Merge pull request #1267 from MicrosoftDocs/main

PhilKang0704 · web-flow · commit 31bd36fa08ab · 2024-11-05T13:30:51.000+08:00
11/5 11:00 AM IST Publish
diff --git a/articles/ai-services/openai/overview.md b/articles/ai-services/openai/overview.md
@@ -27,15 +27,28 @@ Azure OpenAI Service provides REST API access to OpenAI's powerful language mode
 | Managed Identity| Yes, via Microsoft Entra ID | 
 | UI experience | [Azure portal](https://portal.azure.com) for account & resource management, <br> [Azure AI Studio](https://ai.azure.com) for model exploration and fine-tuning |
 | Model regional availability | [Model availability](./concepts/models.md) |
-| Content filtering | Prompts and completions are evaluated against our content policy with automated systems. High severity content will be filtered. |
+| Content filtering | Prompts and completions are evaluated against our content policy with automated systems. High severity content is filtered. |
 
 ## Responsible AI
 
 At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s <a href="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6" target="_blank">principles for responsible AI use</a>, adopting a [Code of Conduct](/legal/cognitive-services/openai/code-of-conduct?context=/azure/ai-services/openai/context/context) for use of the service, building [content filters](/azure/ai-services/content-safety/overview) to support customers, and providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure OpenAI.
 
-## How do I get access to Azure OpenAI?
+## Get started with Azure OpenAI Service
 
-A Limited Access registration form is not required to access most Azure OpenAI models. Learn more on the [Azure OpenAI Limited Access page](/legal/cognitive-services/openai/limited-access?context=/azure/ai-services/openai/context/context).
+To get started with Azure OpenAI Service, you need to create an Azure OpenAI Service resource in your Azure subscription. 
+
+Start with the [Create and deploy an Azure OpenAI Service resource](./how-to/create-resource.md) guide.
+1. You can create a resource via Azure portal, Azure CLI, or Azure PowerShell. 
+1. When you have an Azure OpenAI Service resource, you can deploy a model such as GPT-4o.
+1. When you have a deployed model, you can:
+
+    - Try out the Azure AI Studio playgrounds to explore the capabilities of the models. 
+    - You can also just start making API calls to the service using the REST API or SDKs.
+    
+    For example, you can try [real-time audio](./realtime-audio-quickstart.md) and [assistants](./assistants-quickstart.md) in the playgrounds or via code.
+
+> [!NOTE]
+> A Limited Access registration form is required to access some Azure OpenAI Service models or features. Learn more on the [Azure OpenAI Limited Access page](/legal/cognitive-services/openai/limited-access?context=/azure/ai-services/openai/context/context).
 
 ## Comparing Azure OpenAI and OpenAI
 
@@ -47,7 +60,7 @@ With Azure OpenAI, customers get the security capabilities of Microsoft Azure wh
 
 ### Prompts & completions
 
-The completions endpoint is the core component of the API service. This API provides access to the model's text-in, text-out interface. Users simply need to provide an input  **prompt** containing the English text command, and the model will generate a text **completion**.
+The completions endpoint is the core component of the API service. This API provides access to the model's text-in, text-out interface. Users simply need to provide an input  **prompt** containing the English text command, and the model generates a text **completion**.
 
 Here's an example of a simple prompt and completion:
 
@@ -70,7 +83,7 @@ Here's an example of a simple prompt and completion:
 
 Azure OpenAI processes text by breaking it down into tokens. Tokens can be words or just chunks of characters. For example, the word “hamburger” gets broken up into the tokens “ham”, “bur” and “ger”, while a short and common word like “pear” is a single token. Many tokens start with a whitespace, for example “ hello” and “ bye”.
 
-The total number of tokens processed in a given request depends on the length of your input, output and request parameters. The quantity of tokens being processed will also affect your response latency and throughput for the models.
+The total number of tokens processed in a given request depends on the length of your input, output, and request parameters. The quantity of tokens being processed will also affect your response latency and throughput for the models.
  
 #### Image tokens
 
@@ -106,9 +119,9 @@ Once you create an Azure OpenAI Resource, you must deploy a model before you can
 
 ### Prompt engineering
 
-The GPT-3, GPT-3.5 and GPT-4 models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text.
+The GPT-3, GPT-3.5, and GPT-4 models from OpenAI are prompt-based. With prompt-based models, the user interacts with the model by entering a text prompt, to which the model responds with a text completion. This completion is the model’s continuation of the input text.
 
-While these models are extremely powerful, their behavior is also very sensitive to the prompt. This makes [prompt engineering](./concepts/prompt-engineering.md) an important skill to develop.
+While these models are powerful, their behavior is also sensitive to the prompt. This makes [prompt engineering](./concepts/prompt-engineering.md) an important skill to develop.
 
