Local AI on Any PC or Mac
Imagine running powerful AI applications on your laptop without the need for cloud dependency. This is the promise of Foundry Local, showcased in the Microsoft Mechanics video titled “Run local AI on any PC or Mac – Microsoft Foundry Local,” published on November 19, 2025. Led by Raji Rajagopalan, Microsoft CoreAI Vice President, the discussion uncovers how Foundry Local enables developers to leverage AI efficiently across various platforms without modifying their applications for different hardware configurations. Rajagopalan explains that the evolution of hardware and AI models now permits their operation on local devices, which significantly reduces latency and enhances data privacy—benefits that the Foundry Local SDK encapsulates effectively.
During the video, various use cases are explored, emphasizing scenarios where internet connectivity might be limited, such as during air travel or in remote areas. This approach also grants developers more predictable cost structures, sidestepping the necessity for cloud resources. However, while the capability to run AI locally is compelling, one might argue that more exploration of the long-term ecosystem support for new devices and updates from silicon partners could reinforce the sustainability of this approach, especially in an ever-evolving tech landscape.
The demonstration reveals the practical application of the Foundry Local SDK, as it simplifies the development process by eliminating complex cross-platform setups. The benefit of app portability is highlighted as crucial, allowing developers to focus primarily on the development rather than the varied device execution. The presentation of the healthcare concierge app exemplifies this seamlessly, yet it also surfaces the need for continued attention to legacy hardware optimizations, which although functional, do exhibit slower performance.
Rajagopalan further elaborates on how Foundry Local circumvents the typical device and platform restrictions by accommodating execution providers like NVIDIA, Intel, Qualcomm, and AMD within its unified ONNX-based runtime. Nevertheless, as promising as these advancements are, the discussion could have benefited from a closer look at potential security challenges inherent in such wide-scale data processing on personal devices.
To adapt Foundry Local on devices, users are provided straightforward installation instructions augmented by the AI Toolkit in Visual Studio Code, demonstrating Microsoft’s commitment to user-friendly experiences. Rajagopalan encourages developers to explore and integrate the SDK into their applications, easily transitioning from theory to practice through available resources like code samples published by Microsoft.