Windows AI Studio | STUDIO11

Microsoft Ignite
17 Nov 202309:45

TLDRWindows AI Studio is a suite of advanced tools and AI models, including those from Hugging Face and Azure AI Studio, designed for developers to discover, integrate, optimize, and deploy AI models in Windows applications. It enables local AI execution on devices, supporting scenarios like video editing, photo editing, and real-time video conferencing effects. The platform offers models like LAMa2, Microsoft's own Fu, and others, with no cloud involvement, ensuring local machine processing. It simplifies generative AI app development, providing a model catalog and tools in one place, and will be accessible via a Visual Studio Code extension.

Takeaways

  • 🚀 Windows AI Studio is a suite of advanced tools combined with AI models from sources like Hugging Face and Azure AI Studio.
  • 🔍 Developers can discover, integrate, optimize, and deploy AI models natively within Windows applications.
  • 🎯 The platform targets scenarios requiring real-time precision, such as video editing, photo editing, and advanced video conferencing effects.
  • 🌐 AI models run locally on Windows devices, offering privacy and speed advantages.
  • 💡 Edge AI is highlighted, utilizing the millions of GPUs and the emerging NPU (Neural Processing Unit) technology in Windows machines.
  • 🧠 Examples of AI models include summarization models for confidential documents and other advanced AI capabilities like LAMa2, Microsoft's own model, and more.
  • 🛠️ Windows AI Studio simplifies generative AI app development, providing a model catalog and integrated toolset.
  • 🔧 In two weeks, developers will be able to try Windows AI Studio through a Visual Studio Code extension.
  • 📈 The Windows platform, with its scale and optimized toolchains, is positioned as an ideal environment for AI development.
  • 🔗 Interested parties can learn more and access the upcoming extension at the Windows AI Studio website.

Q & A

  • What is Windows AI Studio?

    -Windows AI Studio is a collection of cutting-edge tooling paired with AI models from repositories like Hugging Face and Azure AI Studio, designed for developers to discover, integrate, optimize, and deploy AI models in a Windows-optimized fashion within their applications.

  • How does Windows AI Studio benefit developers?

    -Windows AI Studio simplifies generative AI app development by providing a centralized platform with a model catalog and toolset, enabling developers to easily get started with AI and create AI-driven applications without the complexity of selecting the right toolset or models.

  • Is Windows AI Studio limited to Windows or does it involve cloud computing?

    -Windows AI Studio is focused on local development, running AI models directly on a Windows machine without any cloud computing involvement.

  • What kind of AI models can be used with Windows AI Studio?

    -Developers can use a variety of AI models with Windows AI Studio, including LAMa2 models, Microsoft's own F缕 model, and other models like mral Falcon.

  • How does Windows AI Studio support edge AI development?

    -Windows AI Studio supports edge AI development by enabling AI models to run on the edge, specifically on the processor of a Windows machine, utilizing GPUs and neural processing units (NPUs) designed for AI workloads.

  • What is the role of the Windows Subsystem for Linux in AI development?

    -The Windows Subsystem for Linux provides a robust platform for developers to run both Linux and Windows workloads simultaneously on a Windows machine, allowing for easy sharing of GUI apps, GPU, and files between the two environments without additional setup.

  • How does Windows AI Studio address the challenge of getting started with AI for developers?

    -By bringing together a curated model catalog and a comprehensive toolset, Windows AI Studio reduces the complexity and effort required for developers to begin working with AI, making it easier to start generating AI applications.

  • What tools does Windows AI Studio provide for local AI model fine-tuning?

    -Windows AI Studio includes tools like Kora through Olive for generating quantized models with low-rank adapters, as well as model evaluation and optimization features, all of which can be performed locally on a Windows device.

  • How soon will developers be able to try Windows AI Studio?

    -Developers will be able to try Windows AI Studio in about two weeks through a Visual Studio Code extension, which will be available to those with a GitHub account.

