Microsoft has launched Windows ML, an AI framework designed to integrate AI models into Windows applications, allowing local inferences on various hardware, including CPUs, GPUs, and NPUs. It abstracts hardware complexities to optimize performance across devices and supports AI formats like ONNX for compatibility with multiple vendors. Windows ML integrates with the Windows App SDK and offers APIs in languages such as C#, C++, and Python, facilitating the development of AI-enhanced applications. Performance benchmarks indicate up to 4x faster inference on NPUs compared to CPUs. The framework aims to create a hybrid AI ecosystem, balancing local and cloud processing. Windows 11’s 24H2 update requires NPU support in Copilot+ PCs, aligning with edge computing trends. Microsoft’s strategy emphasizes cross-hardware compatibility, potentially benefiting enterprise environments. Challenges remain in model training and security, and Microsoft plans to enhance Windows ML with future updates.