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How to migrate and modernize Linux workloads and open source databases to Azure 

With extensive support for all major Linux distributions including Red Hat, SUSE, Ubuntu, CentOS, Debian, and managed platform-as-a-service (PaaS) offerings for open source databases like Azure Database for MySQL, Azure Database for PostgreSQL, and Azure Database for MariaDB—it’s no surprise that Linux is the fastest growing platform on Azure. Furthermore, Azure Migrate makes the discovery,...Read more

Empowering you to achieve more with open source on Azure 

At Microsoft, we are taking cloud architecture to the next level and our open cloud reduces the friction for developers to get applications up and running. We give autonomy and control to the developers to flexibly choose their infrastructure and give them options to build, migrate, and deploy across multiple environments on-premises, in the cloud,...Read more

ONNX Runtime 1.8: mobile, web, and accelerated training 

The V1.8 release of ONNX Runtime includes many exciting new features. This release launches ONNX Runtime machine learning model inferencing acceleration for Android and iOS mobile ecosystems (previously in preview) and introduces ONNX Runtime Web. Additionally, the release also debuts official packages for accelerating model training workloads in PyTorch. ONNX Runtime is a cross-platform runtime...Read more

Delivering reliable production experiences with PyTorch Enterprise on Microsoft Azure 

At Microsoft, we use PyTorch to power products such as Bing and Azure Cognitive Services and we actively contribute to several PyTorch open-source projects, including PyTorch Profiler, ONNX Runtime, DeepSpeed, and more. Today, we’re announcing a new initiative in collaboration with Facebook—the PyTorch Enterprise Support Program. This new program enables service providers to develop and...Read more

Making eBPF work on Windows 

eBPF is a well-known but revolutionary technology—providing programmability, extensibility, and agility. eBPF has been applied to use cases such as denial-of-service protection and observability. Over time, a significant ecosystem of tools, products, and experience has been built up around eBPF. Although support for eBPF was first implemented in the Linux kernel, there has been increasing...Read more

Optimizing BERT model for Intel CPU Cores using ONNX runtime default execution provider 

This blog was co-authored with Manash Goswami, Principal Program Manager, Machine Learning Platform. The performance improvements provided by ONNX Runtime powered by Intel® Deep Learning Boost: Vector Neural Network Instructions (Intel® DL Boost: VNNI) greatly improves performance of machine learning model execution for developers. In the past, machine learning models mostly relied on 32-bit floating...Read more

Microsoft Open Source success story—Babylon 

An ongoing series of stories about Microsoft people and projects making their world better through open source. If you haven’t heard of Babylon.js, there is no doubt that it’s already made your day more cheerful, powering Microsoft Teams’ Reactions‘ (those cute floating emojis), or your presentation faster and smoother as the engine that powers rendering...Read more

Create privacy-preserving synthetic data for machine learning with SmartNoise 

Watch our webinar on Open Data Science Conference  Read the white paper on SmartNoise Differential Privacy machine learning case studies The COVID-19 pandemic demonstrates the tremendous importance of sufficient and relevant data for research, causal analysis, government action, and medical progress. However, for understandable data protection considerations, individuals and decision-makers are often very reluctant to share personal or sensitive data....Read more

Enabling responsible AI development with new open source capabilities 

At last year’s Microsoft Build conference in May 2020, Microsoft introduced three responsible AI (RAI) toolkits available in both open source as well as integrated within Azure Machine Learning: InterpretML, Fairlearn, and SmartNoise. These tools enable machine learning data scientists to understand model predictions, assess fairness, and protect sensitive data. Building on this family of...Read more