Merge pull request #1343 from MicrosoftDocs/main

Taojunshen · web-flow · commit 8be63203ba9c · 2024-11-07T06:59:35.000+08:00
11/6/2024 PM Publish
diff --git a/articles/ai-services/containers/docker-compose-recipe.md b/articles/ai-services/containers/docker-compose-recipe.md
@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: how-to
-ms.date: 02/22/2024
+ms.date: 11/06/2024
 ms.author: aahi
 
 # SME: Brendan Walsh
diff --git a/articles/ai-services/content-safety/whats-new.md b/articles/ai-services/content-safety/whats-new.md
@@ -45,7 +45,7 @@ The groundedness detection API includes a correction feature that automatically
 
 ### New features are GA
 
-The Prompt Shields API and groundedness detection API are now generally available (GA). Follow a quickstart to try them out.
+The Prompt Shields API and Protected Material for text API are now generally available (GA). Follow a quickstart to try them out.
 * [Prompt Shields quickstart](/azure/ai-services/content-safety/quickstart-jailbreak)
 * [Protected Material quickstart](/azure/ai-services/content-safety/quickstart-protected-material?tabs=curl)
 ## July 2024
diff --git a/articles/ai-services/create-account-bicep.md b/articles/ai-services/create-account-bicep.md
@@ -5,7 +5,7 @@ keywords: Azure AI services, cognitive solutions, cognitive intelligence, cognit
 author: eric-urban
 ms.service: azure-ai-services
 ms.topic: quickstart
-ms.date: 8/1/2024
+ms.date: 11/06/2024
 ms.author: eur
 ms.custom:
   - subject-armqs
diff --git a/articles/ai-services/luis/client-libraries-rest-api.md b/articles/ai-services/luis/client-libraries-rest-api.md
@@ -2,12 +2,12 @@
 title: "Quickstart: Language Understanding (LUIS) SDK client libraries and REST API"
 description: Create and query a LUIS app with the LUIS SDK client libraries and REST API.
 ms.topic: quickstart
-ms.date: 01/19/2024
+ms.date: 11/06/2024
 ms.service: azure-ai-language
-ms.author: aahi
+ms.author: jboback
 manager: nitinme
 ms.subservice: azure-ai-luis
-author: aahill
+author: jboback
 keywords: Azure, artificial intelligence, ai, natural language processing, nlp, LUIS, azure luis, natural language understanding, ai chatbot, chatbot maker,  understanding natural language
 ms.devlang: csharp
 # ms.devlang: csharp, javascript, python
diff --git a/articles/ai-services/luis/concepts/entities.md b/articles/ai-services/luis/concepts/entities.md
@@ -3,13 +3,13 @@ title: Entities
 titleSuffix: Azure AI services
 description: Entities concepts
 #services: cognitive-services
-ms.author: aahi
-author: aahill
+ms.author: jboback
+author: jboback
 manager: nitinme
 ms.service: azure-ai-language
 ms.subservice: azure-ai-luis
 ms.topic: conceptual
-ms.date: 01/19/2024
+ms.date: 11/06/2024
 ---
 
 # Entity types
@@ -23,10 +23,10 @@ An entity is an item or an element that is relevant to the user's intent. Entiti
 | Utterance | Intent predicted | Entities extracted | Explanation |
 |--|--|--|--|
 | Hello, how are you? | Greeting | - | Nothing to extract. |
-| I want to order a small pizza | orderPizza | 'small' | 'Size' entity is extracted as 'small'. |
-| Turn off bedroom light | turnOff | 'bedroom' | 'Room' entity is extracted as 'bedroom'. |
-| Check balance in my savings account ending in 4406 | checkBalance | 'savings', '4406' | 'accountType' entity is extracted as 'savings' and 'accountNumber' entity is extracted as '4406'. |
-| Buy 3 tickets to New York | buyTickets | '3', 'New York' | 'ticketsCount' entity is extracted as '3' and 'Destination' entity is extracted as 'New York". |
+| I want to order a small pizza | orderPizza | 'small' | 'Size' entity is extracted as 'small.' |
+| Turn-off bedroom light | turnOff | 'bedroom' | 'Room' entity is extracted as 'bedroom.' |
+| Check balance in my savings account ending in 4406 | checkBalance | 'savings', '4406' | 'accountType' entity is extracted as 'savings' and 'accountNumber' entity is extracted as '4406.' |
+| Buy 3 tickets to New York | buyTickets | '3', 'New York' | 'ticketsCount' entity is extracted as '3' and 'Destination' entity is extracted as 'New York." |
 
 Entities are optional but recommended. You don't need to create entities for every concept in your app, only when:
 
diff --git a/articles/ai-services/luis/index.yml b/articles/ai-services/luis/index.yml
@@ -5,9 +5,9 @@ summary: Learn how Language Understanding enables your applications to understan
 
 metadata:
   ms.topic: landing-page
-  ms.date: 01/19/2024
-  ms.author: aahi
-  author: aahill
+  ms.date: 11/06/2024
+  ms.author: jboback
+  author: jboback
   manager: nitinme
   ms.service: azure-ai-language
   ms.subservice: azure-ai-luis
diff --git a/articles/ai-services/luis/luis-container-howto.md b/articles/ai-services/luis/luis-container-howto.md
@@ -3,13 +3,13 @@ title: Install and run Docker containers for LUIS
 titleSuffix: Azure AI services
 description: Use the LUIS container to load your trained or published app, and gain access to its predictions on-premises.
 #services: cognitive-services
-author: aahill
+author: jboback
 manager: nitinme
 ms.service: azure-ai-language
 ms.subservice: azure-ai-luis
 ms.topic: how-to
-ms.date: 01/19/2024
-ms.author: aahi
+ms.date: 11/06/2024
+ms.author: jboback
 keywords: on-premises, Docker, container
 ---
 
