made adjusments based on feedback

Author: hhreyes21

learn-pr/device-partner-university/introduction-microsoft-foundry-windows/includes/4-how-microsoft-foundry-windows-works.md

@@ -2,7 +2,7 @@ Microsoft Foundry on Windows is designed as a layered platform that enables deve
 
 Rather than requiring developers to manage models, runtimes, and hardware acceleration independently, the platform provides a structured stack that simplifies how AI workloads are developed and deployed on Windows devices.
 
-:::image type="content" source="../media/developer-it-laptop.png" alt-text="Developer working on a laptop in a modern workspace, with code and development tools visible on external monitors, illustrating how AI capabilities can be integrated into Windows applications using a layered platform approach.":::
+:::image type="content" source="../media/developer-it-laptop.png" alt-text="A photograph of a Developer working on a laptop in a modern workspace, with code and development tools visible on external monitors, illustrating how AI capabilities can be integrated into Windows applications using a layered platform approach.":::
 
 At a high level, Microsoft Foundry on Windows consists of three primary layers:
 

learn-pr/device-partner-university/introduction-microsoft-foundry-windows/includes/5-when-use-microsoft-foundry-windows.md

@@ -17,9 +17,9 @@ Local execution can reduce response time by running inference close to the user
 
 Running models on the device can also support data handling requirements. When inference occurs locally, application data doesn't need to be transmitted to external services, which can help address privacy considerations or regulatory constraints.
 
-The following example shows how Foundry Local can support scenarios where sensitive data should remain on the device. In this case, a developer runs an open model locally to process student financial aid requests without relying on cloud inference.
+The following example illustrates how developers can explore local AI capabilities by using developer tools before integrating them into an application. In this scenario, a developer uses AI Dev Gallery to try Windows AI APIs locally, evaluating features such as text generation or text recognition without relying on cloud-based inference.
 
-:::image type="content" source="../media/foundry-local-financial-aid-demo.gif" alt-text="Example showing a developer running an open model locally with Foundry Local to process sensitive financial aid requests on a Windows device.":::
+:::image type="content"source="../media/ai-dev-gallery-local-inference-demo.gif" alt-text="Example showing AI Dev Gallery interface showing a developer exploring Windows AI APIs locally on a Windows device,with sample inputs and outputs displayed in a development environment." lightbox="../media/ai-dev-gallery-local-inference-demo.gif":::
 
 Common scenarios where local AI may be appropriate include:
 
@@ -48,8 +48,6 @@ Microsoft Foundry on Windows supports hybrid architectures by enabling local exe
 
 This model can be useful for organizations that want to introduce AI capabilities incrementally or avoid designing applications that depend entirely on cloud infrastructure.
 
-This model can be useful for organizations that want to introduce AI capabilities incrementally or avoid designing applications that depend entirely on cloud infrastructure.
-
 ## Use Microsoft Foundry on Windows when targeting diverse hardware environments
 
 Windows applications often need to run across a wide range of devices and hardware configurations, including enterprise laptops, workstations, and specialized edge systems.