  • What was the experience of using Windows AI Studio like for the host of the discussion?

    -The host found the experience of using Windows AI Studio to be straightforward and impressive. They were able to set up an entire fine-tuning environment on their Windows machine, including code generation and Dockerization, without using the Windows Subsystem for Linux.

  • How can interested parties learn more about Windows AI Studio?

    -People interested in Windows AI Studio can visit the official website and look out for the Visual Studio Code extension in the coming weeks to learn more and get started with the platform.

Outlines

00:00

🤖 Introducing Windows AI Studio and Its Capabilities

This paragraph introduces Windows AI Studio, a suite of advanced tools combined with AI models sourced from repositories like Hugging Face and Azure AI Studio. The focus is on empowering developers to discover, integrate, optimize, and deploy AI models within Windows-optimized applications. The conversation highlights the benefits of running AI models locally on Windows devices, emphasizing scenarios like video editing, photo editing, and real-time applications. It also touches on the edge computing aspect of AI, where neural processing units (NPUs) are utilized for on-device AI processing. Examples of AI models like LAMa, Microsoft's in-house model, and others are mentioned, showcasing the variety of tools available to developers.

05:01

🚀 Making Windows the Premier Platform for AI Development

This segment discusses the advantages of using Windows for AI development, citing the vast number of active GPUs and the comprehensive toolchains provided by the platform. It emphasizes the ease of development, with Windows AI Studio simplifying generative AI app development by combining a model catalog and a toolset in one place. The conversation also includes a personal anecdote from the host, who shares their experience of quickly setting up and fine-tuning an AI model using Windows AI Studio without the need for the Windows Subsystem for Linux. The paragraph concludes with information on how developers can access Windows AI Studio through a Visual Studio Code extension and a GitHub account.

Mindmap

Keywords

💡Windows AI Studio

Windows AI Studio is a suite of advanced tools and AI models designed to empower developers to integrate AI capabilities into their applications. It provides a comprehensive environment for discovering, integrating, optimizing, and deploying AI models in a Windows-optimized manner. The platform leverages cutting-edge technology and AI models from repositories like Hugging Face and Azure AI Studio, aiming to simplify the process of bringing AI to Windows applications. This is exemplified in the script where it's mentioned that developers can utilize Windows AI Studio to embed advanced studio effects into their apps with real-time precision.

💡AI models

AI models refer to the algorithms and data structures that are trained to perform specific tasks, such as image recognition, natural language processing, or predictive analytics. In the context of the video, AI models are the core components that developers can discover and integrate into their applications using Windows AI Studio. These models can be sourced from various repositories and can be fine-tuned and optimized to run efficiently on Windows devices.

💡Hugging Face

Hugging Face is an open-source platform that provides a wide range of pre-trained AI models, particularly in the field of natural language processing. These models can be used for various tasks, such as text summarization, sentiment analysis, and chatbot creation. In the video, Hugging Face is mentioned as one of the repositories from which Windows AI Studio sources AI models, highlighting its role in the broader AI ecosystem.

💡Fine-tuning

Fine-tuning is the process of adjusting a pre-trained AI model to better perform on a specific task or dataset. This involves retraining the model with new data to improve its accuracy and relevance for the intended application. In the context of the video, fine-tuning is a critical step in the AI development process within Windows AI Studio, allowing developers to tailor AI models to their specific needs and ensure optimal performance on Windows devices.

💡Neural Processing Units (NPUs)

Neural Processing Units (NPUs) are specialized hardware components designed to efficiently execute AI model workloads. They are particularly suited for tasks that involve deep learning and neural network computations. In the video, NPUs are mentioned as a key component of Windows machines, highlighting the growing trend of integrating AI-specific hardware into mainstream computing devices to enhance their capabilities in running AI models.

