Key Points
- Windows ML Public Preview Launch: Microsoft announces the public preview of Windows ML, a runtime optimized for on-device AI model inference, available on all Windows 11 machines worldwide.
- Simplified AI Development: Windows ML unifies the development process across diverse hardware, including CPUs, GPUs, and NPUs, from partners like AMD, Intel, NVIDIA, and Qualcomm.
- Enhanced Performance & Compatibility: The platform offers up to 20% improved performance compared to other model formats, ensuring seamless integration with existing models and workflows through ONNX and ONNX Runtime Engine.
Microsoft announced the public preview of Windows ML, a cutting-edge runtime designed to simplify the development and deployment of AI-infused applications on Windows 11 devices. This new platform, built on the foundations of ONNX Runtime Engine (ORT), empowers developers to leverage the diverse Windows hardware ecosystem, encompassing entry-level laptops, Copilot+ PCs, and high-end AI workstations. Windows ML is poised to revolutionize the way developers integrate AI into their applications, ensuring optimized performance across various client silicon, including CPUs, GPUs, and NPUs.
Windows ML was developed in collaboration with leading hardware vendors, including AMD, Intel, NVIDIA, and Qualcomm. These partnerships have enabled the seamless integration of their respective execution providers (EPs) into the platform. For instance, NVIDIA’s TensorRT EP promises up to 2x faster performance for AI workloads on NVIDIA RTX GPUs compared to previous implementations. Similarly, AMD’s and Intel’s EPs are designed to maximize the potential of their respective hardware, ensuring developers can effortlessly target the most suitable silicon for their specific workloads.
The Windows ML public preview introduces a unified framework, allowing developers to target all Windows 11 PCs currently available. This framework eliminates the need for multiple application builds to accommodate different silicon, as ONNX and execution providers are readily available on the device. Developers can now focus on innovation, rather than infrastructure management, with the platform handling the complexities of model deployment and optimization. Windows ML also features advanced silicon targeting, enabling developers to optimize for low-power, high-performance, or specific silicon configurations. This flexibility is set to further enhance with future updates, incorporating split processing capabilities.
In terms of performance, Windows ML boasts up to 20% improvement compared to other model formats, thanks to its foundation in ONNX and ONNX Runtime. The platform is designed to guarantee conformance and compatibility through partnerships with Independent Hardware Vendors (IHVs), ensuring developers can rely on consistent improvement and accuracy across builds. To support the development process, Microsoft is introducing a robust set of tools within the AI Toolkit for VS Code. These tools facilitate model conversion from PyTorch, quantization, optimization, and compilation, streamlining the preparation and deployment of high-performance models via Windows ML.
The public preview of Windows ML is now available globally, offering developers the opportunity to explore its capabilities and provide feedback. The preview includes two layers of APIs: the ML Layer for high-level runtime initialization and dependency management, and the Runtime Layer for low-level, fine-grained control over on-device inference. Developers can get started by installing the AI Toolkit, leveraging conversion and optimization templates, and exploring comprehensive documentation and code samples on Microsoft Learn.
Industry leaders, including Adobe, Bufferzone, and Filmora, have already expressed enthusiasm for Windows ML, highlighting its potential to simplify AI integration, reduce app footprints, and accelerate the development of AI-powered features. As Windows ML moves towards general availability later this year, Microsoft invites developers to participate in the journey, shaping the next wave of AI innovation on the Windows platform. The successful integration of Windows ML into the Windows ecosystem is expected to drive the creation of more sophisticated, efficient, and accessible AI applications, ultimately enhancing the user experience across the diverse range of Windows 11 devices.
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