cleaning up images

Author: aahill

articles/ai-services/openai/concepts/provisioned-migration.md

@@ -50,14 +50,10 @@ Provisioned quota granularity is changing from model-specific to model-independe
 
 Starting August 12, 2024, existing customers will have their current, model-specific quota converted to model-independent. This will happen automatically and be complete by August 14, 2024. No quota will be lost in the transition. Existing quota limits will be summed and assigned to a new model-independent quota item.
 
-<!--:::image type="content" source="./media/provisioned/model-independent-quota.png" alt-text="Diagram of model independent quota with one pool of PTUs available to multiple Azure OpenAI models." lightbox="./media/provisioned/model-independent-quota.png":::-->
-
 :::image type="content" source="../media/provisioned/consolidation.png" alt-text="Diagram showing quota consolidation." lightbox="../media/provisioned/consolidation.png":::
 
 The new model-independent quota will show up as a quota item named **Provisioned Managed Throughput Unit**, with model and version no longer included in the name. In the Studio Quota pane, expanding the quota item will still show all of the deployments that contribute to the quota item. 
 
-<!--:::image type="content" source="./media/provisioned/quota.png" alt-text="Screenshot of the quota UI for Azure OpenAI provisioned." lightbox="./media/provisioned/quota.png":::-->
-
 ### Default quota
 
 New and existing subscriptions will be assigned a small amount of provisioned quota in many regions. This allows customers to start using those regions without having to first request quota.

articles/ai-services/openai/concepts/provisioned-throughput.md

@@ -103,8 +103,6 @@ To help users find the capacity needed for their deployments, customers will use
 
 In Azure OpenAI Studio, the deployment experience will identify when a region lacks the capacity to support the desired model, version and number of PTUs, and will direct the user to a select an alternative region when needed.
 
-<!--:::image type="content" source="../media/provisioned/check-capacity.png" alt-text="Screenshot of the check capacity experience for quota for Azure OpenAI provisioned." lightbox="../media/provisioned/check-capacity.png":::-->
-
 Details on the new deployment experience can be found in the Azure OpenAI [Provisioned get started guide](../how-to/provisioned-get-started.md).
 
 The new [model capacities API](/rest/api/aiservices/accountmanagement/model-capacities/list?view=rest-aiservices-accountmanagement-2024-04-01-preview&tabs=HTTP&preserve-view=true) can also be used to programmatically identify the maximum sized deployment of a specified model that can be created in each region based on the availability of both quota in the subscription and service capacity in the region.
@@ -160,7 +158,7 @@ For Provisioned-Managed, we use a variation of the leaky bucket algorithm to mai
 4.	The overall utilization is decremented down at a continuous rate based on the number of PTUs deployed. 
 
 > [!NOTE]
-> Calls are accepted until utilization reaches 100%. Bursts just over 100% maybe permitted in short periods, but over time, your traffic is capped at 100% utilization.
+> Calls are accepted until utilization reaches 100%. Bursts just over 100% may be permitted in short periods, but over time, your traffic is capped at 100% utilization.
 
 
 :::image type="content" source="../media/provisioned/utilization.jpg" alt-text="Diagram showing how subsequent calls are added to the utilization." lightbox="../media/provisioned/utilization.jpg":::

articles/ai-services/openai/how-to/provisioned-get-started.md

@@ -48,7 +48,7 @@ Additional quota can be requested by clicking the Request Quota link to the righ
 Provisioned Throughput deployments are created via Azure OpenAI resource objects within Azure. You must have an Azure OpenAI resource in each region where you intend to create a deployment. Use the Azure portal to [create a resource](./create-resource.md) in a region with available quota, if required.  
 
 > [!NOTE]
-> Azure OpenAI resources can be support multiple types of Azure OpenAI deployments at the same time.  It is not necessary to dedicate new resources for your provisioned deployments. 
+> Azure OpenAI resources can support multiple types of Azure OpenAI deployments at the same time.  It is not necessary to dedicate new resources for your provisioned deployments. 
 
