Azure OpenAI terminology

Author: eric-urban

articles/search/retrieval-augmented-generation-overview.md

@@ -232,7 +232,7 @@ A RAG solution that includes Azure AI Search can leverage [built-in data chunkin
 
   + ["Conversational Knowledge Mining" solution accelerator](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services), helps you create an interactive solution to extract actionable insights from post-contact center transcripts.
 
-  + ["Build your own copilot" solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator), leverages Azure Open AI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
+  + ["Build your own copilot" solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator), leverages Azure OpenAI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
 
     + [Client Advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md) all-in-one custom copilot empowers Client Advisor to harness the power of generative AI across both structured and unstructured data. Help our customers to optimize daily tasks and foster better interactions with more clients
 

articles/search/search-get-started-vector.md

@@ -437,7 +437,7 @@ Authorization: Bearer {{token}}
 Key points:
 
 - Documents in the payload consist of fields defined in the index schema.
-- Vector fields contain floating point values. The dimensions attribute has a minimum of 2 and a maximum of 3,072 floating point values each. This quickstart sets the dimensions attribute to 1,536 because that's the size of embeddings generated by the Open AI's **text-embedding-ada-002** model.
+- Vector fields contain floating point values. The dimensions attribute has a minimum of 2 and a maximum of 3,072 floating point values each. This quickstart sets the dimensions attribute to 1,536 because that's the size of embeddings generated by the Azure OpenAI **text-embedding-ada-002** model.
 
 ## Run queries
 

articles/search/search-what-is-azure-search.md

@@ -97,7 +97,7 @@ Or, try solution accelerators:
 
 + [**Conversational Knowledge Mining** solution accelerator](https://github.com/microsoft/Customer-Service-Conversational-Insights-with-Azure-OpenAI-Services), helps you create an interactive solution to extract actionable insights from post-contact center transcripts.
 
-+ [**Build your own copilot** solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator), leverages Azure Open AI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
++ [**Build your own copilot** solution accelerator](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator), leverages Azure OpenAI Service, Azure AI Search and Microsoft Fabric, to create custom copilot solutions.
 
   + [Client Advisor](https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator/blob/main/ClientAdvisor/README.md) all-in-one custom copilot empowers Client Advisor to harness the power of generative AI across both structured and unstructured data. Help our customers to optimize daily tasks and foster better interactions with more clients