Merge pull request #5316 from PatrickFarley/freshness-pass

JamesJBarnett · web-flow · commit f6995baeac1f · 2025-05-31T16:17:13.000-07:00
Freshness pass
diff --git a/articles/ai-foundry/ai-services/content-safety-overview.md b/articles/ai-foundry/ai-services/content-safety-overview.md
@@ -7,7 +7,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: overview
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ---
diff --git a/articles/ai-foundry/concepts/content-filtering.md b/articles/ai-foundry/concepts/content-filtering.md
@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: conceptual
-ms.date: 04/29/2025
+ms.date: 05/31/2025
 ms.reviewer: eur
 ms.author: pafarley
 author: PatrickFarley
@@ -24,9 +24,9 @@ author: PatrickFarley
 
 ## How it works 
 
-The content filtering system is powered by [Azure AI Content Safety](../../ai-services/content-safety/overview.md), and it works by running both the prompt input and completion output through a set of classification models designed to detect and prevent the output of harmful content. Variations in API configurations and application design might affect completions and thus filtering behavior.
+The content filtering system is powered by [Azure AI Content Safety](../../ai-services/content-safety/overview.md), and it works by running both the model prompt input and completion output through a set of classification models designed to detect and prevent the output of harmful content. Variations in API configurations and application design might affect completions and thus filtering behavior.
 
-With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later on). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Models Sold Directly by Azure ](model-catalog-content-safety.md).
+With Azure OpenAI model deployments, you can use the default content filter or create your own content filter (described later). Models available through **standard deployments** have content filtering enabled by default. To learn more about the default content filter enabled for standard deployments, see [Content safety for Models Sold Directly by Azure ](model-catalog-content-safety.md).
 
 ## Language support
 
@@ -73,20 +73,7 @@ You can also enable the following special output filters:
 
 ### Configurability (preview)
 
-The default content filtering configuration for the GPT model series is set to filter at the medium severity threshold for all four content harm categories (hate, violence, sexual, and self-harm) and applies to both prompts (text, multi-modal text/image) and completions (text). This means that content that is detected at severity level medium or high is filtered, while content detected at severity level low isn't filtered by the content filters. For DALL-E, the default severity threshold is set to low for both prompts (text) and completions (images), so content detected at severity levels low, medium, or high is filtered. 
-
-The configurability feature allows customers to adjust the settings, separately for prompts and completions, to filter content for each content category at different severity levels as described in the table below:
-
-| Severity filtered | Configurable for prompts | Configurable for completions | Descriptions |
-|-------------------|--------------------------|------------------------------|--------------|
-| Low, medium, high | Yes | Yes | Strictest filtering configuration. Content detected at severity levels low, medium and high is filtered.|
-| Medium, high      | Yes | Yes | Content detected at severity level low isn't filtered, content at medium and high is filtered.|
-| High              | Yes| Yes | Content detected at severity levels low and medium isn't filtered. Only content at severity level high is filtered. Requires approval<sup>1</sup>.|
-| No filters | If approved<sup>1</sup>| If approved<sup>1</sup>| No content is filtered regardless of severity level detected. Requires approval<sup>1</sup>.|
-
-<sup>1</sup> For Azure OpenAI models, only customers who have been approved for modified content filtering have full content filtering control, including configuring content filters at severity level high only or turning off content filters. Apply for modified content filters via these forms: [Azure OpenAI Limited Access Review: Modified Content Filters](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUMlBQNkZMR0lFRldORTdVQzQ0TEI5Q1ExOSQlQCN0PWcu), and [Modified Abuse Monitoring](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOE9MUTFMUlpBNk5IQlZWWkcyUEpWWEhGOCQlQCN0PWcu).
-
-Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/ai-code-of-conduct?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext). 
+[!INCLUDE [content-filter-configurability](../../ai-services/openai/includes/content-filter-configurability.md)]
 