 Prompt construction can be difficult. In practice, the prompt acts to configure the model weights to complete the desired task, but it's more of an art than a science, often requiring experience and intuition to craft a successful prompt.
 
diff --git a/articles/ai-services/translator/custom-translator/release-notes.md b/articles/ai-services/translator/custom-translator/release-notes.md
@@ -7,14 +7,118 @@ manager: nitinme
 ms.service: azure-ai-translator
 ms.custom:
   - ignite-2023
-ms.date: 12/06/2023
+ms.date: 11/01/2024
 ms.author: lajanuar
 ms.topic: release-notes
 ---
 # Custom Translator release notes
 
 This page presents the latest feature, improvement, bug fix, and known issue release notes for Custom Translator service.
 
+## 2024-November release
+
+### Language model updates
+
+* Language pairs are listed in the table below.
+
+* We encourage you to retrain your models accordingly for higher quality.
+
+|Source Language|Target Language|
+|:----|:----|
+|Afrikaans | English |
+|Bashkir | English |
+|Belarusian | English |
+|Bosnian | English |
+|Bulgarian | English |
+|Catalan | English |
+|Chhattisgarhi | English |
+|Croatian | English |
+|Czech | English |
+|Danish | English |
+|English | Afrikaans |
+|English | Bangla |
+|English | Belarusian |
+|English | Bosnian |
+|English | Bulgarian |
+|English | Catalan |
+|English | Chinese Simplified |
+|English | Croatian |
+|English | Czech |
+|English | Danish |
+|English | Dutch |
+|English | Faroese |
+|English | French |
+|English | German |
+|English | Hindi |
+|English | Icelandic |
+|English | Indonesian |
+|English | Italian |
+|English | Japanese |
+|English | Khmer |
+|English | Korean |
+|English | Kurdish (Central) |
+|English | Kyrgyz |
+|English | Lao |
+|English | Luxembourgish |
+|English | Macedonian |
+|English | Malay |
+|English | Manipuri |
+|English | Mongolian (Cyrillic) |
+|English | Norwegian |
+|English | Persian |
+|English | Polish |
+|English | Portuguese (Brazil) |
+|English | Romanian |
+|English | Russian |
+|English | Serbian (Latin) |
+|English | Slovak |
+|English | Slovenian |
+|English | Spanish |
+|English | Swedish |
+|English | Tamil |
+|English | Tatar |
+|English | Thai |
+|English | Turkish |
+|English | Ukrainian |
+|English | Uyghur |
+|English | Uzbek (Latin) |
+|Faroese | English |
+|French | English |
+|German | English |
+|Hindi | English |
+|Icelandic | English |
+|Indonesian | English |
+|Italian | English |
+|Kashmiri | English |
+|Khmer | English |
+|Kurdish (Central) | English |
+|Kyrgyz | English |
+|Lao | English |
+|Luxembourgish | English |
+|Macedonian | English |
+|Malay | English |
+|Manipuri | English |
+|Mongolian (Cyrillic) | English |
+|Norwegian | English |
+|Pashto | English |
+|Persian | English |
+|Polish | English |
+|Portuguese (Brazil) | English |
+|Romanian | English |
+|Russian | English |
+|Serbian (Latin) | English |
+|Slovak | English |
+|Slovenian | English |
+|Spanish | English |
+|Swedish | English |
+|Tamil | English |
+|Tatar | English |
+|Thai | English |
+|Turkmen | English |
+|Uyghur | English |
+|Uzbek (Latin) | English |
+|Vietnamese | English |
+
 ## 2023-December release
 
 ### December 2023 model updates
diff --git a/articles/ai-studio/how-to/develop/evaluate-sdk.md b/articles/ai-studio/how-to/develop/evaluate-sdk.md
@@ -432,8 +432,8 @@ result = evaluate(
     },
     # column mapping
     evaluator_config={
-        "column_mapping": {
-            "relevance": {
+        "relevance": {
+            "column_mapping": {
                 "query": "${data.queries}"
                 "ground_truth": "${data.ground_truth}"
                 "response": "${outputs.response}"
@@ -560,8 +560,8 @@ result = evaluate(
         "relevance": relevance_eval
     },
     evaluator_config={
-        "column_mapping": {
-            "default": {
+        "default": {
+            "column_mapping": {
                 "query": "${data.queries}"
                 "context": "${outputs.context}"
                 "response": "${outputs.response}"
diff --git a/articles/ai-studio/includes/install-cli.md b/articles/ai-studio/includes/install-cli.md
@@ -38,4 +38,9 @@ You can follow instructions [How to install the Azure CLI](/cli/azure/install-az
 After you install the Azure CLI, sign in using the ``az login`` command and sign-in using the browser:
 ```
 az login
+
+```
+Alternatively, you can log in manually via the browser with a device code.
+```
+az login --use-device-code
 ```
diff --git a/articles/machine-learning/concept-compute-target.md b/articles/machine-learning/concept-compute-target.md
@@ -92,7 +92,7 @@ When created, these compute resources are automatically part of your workspace,
 > [!NOTE]
 > To avoid charges when the compute is idle:
 > * For a compute *cluster*, make sure the minimum number of nodes is set to 0, or use [serverless compute](./how-to-use-serverless-compute.md).
-> * For a compute *instance*, [enable idle shutdown](how-to-create-compute-instance.md#configure-idle-shutdown).
+> * For a compute *instance*, [enable idle shutdown](how-to-create-compute-instance.md#configure-idle-shutdown). While stopping the compute instance stops the billing for compute hours, you'll still be billed for disk, public IP, and standard load balancer.
 
