misc fixes

Author: HeidiSteen

articles/search/search-how-to-index-markdown-blobs.md

@@ -22,6 +22,9 @@ In Azure AI Search, indexers for Azure Blob Storage, Azure Files, and OneLake su
 + One-to-many parsing mode, creating multiple search documents per Markdown file
 + One-to-one parsing mode, creating one search document per Markdown file
 
+> [!TIP]
+> Continue on to the [Tutorial: Search Markdown data from Azure Blob Storage](search-markdown-data-tutorial.md) after reviewing this article.
+
 ## Prerequisites
 
 + A supported data source: Azure Blob storage, Azure File storage, OneLake in Microsoft Fabric.

articles/search/search-region-support.md

@@ -9,7 +9,7 @@ ms.author: heidist
 ms.service: azure-ai-search
 ms.topic: conceptual
 ms.custom: references_regions
-ms.date: 11/08/2024
+ms.date: 11/19/2024
 
 ---
 
@@ -23,7 +23,7 @@ This article identifies the cloud regions in which Azure AI Search is available.
 |---------|--------------|
 | [Extra capacity](search-limits-quotas-capacity.md#service-limits) | Higher capacity partitions became available in selected regions starting in April 2024 with a second wave following in May 2024. If you're using an older search service, create a new search service to benefit from more capacity at the same billing rate. To check existing capacity, [find your search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) and select the **Properties** tab in the middle of the Overview page. To check search service age, follow [these instructions](vector-search-index-size.md#how-to-check-service-creation-date).  Currently, there are just a few regions that *don't* offer higher capacity partitions. Regional support for extra capacity is noted in the footnotes of this article.|
 | [Availability zones](search-reliability.md#availability-zone-support) | Divides a region's data centers into distinct physical location groups, providing high-availability within the same geo. Regional support is noted in this article. |
-| [Azure AI enrichment](cognitive-search-concept-intro.md) | Refers to skills that make internal calls to Azure AI for enrichment and transformation during indexing. Integration requires that Azure AI Search coexists with an [Azure AI multi-service account](/azure/ai-services/multi-service-resource) in the same physical region. Regional support is noted in this article. |
+| [AI service integration](cognitive-search-concept-intro.md) | Refers to skills that make internal calls to Azure AI for enrichment and transformation during indexing. Integration requires that Azure AI Search coexists with an [Azure AI multi-service account](/azure/ai-services/multi-service-resource) in the same physical region. Regional support is noted in this article. |
 | [Azure OpenAI integration](vector-search-integrated-vectorization.md)  | Refers to skills and vectorizers that make internal calls to deployed embedding and chat models on Azure OpenAI. Check [Azure OpenAI model region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability) for the most current list of regions for each embedding and chat model. Specific Azure OpenAI models are in fewer regions, so be sure to check for joint regional availability before installing.|
 | [Azure AI Studio integration](vector-search-integrated-vectorization-ai-studio.md) | Refers to skills and vectorizers that make internal calls to the models hosted in the model catalog. Check [Azure AI Studio region availability](/azure/ai-studio/reference/region-support) for the most current list of regions. |
 | [Azure AI Vision 4.0 multimodal APIs for image vectorization](search-get-started-portal-image-search.md) | Refers to skills and vectorizers that call the multimodal embedding API. Check the [Azure AI Vision region list](/azure/ai-services/computer-vision/overview-image-analysis#region-availability) for joint regional availability. |
@@ -33,9 +33,11 @@ This article identifies the cloud regions in which Azure AI Search is available.
 
 You can create an Azure AI Search resource in any of the following Azure public regions. Almost all of these regions support [higher capacity tiers](search-limits-quotas-capacity.md#service-limits). Exceptions are noted where they apply.
 
+AI service integration refers to internal connections to an Azure AI multi-service account and doesn't include Azure OpenAI integration.
+
 ### Americas
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | Brazil South​​ ​ | ✅ | ✅ | |  |
 | Canada Central​​ | ✅ | ✅ | ✅ |  |
@@ -52,7 +54,7 @@ You can create an Azure AI Search resource in any of the following Azure public
 
 ### Europe
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | North Europe​​ | ✅ | ✅ | ✅ |  |
 | West Europe​​ <sup>1</sup>| ✅ | ✅ | ✅ | All Tiers |
@@ -72,7 +74,7 @@ You can create an Azure AI Search resource in any of the following Azure public
 
 ### Middle East
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | Israel Central​ <sup>1</sup> |  |  | ✅  |  |
 | Qatar Central​ <sup>1</sup> |  |  | ✅ | |
@@ -82,13 +84,13 @@ You can create an Azure AI Search resource in any of the following Azure public
 
