Ten years ago, Microsoft released the source for MS-DOS 1.25 and 2.0 to the Computer History Museum, and then later republished them for reference purposes. This code holds an important place in history and is a fascinating read of an operating system that was written entirely in 8086 assembly code nearly 45 years ago.  Today, in partnership with IBM and in the spirit of open innovation, we're releasing the source code to MS-DOS 4.00 under the MIT license. There's a somewhat complex and fascinating history behind the 4.0 versions of DOS, as Microsoft partnered with IBM for portions of the ..read more

The rise of open source has had significant impact across the technology landscapetransforming software development, accelerating innovation, and driving digital transformation. In fact, 95% of organizations have either increased or maintained their use of open source software in the past year,1 and 96% of applications now leverage open source.2Open source is fundamental to Microsoft and can be found throughout the company todayacross Microsoft, developers are using open source technology and building it with the collaborators across the globe. Open Source Summit North America 2024 Engage w ..read more

Greetings and welcome to KubeCon Europe 2024! At Microsoft, we are deeply committed to supporting the cloud native ecosystem through contributions and leadership from engineers across Azure. We've made some important enhancements and innovations in Azure, Azure Kubernetes Service (AKS), and our open-source projects, and I'm happy to share the highlights here. Learn more about Azure Kubernetes Service Empowering cloud-native development and AI innovation Artificial intelligence (AI) and machine learning (ML) are transforming every industry and domain, enabling new levels of innovation, efficien ..read more

In-browser machine learning (ML) enables web applications to execute machine learning models entirely client-side in the browser. As a key player of on-device AI, it has garnered significant interest thanks to advantages in privacy protection, enhanced portability, as well as cost and latency savings by eliminating client-server communication. Nevertheless, the rise of large generative models brings a challenge for in-browser ML, as executing these models demands increased computational power and memory resources. ONNX Runtime Web is the web-inference solution offered in ONNX Runtime. This blo ..read more

Continuing the ONNXRuntime On-Device Trainingblog series, we are introducing ONNX Runtime Training for Web, a new feature in ONNX Runtime (ORT) that enables training models in the browser. This capability opens up new scenarios for in-browser federated learning and personalization using data on the device and preserving user privacy. This blog post provides an overview of ORT Training Web. Check out the full demo source code to learn more about ORT Training for Web and explore experimenting with it for your own applications! A glance at ONNX Runtime Training in Web ORT Web has offered in-brows ..read more

Generative Adversarial Networks (GANs) are deep learning architectures that generate high quality synthetic images of people, animals or objects around us. These networks have enabled us to provide text-based prompts for generating realistic images, modifying existing images and to complete missing information in training datasets. StyleGAN is a type of GAN designed to control the style of the generated images for high quality and detailed results. Once such realistic images are created, any minor tweaks or updates can be performed through the DragGAN model, which allows minor edits to the gen ..read more

Hello and welcome to KubeCon North America. I'm thrilled to get a chance to meet up with everyone in person whether it is at one of the conference sessions, at the Microsoft booth, or the best part, the hallway track! Whether you’re a developer, a Site Reliability Engineer, or trying to figure out how cloud-native technology can help deliver more for your business, wherever you go at KubeCon, you'll find Microsoft building and serving the open-source communities that serve our customers. This year we've got some key improvements and innovations in both Azure and our open source projects that w ..read more

Developers and IT operators today know all too well the pain involved with deploying, managing, and making sense of applications in an ever-evolving and increasingly complicated cloud-native landscape. While it’s true that advancements in cloud infrastructure and platforms like Kubernetes have been gamechangers for developing flexible, scalable, and portable microservice applications, they have also made things more challenging for developers and operators alike. For developers, the complexity of managing infrastructure and lack of visibility into the resources that make up their applicat ..read more

Linux Foundation (LF) AI & Data Foundationthe organization building an ecosystem to sustain open source innovation in AI and data open source projects, announced Recommenders as its latest Sandbox project. Recommenders is an open source Github repository designed to assist researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a wide range of classic and state-of-the-art recommendation algorithms. By providing valuable examples such as Jupyter notebooks and establishing best practices for building recommendation systems, Recommenders aims t ..read more

There are currently over 320,000 models on Hugging Face (HF), and this number continues to grow every day. Only about 6,000 of these models have an indication of ONNX support in the HF Model Hub, but over 130,000 support the ONNX format. ONNX models can be accelerated with ONNX Runtime (ORT), which works cross-platform and provides coverage for many cloud models and language models. Updating the HF Model Hub with more accurate information about ONNX coverage will ensure that users can leverage all the benefits of ORT when deploying HF models. This blog post will provide an overview of HF model ..read more