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Enhancing Windows Applications with AI: A Comprehensive Guide

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This article presents a collection of samples demonstrating various ways to enhance Windows applications using local APIs, machine learning models, DirectML for local hardware acceleration, and cloud-based APIs. It includes practical examples such as AI-based audio editing, note-taking apps, and image generation, showcasing the integration of AI functionalities in Windows applications.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Comprehensive coverage of AI integration in Windows applications
    • 2
      Diverse application examples across various domains
    • 3
      Clear explanations of technical implementations and functionalities

  • • unique insights

    • 1
      Innovative use of local ML models for audio transcription and semantic search
    • 2
      Application of RAG (Retrieval-Augmented Generation) for grounding language models in real data

  • • practical applications

    • The article provides practical guidance for developers looking to implement AI features in Windows apps, with step-by-step instructions and real-world use cases.

  • • key topics

    • 1
      Local API integration
    • 2
      Machine Learning models in Windows apps
    • 3
      DirectML for hardware acceleration

  • • key insights

    • 1
      Demonstrates practical AI applications in real-world scenarios
    • 2
      Covers both local and cloud-based AI functionalities
    • 3
      Provides a variety of sample applications for different use cases

  • • learning outcomes

    • 1
      Understand how to integrate AI functionalities in Windows applications
    • 2
      Learn to implement local ML models and DirectML for hardware acceleration
    • 3
      Explore innovative AI applications through practical examples
examples
tutorials
code samples
visuals
fundamentals
advanced content
practical tips
best practices

“ Introduction to Windows AI Enhancements

In recent years, artificial intelligence (AI) has transformed the landscape of software development, particularly in enhancing user experiences within applications. Windows provides a robust framework for developers to integrate AI capabilities into their applications, leveraging local APIs and machine learning (ML) models.

“ Utilizing Local APIs and Machine Learning

Windows developers can utilize local APIs and machine learning models to create applications that are not only responsive but also intelligent. DirectML, a key component, allows for hardware-accelerated AI processing, enabling applications to perform complex tasks efficiently on local hardware.

“ AI-Based Applications Overview

This section explores various AI-based applications that have been developed using Windows technologies. These applications range from audio editing tools to note-taking systems, all designed to leverage the power of AI for improved functionality.

“ Sample Applications and Their Features

1. **AI-Based Audio Editor**: This application demonstrates how to build a WinUI 3 audio editing app that uses AI to match audio snippets with relevant queries. It employs local ML model inference for transcription and semantic search. 2. **AI-Based Notes App**: This app showcases OCR text recognition, audio transcription, and semantic search using local ML models, providing users with a comprehensive tool for note-taking. 3. **RAG PDF Analyzer**: This WPF sample app uses a local language model to answer questions about PDF document content, demonstrating the retrieval-augmented generation (RAG) pattern.

“ Integrating Cloud APIs for Enhanced Functionality

In addition to local capabilities, Windows applications can also integrate cloud-based APIs to enhance their functionality. For instance, developers can add OpenAI's chat completion features or DALL-E image generation capabilities to their applications, expanding the range of services offered.

“ Conclusion and Future Directions

The integration of AI into Windows applications is a rapidly evolving field. As developers continue to explore the capabilities of local APIs and machine learning, the potential for innovative applications is vast. Future developments may include more sophisticated AI models and enhanced hardware acceleration techniques.

 Original link: https://learn.microsoft.com/ko-kr/windows/ai/samples/

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