Internet of things

We announced the general availability of Azure Security Center for IoT in July 2019. Since then, we have seen a lot of interest from both our customers and partners.

At Microsoft, building a future that we can all thrive in is at the center of everything we do.

Microsoft Azure Machine Learning (ML) is addressing complex business challenges that were previously thought unsolvable and is having a transformative impact across every vertical.

For many retailers around the world, the busiest quarter of the year just finished with holiday shopping through Black Friday and Cyber Monday to Boxing Day.

Few industries have been disrupted by emerging technology quite like retail. From exploding online sales to the growth of mobile shopping, the industry has made a permanent shift to accommodate digital consumers.

As 2020 is upon us, we typically take this time to reflect back on the current year’s achievements (and challenges) and begin planning for the next year.

Since releasing Microsoft Azure IoT Edge, we have seen many customers using IoT Edge automatic deployments to deploy workloads to the edge at scale.

One of the toughest IoT quandaries is figuring out how to bake IoT into existing hardware in a secure, cost-effective way. For many customers, scrapping existing hardware investments for new IoT-enabled devices (“greenfield” installations) isn’t feasible.

Digital twins have moved from an exciting concept to reality.

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.