Internet of things

At the recent Microsoft Ignite 2019 conference, we introduced two new and related perspectives on the future and roadmap of edge computing.

It’s exciting to see the PyTorch Community continue to grow and regularly release updated versions of PyTorch! Recent releases improve performance, ONNX export, TorchScript, C++ frontend, JIT, and distributed training. Several new experimental features, such as quantization, have also been introduced.

Microsoft is expanding the ecosystem of FHIR® for developers with a new tool to securely ingest, normalize, and persist Protected Health Information (PHI) from IoMT devices in the cloud.

As a company, we work every day to empower every person on the planet to achieve more.

We live in amazing times when people and businesses at different continents can interact at the speed of light. Numerous industries and applications target users around the globe: e-commerce websites, multiplayer online games, connected IoT devices, collaborative work and leisure experience, and many more.

Cities are using the Internet of Things (IoT) to manage their infrastructure by capturing and analyzing data from connected devices and sensors, giving city managers real-time insights to improve operational efficiency and outcomes and to altogether rethink and reinvent city government functions and operations.

Cloud computing has opened new paradigms that enable enterprises to reach new levels of productivity and scale.

With the breakneck speed at which technology is changing, more and more applications, big and small, are being created every day.

Enterprises today are adopting artificial intelligence (AI) at a rapid pace to stay ahead of their competition, deliver innovation, improve customer experiences, and grow revenue.

Over the past few years, we’ve seen incredible transformation across industries as companies harness the power of AI to transform business processes and drive impact for their customers.

Congratulations to the TensorFlow community on the release of TensorFlow 2.0! In this blog, we aim to highlight some of the ways that Azure can streamline the building, training, and deployment of your TensorFlow model.

Azure Stream Analytics is a fully managed Platform as a Service (PaaS) that supports thousands of mission-critical customer applications powered by real-time insights.