update

Author: mrbullwinkle

articles/ai-services/openai/includes/studio.md

@@ -5,20 +5,14 @@ description: Walkthrough on how to get started with Azure OpenAI and make your f
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: include
-ms.date: 11/15/2023
+ms.date: 09/19/2023
 ---
 
 ## Prerequisites
 
 - An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
 - An Azure OpenAI resource with a model deployed. For more information about model deployment, see the [resource deployment guide](../how-to/create-resource.md).
 
-> [!div class="nextstepaction"]
-> [I ran into an issue with the prerequisites.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=STUDIO&Pillar=AOAI&Product=gpt&Page=quickstart&Section=Prerequisites)
-
-> [!TIP]
-> Try out the new unified [Azure AI Studio (preview)](../../../ai-studio/what-is-ai-studio.md) which brings together capabilities from across multiple Azure AI services.
-
 ## Go to the Azure OpenAI Studio
 
 Navigate to Azure OpenAI Studio at <a href="https://oai.azure.com/" target="_blank">https://oai.azure.com/</a> and sign-in with credentials that have access to your Azure OpenAI resource. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
@@ -45,30 +39,23 @@ You can experiment with the configuration settings such as temperature and pre-r
 
 Azure OpenAI also performs content moderation on the prompt inputs and generated outputs. The prompts or responses may be filtered if harmful content is detected. For more information, see the [content filter](../concepts/content-filter.md) article.
 
-In the GPT-3 playground you can also view Python and curl code samples pre-filled according to your selected settings. Just select **View code** next to the examples dropdown. You can write an application to complete the same task with the OpenAI Python SDK, curl, or other REST API client.
+In the Completions playground you can also view Python and curl code samples pre-filled according to your selected settings. Just select **View code** next to the examples dropdown. You can write an application to complete the same task with the OpenAI Python SDK, curl, or other REST API client.
 
 ### Try text summarization
 
-To use the Azure OpenAI for text summarization in the GPT-3 Playground, follow these steps:
+To use the Azure OpenAI for text summarization in the Completions playground, follow these steps:
 
 1. Sign in to [Azure OpenAI Studio](https://oai.azure.com).
 1. Select the subscription and OpenAI resource to work with. 
-1. Select **GPT-3 Playground** at the top of the landing page.
+1. Select **Completions playgrond** on the landing page.
 1. Select your deployment from the **Deployments** dropdown. If your resource doesn't have a deployment, select **Create a deployment** and then revisit this step.
-1. Select **Summarize Text** from the **Examples** dropdown. 
+1. Enter a prompt for the model.
 
-    :::image type="content" source="../media/quickstarts/summarize-text.png" alt-text="Screenshot of the playground page of the Azure OpenAI Studio with the Summarize Text dropdown selection visible" lightbox="../media/quickstarts/summarize-text.png":::
+    :::image type="content" source="../media/quickstarts/summarize-text.png" alt-text="Screenshot of the playground page of the Azure OpenAI Studio with a text summarization example" lightbox="../media/quickstarts/summarize-text.png":::
 
 1. Select `Generate`. Azure OpenAI will attempt to capture the context of text and rephrase it succinctly. You should get a result that resembles the following text:
 
-    ```
-    Tl;dr A neutron star is the collapsed core of a supergiant star. These incredibly dense objects are incredibly fascinating due to their strange properties and their potential for phenomena such as extreme gravitational forces and a strong magnetic field.
-    ```
-
-The accuracy of the response can vary per model. The Davinci based model in this example is well-suited to this type of summarization, whereas a Codex based model wouldn't perform as well at this particular task.
-
-> [!div class="nextstepaction"]
-> [I ran into an issue with the playground.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=STUDIO&Pillar=AOAI&Product=gpt&Page=quickstart&Section=Set-up)
+The accuracy of the response can vary per model. The `gpt-35-turbo-instruct` based model in this example is well-suited to this type of summarization, though in general we recommend using the alternate chat completions API unless you have a particular use case that is particularly suited to the completions API.
 
 ## Clean up resources