Merge pull request #259470 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/ai-services/LUIS/luis-container-configuration.md

@@ -55,7 +55,7 @@ Do not use the starter key or the authoring key.
 
 ## Billing setting
 
-The `Billing` setting specifies the endpoint URI of the _Azure AI services_ resource on Azure used to meter billing information for the container. You must specify a value for this configuration setting, and the value must be a valid endpoint URI for a _Azure AI services_ resource on Azure. The container reports usage about every 10 to 15 minutes.
+The `Billing` setting specifies the endpoint URI of the _Azure AI services_ resource on Azure used to meter billing information for the container. You must specify a value for this configuration setting, and the value must be a valid endpoint URI for an _Azure AI services_ resource on Azure. The container reports usage about every 10 to 15 minutes.
 
 This setting can be found in the following places:
 

articles/search/vector-search-integrated-vectorization.md

@@ -46,7 +46,7 @@ Here's a checklist of the components responsible for integrated vectorization:
 + A skillset providing a Text Split skill for data chunking, and a skill for vectorization (either the AzureOpenAiEmbedding skill or a custom skill pointing to an external embedding model).
 + Optionally, index projections (also defined in a skillset) to push chunked data to a secondary index
 + An embedding model, deployed on Azure OpenAI or available through an HTTP endpoint.
-+ An indexer for driving the process end-t-end. An indexer also specifies a schedule, field mappings, and properties for change detection.
++ An indexer for driving the process end-to-end. An indexer also specifies a schedule, field mappings, and properties for change detection.
 
 This checklist focuses on integrated vectorization, but your solution isn't limited to this list. You can add more skills for AI enrichment, create a knowledge store, add semantic ranking, add relevance tuning, and other query features.