 
 ## Related content
diff --git a/articles/ai-foundry/how-to/use-blocklists.md b/articles/ai-foundry/how-to/use-blocklists.md
@@ -7,7 +7,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ---
diff --git a/articles/ai-foundry/responsible-use-of-ai-overview.md b/articles/ai-foundry/responsible-use-of-ai-overview.md
@@ -6,7 +6,7 @@ manager: nitinme
 keywords: Azure AI services, cognitive
 ms.service: azure-ai-foundry
 ms.topic: overview
-ms.date: 05/09/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 author: PatrickFarley
 ms.custom: ignite-2024
diff --git a/articles/ai-services/computer-vision/concept-face-recognition.md b/articles/ai-services/computer-vision/concept-face-recognition.md
@@ -10,7 +10,7 @@ ms.subservice: azure-ai-face
 ms.custom:
   - ignite-2023
 ms.topic: conceptual
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 feedback_help_link_url: https://learn.microsoft.com/answers/tags/156/azure-face
 ---
diff --git a/articles/ai-services/computer-vision/concept-object-detection-40.md b/articles/ai-services/computer-vision/concept-object-detection-40.md
@@ -7,8 +7,9 @@ manager: nitinme
 
 ms.service: azure-ai-vision
 ms.topic: conceptual
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
+ms.collection: "ce-skilling-fresh-tier2, ce-skilling-ai-copilot"
 ---
 
 # Object detection (version 4.0)
diff --git a/articles/ai-services/computer-vision/concept-object-detection.md b/articles/ai-services/computer-vision/concept-object-detection.md
@@ -9,6 +9,8 @@ ms.service: azure-ai-vision
 ms.topic: conceptual
 ms.date: 03/26/2025
 ms.author: pafarley
+ms.collection: "ce-skilling-fresh-tier2, ce-skilling-ai-copilot"
+
 ---
 
 # Object detection
diff --git a/articles/ai-services/computer-vision/concept-people-detection.md b/articles/ai-services/computer-vision/concept-people-detection.md
@@ -9,6 +9,8 @@ ms.service: azure-ai-vision
 ms.topic: conceptual
 ms.date: 01/22/2025
 ms.author: pafarley
+ms.collection: "ce-skilling-fresh-tier2, ce-skilling-ai-copilot"
+
 ---
 
 # People detection (version 4.0)
diff --git a/articles/ai-services/openai/concepts/default-safety-policies.md b/articles/ai-services/openai/concepts/default-safety-policies.md
@@ -6,7 +6,7 @@ author: PatrickFarley
 ms.author: pafarley
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
diff --git a/articles/ai-services/openai/concepts/gpt-4-v-prompt-engineering.md b/articles/ai-services/openai/concepts/gpt-4-v-prompt-engineering.md
@@ -6,13 +6,13 @@ author: PatrickFarley
 ms.author: pafarley
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
 # Image prompt engineering techniques
 
-To unlock the full potential of vision-enabled chat models like GPT-4 Turbo with Vision and GPT-4o, it's essential to tailor the prompts to your specific needs. Here are some guidelines to enhance the accuracy and efficiency of your prompts.
+To unlock the full potential of vision-enabled chat models, it's essential to tailor the prompts to your specific needs. Here are some guidelines to enhance the accuracy and efficiency of your prompts.
 
 ## Fundamentals of writing an image prompt
 
diff --git a/articles/ai-services/openai/concepts/gpt-with-vision.md b/articles/ai-services/openai/concepts/gpt-with-vision.md
@@ -6,13 +6,13 @@ author: PatrickFarley
 ms.author: pafarley
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
 # Vision-enabled chat model concepts
 
-Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. The current vision-enabled models are GPT-4 Turbo with Vision, GPT-4o, and GPT-4o-mini. This guide provides details on their capabilities and limitations.
+Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. This guide provides details on their capabilities and limitations. To see which models support image input, see the [Models page](./models.md).
 
 To try out vision-enabled chat models, see the [quickstart](/azure/ai-services/openai/gpt-v-quickstart).
 
