting the entities after the tutorial.
+
 1. Review the information and select **Create**.
 
     :::image type="content" source="../media/how-to/hubs/hub-new-review-create.png" alt-text="Screenshot of the dialog to review the settings for the new hub." lightbox="../media/how-to/hubs/hub-new-review-create.png":::