Merge pull request #252903 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)

Author: Taojunshen

articles/active-directory/devices/hybrid-join-plan.md

@@ -64,11 +64,8 @@ For devices running the Windows desktop operating system, supported versions are
 
 ### Windows down-level devices
 
-- Windows 8.1
-- Windows 7 support ended on January 14, 2020. For more information, see [Support for Windows 7 has ended](https://support.microsoft.com/en-us/help/4057281/windows-7-support-ended-on-january-14-2020)
 - Windows Server 2012 R2
 - Windows Server 2012
-- Windows Server 2008 R2 for support information on Windows Server 2008 and 2008 R2, see [Prepare for Windows Server 2008 end of support](https://www.microsoft.com/cloud-platform/windows-server-2008)
 
 As a first planning step, you should review your environment and determine whether you need to support Windows down-level devices.
 

articles/azure-video-indexer/video-indexer-embed-widgets.md

@@ -21,7 +21,7 @@ A Cognitive Insights widget includes all visual insights that were extracted fro
 
 |Name|Definition|Description|
 |---|---|---|
-|`widgets` | Strings separated by comma | Allows you to control the insights that you want to render.<br/>Example: `https://www.videoindexer.ai/embed/insights/<accountId>/<videoId>/?widgets=people,keywords` renders only people and keywords UI insights.<br/>Available options: `people`, `keywords`, `audioEffects`, `labels`, `sentiments`, `emotions`, `topics`, `keyframes`, `transcript`, `ocr`, `speakers`, `scenes`, `spokenLanguage`, `observedPeople`, `namedEntities`.|
+|`widgets` | Strings separated by comma | Allows you to control the insights that you want to render.<br/>Example: `https://www.videoindexer.ai/embed/insights/<accountId>/<videoId>/?widgets=people,keywords` renders only people and keywords UI insights.<br/>Available options: `people`, `keywords`, `audioEffects`, `labels`, `sentiments`, `emotions`, `topics`, `keyframes`, `transcript`, `ocr`, `speakers`, `scenes`, `spokenLanguage`, `observedPeople`, `namedEntities`, `detectedObjects`.|
 |`controls`|Strings separated by comma|Allows you to control the controls that you want to render.<br/>Example: `https://www.videoindexer.ai/embed/insights/<accountId>/<videoId>/?controls=search,download` renders only search option and download button.<br/>Available options: `search`, `download`, `presets`, `language`.|
 |`language`|A short language code (language name)|Controls insights language.<br/>Example: `https://www.videoindexer.ai/embed/insights/<accountId>/<videoId>/?language=es-es` <br/>or `https://www.videoindexer.ai/embed/insights/<accountId>/<videoId>/?language=spanish`|
 |`locale` | A short language code | Controls the language of the UI. The default value is `en`. <br/>Example: `locale=de`.|
@@ -43,7 +43,7 @@ You can use the Player widget to stream video by using adaptive bit rate. The Pl
 |`autoplay` | A Boolean value | Indicates if the player should start playing the video when loaded. The default value is `true`.<br/> Example: `autoplay=false`. |
 |`language`/`locale` | A language code | Controls the player language. The default value is `en-US`.<br/>Example: `language=de-DE`.|
 |`location` ||The `location` parameter must be included in the embedded links, see [how to get the name of your region](regions.md). If your account is in preview, the `trial` should be used for the location value. `trial` is the default value for the `location` parameter.| 
-|`boundingBoxes`|Array of bounding boxes options: people (faces) and observed people. <br/>Values should be separated by a comma (",").|Controls the option to set bounding boxes on/off when embedding the player.<br/>All mentioned option will be turned on.<br/><br/>Example: `boundingBoxes= observedPeople, people`<br/>Default value is `boundingBoxes= observedPeople` (only observed people bounding box are turned on).|
+|`boundingBoxes`|Array of bounding boxes. Options: people (faces), observed people and detected objects. <br/>Values should be separated by a comma (",").|Controls the option to set bounding boxes on/off when embedding the player.<br/>All mentioned option will be turned on.<br/><br/>Example: `boundingBoxes=observedPeople,people,detectedObjects`<br/>Default value is `boundingBoxes=observedPeople,detectedObjects` (only observed people and detected objects bounding box are turned on).|
 
 ### Editor widget
 
@@ -70,7 +70,7 @@ To embed a video, use the website as described below:
 
 1. Sign in to the [Azure AI Video Indexer](https://www.videoindexer.ai/) website.
 1. Select the video that you want to work with and press **Play**.
-1. Select the type of widget that you want (**Cognitive Insights**, **Player**, or **Editor**).
+1. Select the type of widget that you want (**Insights**, **Player**, or **Editor**).
 1. Click **&lt;/&gt; Embed**.
 5. Copy the embed code (appears in **Copy the embedded code** in the **Share & Embed** dialog).
 6. Add the code to your app.
@@ -253,7 +253,7 @@ If you embed Azure AI Video Indexer insights with your own [Azure Media Player](
 
 You can choose the types of insights that you want. To do this, specify them as a value to the following URL parameter that's added to the embed code that you get (from the [API](https://aka.ms/avam-dev-portal) or from the [Azure AI Video Indexer](https://www.videoindexer.ai/) website): `&widgets=<list of wanted widgets>`.
 