@@ -21,6 +21,16 @@ To try out vision-enabled chat models, see the [quickstart](/azure/ai-services/o
 The vision-enabled models answer general questions about what's present in the images you upload.
 
 
+## Input limitations
+
+This section describes the limitations of vision-enabled chat models.
+
+### Image support
+
+- **Maximum input image size**: The maximum size for input images is restricted to 20 MB.
+- **Low resolution accuracy**: When images are analyzed using the "low resolution" setting, it allows for faster responses and uses fewer input tokens for certain use cases. However, this could impact the accuracy of object and text recognition within the image.
+- **Image chat restriction**: When you upload images in [Azure AI Foundry portal](https://ai.azure.com/) or the API, there is a limit of 10 images per chat call.
+
 ## Special pricing information
 
 > [!IMPORTANT]
@@ -70,16 +80,6 @@ For a typical use case, take a 3-minute video with a 100-token prompt input. The
 Additionally, there's a one-time indexing cost of $0.15 to generate the Video Retrieval index for this 3-minute video. This index can be reused across any number of Video Retrieval and GPT-4 Turbo with Vision API calls.
 -->
 
-## Input limitations
-
-This section describes the limitations of vision-enabled chat models.
-
-### Image support
-
-- **Maximum input image size**: The maximum size for input images is restricted to 20 MB.
-- **Low resolution accuracy**: When images are analyzed using the "low resolution" setting, it allows for faster responses and uses fewer input tokens for certain use cases. However, this could impact the accuracy of object and text recognition within the image.
-- **Image chat restriction**: When you upload images in [Azure AI Foundry portal](https://ai.azure.com/) or the API, there is a limit of 10 images per chat call.
-
 <!--
 ### Video support
 
diff --git a/articles/ai-services/openai/concepts/prompt-transformation.md b/articles/ai-services/openai/concepts/prompt-transformation.md
@@ -6,7 +6,7 @@ author: PatrickFarley
 ms.author: pafarley
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
diff --git a/articles/ai-services/openai/dall-e-quickstart.md b/articles/ai-services/openai/dall-e-quickstart.md
@@ -8,7 +8,7 @@ ms.custom: devx-track-python, devx-track-dotnet, devx-track-extended-java, devx-
 ms.topic: quickstart
 author: PatrickFarley
 ms.author: pafarley
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 zone_pivot_groups: openai-quickstart-dall-e
 ---
 
diff --git a/articles/ai-services/openai/gpt-v-quickstart.md b/articles/ai-services/openai/gpt-v-quickstart.md
@@ -9,18 +9,14 @@ ms.custom: devx-track-python, devx-track-js, devx-track-ts
 ms.topic: quickstart
 author: PatrickFarley
 ms.author: pafarley
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 zone_pivot_groups: openai-quickstart-gpt-v
 ---
 
 # Quickstart: Use images in your AI chats
 
-Get started using GPT-4 Turbo with images with the Azure OpenAI in Azure AI Foundry Models.
+Get started using images in your chats with Azure OpenAI in Azure AI Foundry Models.
 
-> [!NOTE]
-> **Model choice**
->
-> The latest vision-capable models are `gpt-4o` and `gpt-4o mini`. These models are in public preview. The latest available GA model is `gpt-4` version `turbo-2024-04-09`.
 
