Merge pull request #275857 from MicrosoftDocs/main

5/21 Publish for Build 2024

Author: huypub

.openpublishing.publish.config.json

@@ -1004,6 +1004,12 @@
       "branch": "docs-snippets",
       "branch_mapping": {}
     },
+    {
+      "path_to_root": "functions-openai-extension",
+      "url": "https://github.com/Azure/azure-functions-openai-extension",
+      "branch": "main",
+      "branch_mapping": {}
+    },
     {
       "path_to_root": "cosmos-db-nosql-dotnet-samples",
       "url": "https://github.com/azure-samples/cosmos-db-nosql-dotnet-samples",

.openpublishing.redirection.azure-kubernetes-service.json

@@ -451,6 +451,11 @@
             "redirect_url": "/azure/aks/create-node-pools",
             "redirect_document_id": false
         },
+        {
+            "source_path_from_root": "/articles/copilot/limited-access.md",
+            "redirect_url": "/azure/copilot/manage-access",
+            "redirect_document_id": false
+        },
         {
             "source_path_from_root": "/articles/aks/command-invoke.md",
             "redirect_url": "/azure/aks/access-private-cluster",

articles/ai-services/includes/preview-feature.md

@@ -0,0 +1,14 @@
+---
+title: include file
+description: include file
+author: eur
+ms.reviewer: eur
+ms.author: eric-urban
+ms.service: azure-ai-studio
+ms.topic: include
+ms.date: 2/22/2024
+ms.custom: include, build-2024
+---
+
+> [!NOTE]
+> This feature is currently in public preview. This preview is provided without a service-level agreement, and we don't recommend it for production workloads. Certain features might not be supported or might have constrained capabilities. For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).

articles/ai-services/includes/quickstarts/ai-studio-prerequisites.md

@@ -0,0 +1,13 @@
+---
+author: eric-urban
+ms.service: azure-ai-services
+ms.custom:
+  - build-2024
+ms.date: 5/21/2024
+ms.topic: include
+ms.author: eur
+---
+
+> [!div class="checklist"]
+> - Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services).
+> - Some AI services features are free to try in AI Studio. For access to all capabilities described in this article, you need to [connect AI services to your hub in AI Studio](../../../ai-studio/ai-services/connect-ai-services.md#connect-to-ai-services). 

articles/ai-services/language-service/personally-identifiable-information/concepts/conversations-entity-categories.md

@@ -1,15 +1,15 @@
 ---
 title: Entity categories recognized by Conversational Personally Identifiable Information (detection) in Azure AI Language
 titleSuffix: Azure AI services
-description: Learn about the entities the Conversational PII feature (preview) can recognize from conversation inputs.
+description: Learn about the entities the Conversational PII feature can recognize from conversation inputs.
 #services: cognitive-services
 author: jboback
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: conceptual
 ms.date: 12/19/2023
 ms.author: jboback
-ms.custom: language-service-pii
+ms.custom: language-service-pii, build-2024
 ---
 
 # Supported customer content (PII) entity categories in conversations

articles/ai-services/language-service/personally-identifiable-information/language-support.md

@@ -9,12 +9,12 @@ ms.service: azure-ai-language
 ms.topic: conceptual
 ms.date: 12/19/2023
 ms.author: jboback
-ms.custom: language-service-pii
+ms.custom: language-service-pii, build-2024
 ---
 
 # Personally Identifiable Information (PII) detection language support 
 
-Use this article to learn which natural languages are supported by the PII and conversation PII (preview) features of Azure AI Language.
+Use this article to learn which natural languages are supported by the PII and conversation PII features of Azure AI Language.
 
 # [PII for documents](#tab/documents)
 

articles/ai-services/language-service/personally-identifiable-information/overview.md

@@ -9,22 +9,20 @@ ms.service: azure-ai-language
 ms.topic: overview
 ms.date: 01/31/2024
 ms.author: jboback
-ms.custom: language-service-pii
+ms.custom: language-service-pii, build-2024
 ---
 
 # What is Personally Identifiable Information (PII) detection in Azure AI Language?
 
-PII detection is one of the features offered by [Azure AI Language](../overview.md), a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The PII detection feature can **identify, categorize, and redact** sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. The method for utilizing PII in conversations is different than other use cases, and articles for this use are separate.
+As of June 2024, we now provide General Availability support for the Conversational PII service (English-language only).
+Customers can now redact transcripts, chats, and other text written in a conversational style (i.e. text with “um”s, “ah”s, multiple speakers, and the spelling out of words for more clarity) with better confidence in AI quality, Azure SLA support and production environment support, and enterprise-grade security in mind.
+
+PII detection is one of the features offered by [Azure AI Language](../overview.md), a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The PII detection feature can **identify, categorize, and redact** sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification. Azure AI Language supports general text PII redaction, as well as [Conversational PII](how-to-call-for-conversations.md), a specialized model for handling speech transcriptions and the more informal, conversational tone of meeting and call transcripts. The service also supports [Native Document PII redaction](#native-document-support), where the input and output are structured document files.
 
