Update fdp-backward-compatibility-azure-openai.md

Author: ShawnJackson

articles/ai-foundry/includes/fdp-backward-compatibility-azure-openai.md

@@ -11,18 +11,16 @@ ms.custom: include file
 ---
 
 > [!CAUTION]
-> See the following information about backward compatibility for Azure OpenAI users who onboarded to the Azure AI Foundry developer platform:
+> Users who previously managed their model deployments and ran evaluations by using `oai.azure.com`, and then onboarded to the Azure AI Foundry developer platform, have these limitations when they use `ai.azure.com`:
 >
-> Users who previously managed their model deployments and ran evaluations by using `oai.azure.com` and have since onboarded to the Azure AI Foundry developer platform have a few limitations when using `ai.azure.com`:
+> - These users can't view their evaluations that were created through the Azure OpenAI API. To view these evaluations, they have to go back to `oai.azure.com`.
+> - These users can't use the Azure OpenAI API to run evaluations within Azure AI Foundry. Instead, they should continue to use `oai.azure.com` for this task. However, they can use the Azure OpenAI evaluators that are available directly in Azure AI Foundry (`ai.azure.com`) in the option for dataset evaluation creation. The option for fine-tuned model evaluation isn't supported if the deployment is a migration from Azure OpenAI to Azure AI Foundry.
 >
-> - Users are unable to view their evaluations that were created by using the Azure OpenAI API. To view these evaluations, users have to navigate back to `oai.azure.com`.
-> - Users are unable to use the Azure OpenAI API to run evaluations within Azure AI Foundry. Instead, these users should continue to use `oai.azure.com` for this task. However, users can use the Azure OpenAI evaluators that are available directly in Azure AI Foundry (`ai.azure.com`) in the dataset evaluation creation option. The fine-tuned model evaluation option isn't supported if the deployment is a migration from Azure OpenAI to Azure AI Foundry.
->
-> For the dataset upload and bring your own storage scenario, there are a few configuration requirements:
+> For the scenario of dataset upload and bring your own storage, there are a few configuration requirements:
 >
 > - Account authentication must be Microsoft Entra ID.
-> - The storage must be added to the account, because if it's added to the project, you get service errors.
-> - The user must add their project to their storage account through access control in the Azure portal.
+> - The storage must be added to the account. Adding it to the project causes service errors.
+> - Users must add their project to their storage account through access control in the Azure portal.
 >
 > To learn more about creating evaluations with OpenAI evaluation graders in the Azure OpenAI hub, see [How to use Azure OpenAI in Azure AI Foundry models evaluation](../../ai-services/openai/how-to/evaluations.md).