💡Edge AI

Edge AI refers to the concept of running AI algorithms and models on devices at the 'edge' of a network, rather than relying on centralized cloud-based processing. This approach allows for faster response times and can be particularly useful in scenarios where real-time processing is crucial. In the video, edge AI is discussed in the context of running AI models directly on Windows machines, leveraging the power of GPUs and NPUs for localized AI processing.

💡Linux

Linux is a free and open-source operating system that is widely used in the world of computing, especially in servers and supercomputers. It is known for its stability, security, and flexibility. In the context of the video, Linux is mentioned as a platform traditionally associated with AI development. However, the Windows subsystem for Linux is introduced as a way to bridge the gap, allowing developers to run Linux and Windows workloads simultaneously on a Windows machine, thus expanding the capabilities for AI development on Windows.

💡Visual Studio Code extension

A Visual Studio Code extension is a software component that adds new features or functionality to the Visual Studio Code integrated development environment (IDE). Extensions can range from debugging tools to language support, and they are designed to enhance the developer's experience and productivity. In the video, the mention of a Visual Studio Code extension for Windows AI Studio indicates that developers will soon be able to access the AI Studio's capabilities directly within the Visual Studio Code environment, streamlining the process of developing AI applications on Windows.

💡Generative AI app development

Generative AI app development refers to the process of creating applications that utilize AI models to generate new content, such as text, images, or audio. This type of development often involves training AI models on large datasets to produce outputs that are not pre-defined but are instead created based on patterns learned from the data. In the video, generative AI app development is presented as the main focus of Windows AI Studio, with the platform aiming to simplify the process for developers by providing a comprehensive environment for model integration, optimization, and deployment.

💡GitHub account

A GitHub account is a user profile on GitHub, a web-based platform for version control and collaboration that allows developers to manage and share their code. GitHub is widely used in the software development community for hosting and reviewing code, managing projects, and building software collaboratively. In the video, the mention of a GitHub account indicates that developers will need one to access and utilize the Visual Studio Code extension for Windows AI Studio, emphasizing the importance of GitHub in the modern software development workflow.

Highlights

Windows AI Studio is a collection of cutting-edge tooling paired with AI models from repositories like Hugging Face and Azure AI Studio.

Developers can discover, integrate, optimize, and deploy AI models in a Windows-optimized fashion within their applications.

The focus of Windows AI Studio is on running AI models locally on Windows machines,而非云端.

Windows AI Studio is beneficial for scenarios requiring real-time precision, such as video editing, photo editing, or enhancing video conferencing apps with advanced studio effects.

Edge AI refers to running AI models on the processor of a Windows machine, utilizing GPUs and神经处理单元 (NPUs) for AI workloads.

Examples of AI models that can be used include summarization models for confidential documents, LAMa2 models, Microsoft's own Fugou model, and more.

Windows AI Studio promotes the use of the Windows subsystem for Linux, allowing developers to run Linux and Windows workloads simultaneously.

The platform is designed to make Windows the best place for AI developers, with a large scale of active GPUs and optimized tool chains.

Windows AI Studio simplifies generative AI app development, providing a model catalog and toolset in one place for developers.

Developers can expect a VS Code extension for Windows AI Studio in about two weeks, making it easy to get started with AI development on Windows.

The Windows AI Studio environment includes fine-tuning locally on Windows machines without the need for the Windows subsystem for Linux.

The platform enables model evaluation and optimization to be done locally, with tools like Olive embedded into the workspace.

An example is provided where a host set up an AI model fine-tuning environment on their Windows machine in just an hour.

The process of fine-tuning involved code generation, Dockerization, and training on a Windows machine's GPU without using the Windows subsystem for Linux.

The host's experience demonstrates the ease and speed of setting up and interacting with AI models using Windows AI Studio, including the use of prom flow for model interaction.

Developers can look forward to learning more about Windows AI Studio through an upcoming Visual Studio Code extension and the Windows AI Studio website.

To get started with Windows AI Studio, a GitHub account is all that is needed, showcasing its accessibility for developers.

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