Arm Holdings Limited (NASDAQ stock code: ARM， Arm (hereinafter referred to as "Arm") announced that it has officially launched a new extension designed specifically for GitHub Copilot. GitHub Copilot is one of the most widely deployed artificial intelligence (AI) developer tools globally, and the newly launched extension will make it easier for millions of Copilot users to access Arm? Architecture technology and providing developers with a more user-friendly experience. In addition, this release also provides for the first time a complete CI/CD workflow based on the Arm platform for global developers free of charge, including GitHub Actions, Arm Runners, and Arm extensions for GitHub Copilot. Alex Spinelli, Senior Vice President of Artificial Intelligence Platforms and Developer Platforms and Services at Arm, said, "In today's fast-paced technological environment, developers need tools that can simplify workflows, reduce costs, and improve efficiency, and AI assisted tools are rapidly becoming indispensable assistants. In fact, over 25% of developers have used AI assisted tools to complete tasks such as code generation, test case creation, vulnerability fixing, and security checks, achieving significant improvements in work efficiency According to a recent report released by Accenture, GitHub Copilot can increase programming speed by 55% and boost developer confidence by 85%. Copilot currently has over 1 million paying users across more than 20000 businesses, with an average of 3.4 days of usage per week. The Arm extension is designed specifically for GitHub Copilot to simplify the process of migrating to the Arm architecture, shorten development cycles, and reduce costs. The extension initially focused on server and cloud environments, and plans to further expand to use cases such as mobile, IoT, software defined cars, and Windows on Arm development in the future. Developers only need to enter "@ arm" in GitHub Copilot Chat to easily obtain selected code examples, best practices, migration strategies, and performance optimization tips for Arm architecture development. Rinat Shagisultanov, Vice President of Modern Dev and DevOps Services Technology at InfoMagnus, said, "Arm extensions for GitHub Copilot are enough to reshape the development landscape for developers. Nowadays, developers can fully utilize Arm's internal functions and architecture features, significantly improving software performance and efficiency. This extension will greatly simplify the process of customers migrating workloads to Arm servers, which are not only lower in cost and more energy-efficient, but also widely deployed in the cloud. In addition, users can easily create Arm native CI/CD and MLOps workflows with the latest release of Arm Runners for GitHub Actions Software and Application Security Architect, Windows Developer, and Jeremy Sinclair, Microsoft's Most Valuable Player (MVP) in the. NET field, said, "What amazed me about the Arm extension is not only its ability to assist in coding, but also its ability to provide practical and effective background information about the Arm architecture. When I asked how to set up CI/CD for Kubernetes, it didn't give me a general answer, but directly provided me with the Arm learning path and actual documentation. Unlike general and useless guidance, Arm provides reasonable guidance for specific architectures, which is crucial for improving development efficiency To further understand how developers can use GitHub Copilot and Arm Runners to seamlessly build, test, and deploy, simplify workflows, and significantly improve efficiency, please refer to this blog post. Arm extension and native CI/CD for GitHub Copilot: providing powerful support for developers With the continuous updates of the Arm intelligent platform, constantly supplementing selected data and best practices, Arm extensions will also continue to evolve to provide support for a wider range of application scenarios, including: Generative AI: Simplify the creation and deployment of AI applications. Mobile and gaming: optimizing application performance on the Arm platform. Internet of Things and Software Defined Cars: Creating seamless workflows to achieve efficient deployment from the cloud to the edge and from the cloud to the car. Nowadays, Arm provides a complete integrated development environment, including CI/CD and MLOps workflows, which are implemented through Arm hosted Runners on GitHub Actions. In addition, GitHub recently released the free GitHub Runners for Arm, which allows developers to easily access fully integrated native Arm workflows, simplifying the development process from the cloud to the edge and making it suitable for various markets. With GitHub Actions, developers can build end-to-end MLOps workflows that combine and automate various steps in the machine learning (ML) lifecycle. When these workflows run natively on the Arm platform, developers can unlock significant advantages for AI/ML applications, especially in cloud to edge optimization. The Arm extension designed specifically for GitHub Copilot can provide developers with tailored, architecture related solutions, helping to further improve efficiency. With this extension, developers can easily utilize Arm architecture features such as BF16 and I8MM, as well as the latest Armv9 architecture features, including SVE2, which significantly improves ML performance, in native Azure Cobalt 100 GitHub Runners. GitHub Actions、 The latest Cobalt 100 native Arm Runners and Arm extensions designed specifically for GitHub Copilot will work together to help developers simplify workflows, optimize costs, and achieve better results at every stage of the MLOps journey. The vast future developed based on Arm architecture As Arm continues to improve its extensions, future versions will support a wider range of device types, including Android systems, gaming platforms, embedded systems, and software defined cars. Arm is committed to becoming a trusted platform for developers and will continue to collaborate with ecosystem partners to ensure that developers benefit from the latest Arm platform features in any computing field from the beginning of the project.

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