-The possible values are: `people`, `keywords`, `labels`, `sentiments`, `emotions`, `topics`, `keyframes`, `transcript`, `ocr`, `speakers`, `scenes`, `namedEntities`, `logos`.
+The possible values are listed [here](#cognitive-insights-widget).
 
 For example, if you want to embed a widget that contains only people and keywords insights, the iframe embed URL will look like this:
 

articles/cosmos-db/mongodb/vcore/vector-search.md

@@ -19,7 +19,7 @@ Use vector search in Azure Cosmos DB for MongoDB vCore to seamlessly integrate y
 
 ## What is vector search?
 
-Vector search is a method that helps you find similar items based on their data characteristics rather than by exact matches on a property field. This technique is useful in applications such as searching for similar text, finding related images, making recommendations, or even detecting anomalies. It works by taking the [vector representations](../../../ai-services/openai/concepts/understand-embeddings.md) (lists of numbers) of your data that you created by using a machine learning model by using or an embeddings API. Examples of embeddings APIs are [Azure OpenAI Embeddings](/azure/ai-services/openai/how-to/embeddings) or [Hugging Face on Azure](https://azure.microsoft.com/solutions/hugging-face-on-azure/). It then measures the distance between the data vectors and your query vector. The data vectors that are closest to your query vector are the ones that are found to be most similar semantically.
+Vector search is a method that helps you find similar items based on their data characteristics rather than by exact matches on a property field. This technique is useful in applications such as searching for similar text, finding related images, making recommendations, or even detecting anomalies. It works by taking the [vector representations](../../../ai-services/openai/concepts/understand-embeddings.md) (lists of numbers) of your data that you created by using a machine learning model by using an embeddings API. Examples of embeddings APIs are [Azure OpenAI Embeddings](/azure/ai-services/openai/how-to/embeddings) or [Hugging Face on Azure](https://azure.microsoft.com/solutions/hugging-face-on-azure/). It then measures the distance between the data vectors and your query vector. The data vectors that are closest to your query vector are the ones that are found to be most similar semantically.
 
 By integrating vector search capabilities natively, you can unlock the full potential of your data in applications that are built on top of the [OpenAI API](../../../ai-services/openai/concepts/understand-embeddings.md). You can also create custom-built solutions that use vector embeddings.
 

articles/operator-nexus/howto-kubernetes-cluster-agent-pools.md

@@ -35,7 +35,7 @@ Before proceeding with this how-to guide, it's recommended that you:
 ## System pool
 For a system node pool, Nexus Kubernetes automatically assigns the label `kubernetes.azure.com/mode: system` to its nodes. This label causes Nexus Kubernetes to prefer scheduling system pods on node pools that contain this label. This label doesn't prevent you from scheduling application pods on system node pools. However, we recommend you isolate critical system pods from your application pods to prevent misconfigured or rogue application pods from accidentally killing system pods.
 
-You can enforce this behavior by creating a dedicated system node pool. Use the `CriticalAddonsOnly=true:NoSchedule` taint to prevent application pods from being scheduled on system node pools.
+You can enforce this behavior by creating a dedicated system node pool. Use the `CriticalAddonsOnly=true:NoSchedule` taint to prevent application pods from being scheduled on system node pools. If you intend to use the system pool for application pods (not dedicated), do not apply any application specific taints to the pool, as this can cause cluster creation to fail. 
 
 > [!IMPORTANT]
 > If you run a single system node pool for your Nexus Kubernetes cluster in a production environment, we recommend you use at least three nodes for the node pool.

articles/virtual-network/ip-services/configure-public-ip-bastion.md

@@ -19,7 +19,7 @@ Azure Bastion is deployed to provide secure management connectivity to virtual m
 
 An Azure Bastion host requires a public IP address for its configuration.
 
-In this article, you learn how to create an Azure Bastion host using an existing public IP in your subscription. Azure Bastion doesn't support the change of the public IP address after creation.  Azure Bastion doesn't support public IP prefixes.
+In this article, you learn how to create an Azure Bastion host using an existing public IP in your subscription. Azure Bastion doesn't support the change of the public IP address after creation.  Azure Bastion supports assigning an IP address within an IP prefix range but not assigning the IP prefix range itself. 
 
 >[!NOTE]
 >[!INCLUDE [Pricing](../../../includes/bastion-pricing.md)]