 > [!IMPORTANT]
 > Extra usage fees might apply when using chat completion models with vision functionality.
@@ -62,7 +58,7 @@ Get started using GPT-4 Turbo with images with the Azure OpenAI in Azure AI Foun
 
 ::: zone-end
 
-## Next steps
+## Related content
 
 * [Get started with multimodal vision chat apps using Azure OpenAI AI App template](/azure/developer/ai/get-started-app-chat-vision?tabs=github-codespaces)
 * Learn more about these APIs in the [Vision-enabled models how-to guide](./gpt-v-quickstart.md)
diff --git a/articles/ai-services/openai/how-to/gpt-with-vision.md b/articles/ai-services/openai/how-to/gpt-with-vision.md
@@ -7,14 +7,14 @@ ms.author: pafarley #delegenz
 #customer intent: As a developer, I want to learn how to use vision-enabled chat models so that I can integrate image processing capabilities into my applications.
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
 # Use vision-enabled chat models
 
 
-Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. The current vision-enabled models are [o1](./reasoning.md), GPT-4o, GPT-4o-mini, and GPT-4 Turbo with Vision.
+Vision-enabled chat models are large multimodal models (LMM) developed by OpenAI that can analyze images and provide textual responses to questions about them. They incorporate both natural language processing and visual understanding. The current vision-enabled models are the [o-series reasoning models](./reasoning.md), GPT-4.1 series models, GPT-4.5, GPT-4o series, and GPT-4 Turbo with Vision.
 
 The vision-enabled models can answer general questions about what's present in the images you upload.
 
@@ -383,7 +383,7 @@ Every response includes a `"finish_reason"` field. It has the following possible
 [!INCLUDE [GPT-4 Turbo](../includes/gpt-4-turbo.md)]
 
 
-## Next steps
+## Related content
 
 * [Learn more about Azure OpenAI](../overview.md).
 * [Vision-enabled chats quickstart](../gpt-v-quickstart.md)
diff --git a/articles/ai-services/openai/how-to/risks-safety-monitor.md b/articles/ai-services/openai/how-to/risks-safety-monitor.md
@@ -6,7 +6,7 @@ author: PatrickFarley
 ms.author: pafarley 
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 manager: nitinme
 ---
 
@@ -43,14 +43,14 @@ Adjust your content filter configuration to further align with business needs an
 
 ## Potentially abusive user detection   
 
-The **Potentially abusive user detection** pane leverages user-level abuse reporting to show information about users whose behavior has resulted in blocked content. The goal is to help you get a view of the sources of harmful content so you can take responsive actions to ensure the model is being used in a responsible way. 
+The **Potentially abusive user detection** pane shows information about users whose behavior has resulted in blocked content. The goal is to help you get a view of the sources of harmful content so you can take responsive actions to ensure the model is being used in a responsible way. 
 
 
 To use Potentially abusive user detection, you need:
 - A content filter configuration applied to your deployment.
 - You must be sending user ID information in your Chat Completion requests (see the _user_ parameter of the [Completions API](/azure/ai-services/openai/reference#completions), for example).
     > [!CAUTION]
-    > Use GUID strings to identify individual users. Do not include sensitive personal information in the _user_ field.
+    > Use GUID strings to identify individual users. Don't include sensitive personal information in the _user_ field.
 - An Azure Data Explorer database set up to store the user analysis results (instructions below).
 
 ### Set up your Azure Data Explorer database
diff --git a/articles/ai-services/openai/how-to/use-blocklists.md b/articles/ai-services/openai/how-to/use-blocklists.md
@@ -5,7 +5,7 @@ description: Learn how to use blocklists with Azure OpenAI
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: how-to
-ms.date: 02/20/2025
+ms.date: 05/31/2025
 author: PatrickFarley
 ms.author: pafarley
 ---
@@ -17,7 +17,7 @@ The [configurable content filters](/azure/ai-services/openai/how-to/content-filt
 ## Prerequisites
 
 - An Azure subscription. <a href="https://azure.microsoft.com/free/ai-services" target="_blank">Create one for free</a>.
-- Once you have your Azure subscription, create an Azure OpenAI resource in the Azure portal to get your token, key and endpoint. Enter a unique name for your resource, select the subscription you entered on the application form, select a resource group, supported region, and supported pricing tier. Then select **Create**.
+- Once you have your Azure subscription, create an Azure OpenAI resource in the Azure portal to get your token, key, and endpoint. Enter a unique name for your resource, select the subscription you entered on the application form, select a resource group, supported region, and supported pricing tier. Then select **Create**.
     - The resource takes a few minutes to deploy. After it finishes, select **go to resource**. In the left pane, under **Resource Management**, select **Subscription Key and Endpoint**. The endpoint and either of the keys are used to call APIs.
 - [Azure CLI](/cli/azure/install-azure-cli) installed
 - [cURL](https://curl.haxx.se/) installed
@@ -30,7 +30,7 @@ You can create blocklists with the Azure OpenAI API. The following steps help yo
 