diff --git a/articles/ai-studio/how-to/develop/ai-template-get-started.md b/articles/ai-studio/how-to/develop/ai-template-get-started.md
@@ -28,7 +28,7 @@ Start with our sample applications! Choose the right template for your needs, th
 
 | Template      | App host | Tech stack | Description |
 | ----------- | ----------| ----------- | ------------|
-| [Contoso Chat Retail copilot with Azure AI Studio](https://github.com/Azure-Samples/contoso-chat) | [Azure AI Studio online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Cosmos DB](/azure/cosmos-db/index-overview), [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Azure AI Search](/azure/search/search-what-is-azure-search), Bicep  | A retailer conversation agent that can answer questions grounded in your product catalog and customer order history. This template uses a retrieval augmented generation architecture with cutting-edge models for chat completion, chat evaluation, and embeddings. Build, evaluate, and deploy, an end-to-end solution with a single command. | 
+| [Contoso Chat Retail copilot with Azure AI Studio](https://github.com/Azure-Samples/contoso-chat) | [Azure Container Apps](/azure/container-apps/overview) | [Azure Cosmos DB](/azure/cosmos-db/index-overview), [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Azure AI Search](/azure/search/search-what-is-azure-search), Bicep  | A retailer conversation agent that can answer questions grounded in your product catalog and customer order history. This template uses a retrieval augmented generation architecture with cutting-edge models for chat completion, chat evaluation, and embeddings. Build, evaluate, and deploy, an end-to-end solution with a single command. | 
 | [Process Automation: speech to text and summarization with Azure AI Studio](https://github.com/Azure-Samples/summarization-openai-python-prompflow) | [Azure AI Studio online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure OpenAI Service](../../../ai-services/openai/overview.md), [Azure AI speech to text service](../../../ai-services/speech-service/index-speech-to-text.yml), Bicep  | An app for workers to report issues via text or speech, translating audio to text, summarizing it, and specify the relevant department. | 
 | [Multi-Modal Creative Writing copilot with Dalle](https://github.com/Azure-Samples/agent-openai-python-prompty) | [Azure AI Studio online endpoints](/azure/machine-learning/concept-endpoints-online) | [Azure AI Search](/azure/search/search-what-is-azure-search), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep | demonstrates how to create and work with AI agents. The app takes a topic and instruction input and then calls a research agent, writer agent, and editor agent. |  
 | [Assistant API Analytics Copilot with Python and Azure AI Studio](https://github.com/Azure-Samples/assistant-data-openai-python-promptflow) | [Azure AI Studio online endpoints](/azure/machine-learning/concept-endpoints-online) |  [Azure Managed Identity](/entra/identity/managed-identities-azure-resources/overview), [Azure AI Search](/azure/search/search-what-is-azure-search), [Azure OpenAI Service](../../../ai-services/openai/overview.md), Bicep| A data analytics chatbot based on the Assistants API. The chatbot can answer questions in natural language, and interpret them as queries on an example sales dataset. |
diff --git a/articles/machine-learning/azure-machine-learning-ci-image-release-notes.md b/articles/machine-learning/azure-machine-learning-ci-image-release-notes.md
@@ -38,6 +38,16 @@ Jupyter-core: `5.7.2`
 
 zeromq: `4.3.5` 
 
+Vulnerabiities fixed:
+- CVE-2024-42472
+- CVE-2024-48957
+- CVE-2024-48958
+- CVE-2024-47175
+- CVE-2024-23984
+- CVE-2024-24968
+- CVE-2024-5742
+- CVE-2024-43802
+
 ## September 27, 2024
 
 Image Version: `24.09.23`
diff --git a/articles/machine-learning/how-to-securely-attach-databricks.md b/articles/machine-learning/how-to-securely-attach-databricks.md
@@ -35,7 +35,7 @@ The information in this article assumes that your Azure Machine Learning workspa
 
 ## Limitations
 
-Scenarios where the Azure Machine Learning control plane needs to communicate with the Azure Databricks control plane are not supported. Currently the only scenario we have identified where this is a problem is when using the [DatabrickStep](/python/api/azureml-pipeline-steps/azureml.pipeline.steps.databricks_step.databricksstep) in a machine learning pipeline. To work around this limitation, allows public access to your workspace. This can be either using a workspace that isn't configured with a private link or a workspace with a private link that is [configured to allow public access](how-to-configure-private-link.md#enable-public-access).
+Scenarios where the Azure Machine Learning control plane needs to communicate with the Azure Databricks control plane are not supported. To work around this limitation, allows public access to your workspace. This can be either using a workspace that isn't configured with a private link or a workspace with a private link that is [configured to allow public access](how-to-configure-private-link.md#enable-public-access).
 
 ## Create a private endpoint for Azure Machine Learning
 
@@ -90,4 +90,4 @@ To allow Azure Databricks to communicate with the VNet that the Azure Machine Le
 
 ## Next steps
 
-* [Manage compute resources for training and deployment](how-to-create-attach-compute-studio.md)
+* [Manage compute resources for training and deployment](how-to-create-attach-compute-studio.md)