 * [**Quickstarts**](quickstart.md) are getting-started instructions to guide you through making requests to the service.
 * [**How-to guides**](how-to-call.md) contain instructions for using the service in more specific or customized ways.
 * The [**conceptual articles**](concepts/entity-categories.md) provide in-depth explanations of the service's functionality and features.
 
-PII comes into two shapes:
-
-* [PII](how-to-call.md) - works on unstructured text.
-* [Conversation PII (preview)](how-to-call-for-conversations.md) - tailored model to work on conversation transcription.
-
 [!INCLUDE [Typical workflow for pre-configured language features](../includes/overview-typical-workflow.md)]
 
 ## Native document support

articles/ai-services/language-service/summarization/custom/how-to/data-formats.md

@@ -6,10 +6,11 @@ description: Learn about how to select and prepare data, to be successful in cre
 author: jboback
 manager: nitinme
 ms.service: azure-ai-language
+ms.custom:
+  - build-2024
 ms.topic: how-to
 ms.date: 12/19/2023
 ms.author: jboback
-
 ---
 
 # Format data for custom Summarization
@@ -21,7 +22,7 @@ This page contains information about how to select and prepare data in order to
 
 ## Custom summarization document sample format
 
-In the abstractive document summarization scenario, each document (whether it has a provided label or not) is expected to be provided in a plain .txt file. The file contains one or more lines. If multiple lines are provided, each is assumed to be a paragraph of the document. The following is an example document with three paragraphs.
+In the abstractive text summarization scenario, each document (whether it has a provided label or not) is expected to be provided in a plain .txt file. The file contains one or more lines. If multiple lines are provided, each is assumed to be a paragraph of the document. The following is an example document with three paragraphs.
 
 *At Microsoft, we have been on a quest to advance AI beyond existing techniques, by taking a more holistic, human-centric approach to learning and understanding. As Chief Technology Officer of Azure AI services, I have been working with a team of amazing scientists and engineers to turn this quest into a reality.*
 
@@ -66,7 +67,7 @@ In the abstractive document summarization scenario, each document (whether it ha
 
 ## Sample mapping JSON format
 
-In both document and conversation summarization scenarios, a set of documents and corresponding labels can be provided in a single JSON file that references individual document/conversation and summary files. 
+In both text and conversation summarization scenarios, a set of documents and corresponding labels can be provided in a single JSON file that references individual document/conversation and summary files. 
 
 The JSON file is expected to contain the following fields:
 
@@ -96,7 +97,7 @@ The JSON file is expected to contain the following fields:
 ```
 ## Custom document summarization mapping sample
 
-The following is an example mapping file for the abstractive document summarization scenario with three documents and corresponding labels.
+The following is an example mapping file for the abstractive text summarization scenario with three documents and corresponding labels.
 
 ```json
 {

articles/ai-services/language-service/summarization/how-to/conversation-summarization.md

@@ -12,6 +12,7 @@ ms.author: jboback
 ms.custom:
   - language-service-summarization
   - ignite-2023
+  - build-2024
 ---
 
 # How to use conversation summarization
@@ -47,8 +48,8 @@ For easier navigation, here are links to the corresponding sections for each ser
 
 The conversation summarization API uses natural language processing techniques to summarize conversations into shorter summaries per request. Conversation summarization can summarize for issues and resolutions discussed in a two-party conversation or summarize a long conversation into chapters and a short narrative for each chapter.
 
-There's another feature in Azure AI Language named [document summarization](../overview.md?tabs=document-summarization) that is more suitable to summarize documents into concise summaries. When you're deciding between document summarization and conversation summarization, consider the following points:
-* Input format: Conversation summarization can operate on both chat text and speech transcripts, which have speakers and their utterances. Document summarization operates using simple text, or Word, PDF, or PowerPoint formats.
+There's another feature in Azure AI Language named [text summarization](../overview.md?tabs=text-summarization) that is more suitable to summarize documents into concise summaries. When you're deciding between text summarization and conversation summarization, consider the following points:
+* Input format: Conversation summarization can operate on both chat text and speech transcripts, which have speakers and their utterances. Text summarization operates using simple text, or Word, PDF, or PowerPoint formats.
 * Purpose of summarization: for example, conversation issue and resolution summarization returns a reason and the resolution for a chat between a customer and a customer service agent.
 
 ## Submitting data