 ### Get your token
 
-First, you need to get a token for accessing the APIs for creating, editing and deleting blocklists. You can get this token using the following Azure CLI command: 
+First, you need to get a token for accessing the APIs for creating, editing, and deleting blocklists. You can get this token using the following Azure CLI command: 
 
 ```bash
 az account get-access-token 
@@ -102,7 +102,7 @@ Copy the cURL command below to a text editor and make the following changes:
 1. Replace {raiBlocklistName} (in the URL) with a custom name for your list. Allowed characters: `0-9, A-Z, a-z, - . _ ~`. 
 1. Replace {raiBlocklistItemName} with a custom name for your list item. 
 1. Replace {token} with the token you got from the "Get your token" step above. 
-1. Replace the value of the `"blocking pattern"` field with the item you'd like to add to your blocklist. The maximum length of a blockItem is 1000 characters. Also specify whether the pattern is regex or exact match. 
+1. Replace the value of the `"blocking pattern"` field with the item you'd like to add to your blocklist. The maximum length of a blockItem is 1,000 characters. Also specify whether the pattern is regex or exact match. 
 
 ```bash
 curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiBlocklists/{raiBlocklistName}/raiBlocklistItems/{raiBlocklistItemName}?api-version=2024-04-01-preview' \ 
@@ -117,7 +117,7 @@ curl --location --request PUT 'https://management.azure.com/subscriptions/{subsc
 ```
 
 > [!NOTE]
-> It can take around 5 minutes for a new term to be added to the blocklist. Please test after 5 minutes. 
+> It can take around 5 minutes for a new term to be added to the blocklist. Test the blocklist after 5 minutes. 
 
 The response code should be `200`. 
 
diff --git a/articles/ai-services/responsible-use-of-ai-overview.md b/articles/ai-services/responsible-use-of-ai-overview.md
@@ -6,7 +6,7 @@ author: PatrickFarley
 manager: nitinme
 ms.service: azure-ai-services
 ms.topic: conceptual
-ms.date: 05/01/2025
+ms.date: 05/31/2025
 ms.author: pafarley
 ---
 
@@ -20,9 +20,8 @@ Azure AI services provides information and guidelines on how to responsibly use
 
 ## Vision
 - [Azure AI Vision - Image Analysis](/legal/cognitive-services/computer-vision/imageanalysis-transparency-note?context=/azure/ai-services/computer-vision/context/context)
-- [Azure AI Vision - OCR](/legal/cognitive-services/computer-vision/ocr-transparency-note?context=/azure/ai-services/computer-vision/context/context)
+- [Azure AI Vision - OCR (legacy)](/legal/cognitive-services/computer-vision/ocr-transparency-note?context=/azure/ai-services/computer-vision/context/context)
 - [Azure AI Vision - Face](/legal/cognitive-services/face/transparency-note?context=/azure/ai-services/computer-vision/context/context)
-- [Azure AI Vision - Spatial Analysis](/legal/cognitive-services/computer-vision/transparency-note-spatial-analysis?context=/azure/ai-services/computer-vision/context/context)
 - [Azure Custom Vision](/legal/cognitive-services/custom-vision/custom-vision-cvs-transparency-note?context=/azure/ai-services/custom-vision-service/context/context)
 - [Azure Video Indexer](/legal/azure-video-indexer/transparency-note?context=%2Fazure%2Fazure-video-indexer%2Fcontext%2Fcontext)
 
