AI for Windows apps

Learn how to take advantage of state-of-the-art local models, NPU hardware, and remote APIs to make your apps smarter than ever before.

Overview

Microsoft AI learning hub

What's new

Microsoft Copilot learning hub

Concept

Microsoft Responsible AI

video

Microsoft AI Show Live

Explore the latest AI innovations with Windows

Guidance on responsibly integrating AI features into your Windows apps, including the Windows Copilot Runtime.

Introducing AI for Windows

Learn more about the possibilities.

• FAQs about using AI on Windows
• Get started using AI-backed APIs locally or in the cloud
• Get started using ML models in your app
• Responsible Generative AI Development on Windows
• AI on Windows Sample Gallery
• Our principles for using AI-generated content on Microsoft Learn

Writing apps using local AI models

Find guidance on how to run ML models in your Windows app and make the most of Copilot+ PCs.

• Copilot+ PCs Developer Guide
• Web Neural Network API (WebNN) Overview
• Get started with WebNN with Windows
• DirectML expands NPU support to Copilot+ PCs and WebNN
• Find pre-built ML models
• AI Toolkit for Visual Studio Code overview

The Windows Copilot Runtime

AI features made easy.

• Overview of Windows Copilot Runtime
• Phi Silica API - Small Language Model with reasoning and language understanding
• Text Recognition API (Optical Character Recognition / OCR)
• Recall API - Retrieval of past activities for user to continue where they left off
• Studio Effects - NPU-accelerated camera and microphone AI effects

Writing apps using hosted AI models

Make use of AI models running in the cloud.

• Build cutting-edge, market-ready AI applications.
• Develop AI apps with .NET
• Introduction to Semantic Kernel
• OpenAI basic samples

DirectML for hardware-accelerated Machine Learning

Integrate Machine Learning (ML) inferencing workloads into your game, engine, middleware, backend, or other applications. DirectML is a low-level API supported by all DirectX 12-compatible hardware.

Overview

Guidance to help you discern whether DirectML is appropriate for your project, the workflow, and how to get started.

• DirectML Overview
• Get started with DirectML
• DirectML Version History
• DirectML developer tools
• Sample applications

DirectML Programming Guide

DirectML executes layers of your inference model as operators. Learn more about programming DirectML.

• Binding in DirectML
• UAV barriers and resource state barriers
• Resource lifetime and synchronization
• Using strides to express padding, memory layout
• Using fused operators to improve performance
• Troubleshooting - using the debug layer
• Troubleshooting - Handling errors and device removal

DirectML support for PyTorch or WebNN

Guidance on how to use DirectML with PyTorch or WebNN.

• Enable PyTorch with DirectML on Windows
• Enable PyTorch with DirectML on WSL 2
• DirectML expands NPU support to Copilot+ PCs and WebNN

API Reference

API Reference for DirectML.

• DirectML interfaces
• DirectML functions
• DirectML structures
• DirectML enumerations
• DirectML constants