Internet of things

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.

Azure IoT Central is an IoT app platform for solution builders that simplifies the challenges of building and deploying scalable and affordable enterprise grade IoT applications.

Azure Machine Learning is the center for all things machine learning on Azure, be it creating new models, deploying models, managing a model repository and/or automating the entire CI/CD pipeline for machine learning.

Late last year, we announced the preview of some of the foundational capabilities for our industrial IoT analytics platform with a scalable time series storage for trending decades of data, semantic model support to describe domain-specific metadata, and enhanced analytics APIs and UX.

Author: Bert Van Hoof For the last five years, our industry has buzzed with the promises of IoT. IoT has evolved from being a next-horizon term, to a common vernacular employed across industry conversations.

Today, Microsoft becomes the first cloud with a fully managed, first-party service to ingest, persist, and manage healthcare data in the native FHIR format. The Azure API for FHIR® is releasing today in generally availability to all Azure customers.

We are excited to share the winners of the first Microsoft Azure AI Hackathon, hosted on Devpost.

The tech world is fast-paced, and cloud services like Azure Cosmos DB get frequent updates with new features, capabilities, and improvements.

Built-in Jupyter notebooks for Azure Cosmos DB are now publicly available. Developers, data scientists, engineers and analysts can use the familiar Jupyter notebooks experience to interactively run queries, explore and analyze data, visualize data & build, train, and run machine learning and AI models.