 ### Supported VM series and sizes
 
diff --git a/articles/machine-learning/how-to-create-compute-instance.md b/articles/machine-learning/how-to-create-compute-instance.md
@@ -62,7 +62,7 @@ Choose the tab for the environment you're using for other prerequisites.
 
 Creating a compute instance is a one time process for your workspace. You can reuse the compute as a development workstation or as a compute target for training. You can have multiple compute instances attached to your workspace.
 
-The dedicated cores per region per VM family quota and total regional quota, which applies to compute instance creation, is unified and shared with Azure Machine Learning training compute cluster quota. Stopping the compute instance doesn't release quota to ensure you are able to restart the compute instance. It isn't possible to change the virtual machine size of compute instance once it's created.
+The dedicated cores per region per VM family quota and total regional quota, which applies to compute instance creation, is unified and shared with Azure Machine Learning training compute cluster quota. Stopping the compute instance doesn't release quota to ensure you are able to restart the compute instance. A quota is a credit limit on Azure resources, not a capacity guarantee, Restarting a compute instance is still dependent on the available capacity of the region. If there is a capacity crunch in the region for the SKU, you may not be able to restart the compute instance.  It isn't possible to change the virtual machine size of compute instance once it's created.
 
 The fastest way to create a compute instance is to follow the [Create resources you need to get started](quickstart-create-resources.md).
 
diff --git a/articles/machine-learning/how-to-manage-compute-instance.md b/articles/machine-learning/how-to-manage-compute-instance.md
@@ -64,7 +64,7 @@ You can [enable automatic shutdown](how-to-create-compute-instance.md#configure-
 You can also [create a schedule](how-to-create-compute-instance.md#schedule-automatic-start-and-stop) for the compute instance to automatically start and stop based on a time and day of week.
 
 > [!TIP]
-> The compute instance has 120GB OS disk. If you run out of disk space, [use the terminal](how-to-access-terminal.md) to clear at least 1-2 GB before you stop or restart the compute instance. Please do not stop the compute instance by issuing sudo shutdown from the terminal. The temp disk size on compute instance depends on the VM size chosen and is mounted on /mnt.
+> The compute instance has 120GB OS disk. If you run out of disk space, [use the terminal](how-to-access-terminal.md) to clear at least 5 GB before you stop or restart the compute instance. Please do not stop the compute instance by issuing sudo shutdown from the terminal. The temp disk size on compute instance depends on the VM size chosen and is mounted on /mnt.
 
 # [Python SDK](#tab/python)
 
diff --git a/articles/search/search-region-support.md b/articles/search/search-region-support.md
@@ -94,7 +94,7 @@ You can create an Azure AI Search resource in any of the following Azure public
 | Australia Southeast​​​ |  | ✅ |  | |
 | East Asia​ | ✅ | ✅ | ✅ |  |
 | Southeast Asia​ ​ ​ | ✅ | ✅ | ✅ |  |
-| Central India | ✅ | ✅ | ✅ | S2, S3, S3HD, L1, L2 |
+| Central India | ✅ | ✅ | ✅ |  |
 | Jio India West​ ​ | ✅ | ✅ |  |
 | South India <sup>1</sup> |  | | ✅ |
 | Japan East  | ✅ | ✅ | ✅ |
diff --git a/articles/search/search-sku-tier.md b/articles/search/search-sku-tier.md
@@ -59,7 +59,6 @@ Currently, several regions are at capacity for specific tiers and can't be used
 
 | Region | Disabled tier (SKU) due to over-capacity | Suggested alternative |
 |--------|------------------------------------------|-----------------------|
-| Central India | S2, S3, S3HD, L1, L2| South India |
 | East US 2| Basic, S1| Central US |
 | South Central US | All tiers | Central US |
 | US Gov Virginia | All tiers | US Gov Arizona |

-Original file line number
+Diff line change
 | Australia Southeast |  | ✅ |  | |
 | East Asia | ✅ | ✅ | ✅ |  |
 | Southeast Asia   | ✅ | ✅ | ✅ |  |
 -| Central India | ✅ | ✅ | ✅ | S2, S3, S3HD, L1, L2 |
 +| Central India | ✅ | ✅ | ✅ |  |
 | Jio India West  | ✅ | ✅ |  |
 | South India <sup>1</sup> |  | | ✅ |
 | Japan East  | ✅ | ✅ | ✅ |