 ## Create your provisioned deployment - capacity is available
 

articles/ai-services/openai/how-to/provisioned-throughput-onboarding.md

@@ -61,7 +61,7 @@ Azure OpenAI Provisioned is purchased on-demand at an hourly basis based on the
 The hourly model is useful for short-term deployment needs, such as validating new models or acquiring capacity for a hackathon.  However, the discounts provided by the Azure Reservation for Azure OpenAI Provisioned are considerable and most customers with consistent long-term usage will find a reserved model to be a better value proposition. 
 
 > [!NOTE]
-> Azure OpenAI Provisioned customers onboarded prior to the August self-service update use a purchase model called the Commitment model.  These customers may continue to use this older purchase model alongside the Hourly/reservation purchase model.  The Commitment model is not available for new customers.  For details on the Commitment purchase model and options for coexistence and migration, please see the [Azure OpenAI Provisioned August Update](./provisioned-migration.md).
+> Azure OpenAI Provisioned customers onboarded prior to the August self-service update use a purchase model called the Commitment model.  These customers can continue to use this older purchase model alongside the Hourly/reservation purchase model.  The Commitment model is not available for new customers.  For details on the Commitment purchase model and options for coexistence and migration, please see the [Azure OpenAI Provisioned August Update](./provisioned-migration.md).
 
 ## Hourly Usage  
 
@@ -80,11 +80,11 @@ Customers that require long-term usage of provisioned deployments, however, migh
 > [!NOTE]
 > It is not recommended to scale production deployments according to incoming traffic and pay for them purely on an hourly basis. There are two reasons for this:
 > * The cost savings achieved by purchasing an Azure Reservation for Azure OpenAI Provisioned are significant, and it will be less expensive in many cases to maintain a deployment sized for full production volume paid for via a reservation than it would be to scale the deployment with incoming traffic.
-> * Having unused provisioned quota (PTUs) does not guarentee that capacity will be available to support increasing the size of the deployment when required. Quota limits the maximum number of PTUs that may be deployed, but it is not a capacity guarantee. Provisioned capacity for each region and modal dynamically changes throughout the day and may not be available when required. As a result, it is recommended to maintain a permanant deployment to cover your traffic needs (paid for via a reservation).
+> * Having unused provisioned quota (PTUs) does not guarentee that capacity will be available to support increasing the size of the deployment when required. Quota limits the maximum number of PTUs that can be deployed, but it is not a capacity guarantee. Provisioned capacity for each region and modal dynamically changes throughout the day and might not be available when required. As a result, it is recommended to maintain a permanant deployment to cover your traffic needs (paid for via a reservation).
 
 ## Azure Reservations for Azure OpenAI Provisioned   
 
-Discounts on top of the hourly usage price may be obtained by purchasing an Azure Reservation for Azure OpenAI Provisioned. An Azure Reservation is a term-discounting mechanism shared by many Azure products. For example, Compute and Cosmos DB. For Azure OpenAI Provisioned, the reservation provides a discount for committing to payment for fixed number of PTUs for a one-month or one-year period.  
+Discounts on top of the hourly usage price can be obtained by purchasing an Azure Reservation for Azure OpenAI Provisioned. An Azure Reservation is a term-discounting mechanism shared by many Azure products. For example, Compute and Cosmos DB. For Azure OpenAI Provisioned, the reservation provides a discount for committing to payment for fixed number of PTUs for a one-month or one-year period.  
 
 * Azure Reservations are purchased via the Azure portal, not Azure OpenAI Studio  Link to Azure reservation portal. 
 
@@ -98,7 +98,7 @@ Discounts on top of the hourly usage price may be obtained by purchasing an Azur
 
 * New reservations can be purchased to cover the same scope as existing reservations, to allow for discounting of new provisioned deployments.  The scope of existing reservations can also be updated at any time without penalty, for example to cover a new subscription. 
 
-* Reservations may be canceled after purchase, but credits are limited.   
+* Reservations can be canceled after purchase, but credits are limited.   
 
 * If the size of provisioned deployments within the scope of a reservation exceeds the amount of the reservation, the excess is charged at the hourly rate. For example, if deployments amounting to 250 PTUs exist within the scope of a 200 PTU reservation, 50 PTUs will be charged on an hourly basis until the deployment sizes are reduced to 200 PTUs, or a new reservation is created to cover the remaining 50.