 ### Africa
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | South Africa North​ | ✅ |  | ✅ |   |
 
 ### Asia Pacific
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | Australia East​ ​ | ✅ | ✅ | ✅ |   |
 | Australia Southeast​​​ |  | ✅ |  | |
@@ -106,16 +108,15 @@ You can create an Azure AI Search resource in any of the following Azure public
 
 ## Azure Government regions
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | Arizona | ✅ | ✅  | | |
 | Texas |  | ✅ |  | |
 | Virginia | ✅ | ✅  | ✅ | All Tiers |
 
-
 ## Azure operated by 21Vianet
 
-| Region | AI integration | Semantic ranker | Availability zones | Capacity constrained |
+| Region | AI service integration | Semantic ranker | Availability zones | Capacity constrained |
 |--|--|--|--|--|
 | China East |  |  |  |
 | China East 2 <sup>1</sup> | ✅  | | | |

articles/search/search-what-is-azure-search.md

@@ -13,11 +13,11 @@ ms.date: 10/27/2024
 
 # What's Azure AI Search?
 
-Azure AI Search ([formerly known as "Azure Cognitive Search"](whats-new.md#new-service-name)) is an enterprise-ready search and retrieval system, with a comprehensive set of advanced search technology, built for high-performance applications at any scale.  
+Azure AI Search ([formerly known as "Azure Cognitive Search"](whats-new.md#new-service-name)) is an enterprise-ready search and retrieval system, with a comprehensive set of advanced search technologies, built for high-performance applications at any scale.
 
-Azure AI Search is the primary recommended retrieval system when building RAG-based applications on Azure, with native LLM integrations between Azure OpenAI Service and Azure Machine Learning.
+Azure AI Search is the recommended retrieval system for building RAG-based applications on Azure, with native LLM integrations between Azure OpenAI Service and Azure Machine Learning, and multiple strategies for relevance tuning.
 
-Azure AI Search can be used in both traditional and GenAI scenarios. Common use cases include knowledge base insights (catalog or document search), information discovery (data exploration), retrieval-augmented generation (RAG), and automation.  
+Azure AI Search can be used in both traditional and GenAI scenarios. Common use cases include knowledge base insights (catalog or document search), information discovery (data exploration), retrieval-augmented generation (RAG), and indexing automation.  
 
 When you create a search service, you work with the following capabilities:
 

articles/search/whats-new.md

@@ -25,7 +25,7 @@ ms.custom:
 |-----------------------------|------|--------------|
 | [**Network security perimeter**](search-security-network-security-perimiter.md) | Security | Join a search service to a [network security perimeter](/azure/private-link/network-security-perimeter-concepts) to control network access to your search service. The Azure portal and the Management REST APIs in the [2024-06-01-preview](/rest/api/searchmanagement/network-security-perimeter-configurations?view=rest-searchmanagement-2024-06-01-preview&preserve-view=true) can be used to view and reconcile network security perimeter configurations. |
 | [**Shared private link support for Azure AI service connections**](search-indexer-howto-access-private.md) | Security  | Connections to Azure AI for built-in skills processing can now be private using a shared private link on the connection. |
-| [**Rescoring options for compressed vectors**](vector-search-how-to-quantization.md) | Relevance | You can set options to rescore with original vectors instead of compressed vectors. Applies to HNSW and exhaustive KNN vector algorithms, using binary and scalar compression. Available in the [Create or Update Index (2024-11-01-preview)](/rest/api/searchservice/indexes/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true), the Azure portal, and in the Azure SDK beta packages that provide this feature. |
+| [**Rescoring options for compressed vectors**](vector-search-how-to-quantization.md#2024-11-01-preview) | Relevance | You can set options to rescore with original vectors instead of compressed vectors. Applies to HNSW and exhaustive KNN vector algorithms, using binary and scalar compression. Available in the [Create or Update Index (2024-11-01-preview)](/rest/api/searchservice/indexes/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true), the Azure portal, and in the Azure SDK beta packages that provide this feature. |
 | [**Store fewer vector instances**](vector-search-how-to-storage-options.md) | vector search | In vector compression scenarios, you can omit storage of full precision vectors if you don't need them for rescoring. Available in the [Create or Update Index (2024-11-01-preview)](/rest/api/searchservice/indexes/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true), the Azure portal, and in the Azure SDK beta packages that provide this feature. |
 | [**Query rewrite in the semantic reranker**](semantic-how-to-query-rewrite.md) | Relevance | You can set options on a semantic query to rewrite the query input into a revised or expanded query that generates more relevant results from the L2 ranker. Available in the [Search Documents (2024-11-01-preview)](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-11-01-preview&preserve-view=true), the Azure portal, and in the Azure SDK beta packages that provide this feature.|
 | [**New semantic ranker models**](semantic-search-overview.md) | Relevance | Semantic ranker runs with improved models in all supported regions. There is no change to APIs or the portal experience. |