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. We recently made some amazing announcements on Azure Machine Learning, and in this post, I’m taking a closer look at two of the most compelling capabilities that your business should consider while choosing the machine learning platform.
We are excited to share the winners of the first Microsoft Azure AI Hackathon, hosted on Devpost. Developers of all backgrounds and skill levels were welcome to join and submit any form of AI project, whether using Azure AI to enhance existing apps with pre-trained machine learning (ML) models, or by building ML models from scratch.
Who spends their summer at the Microsoft Garage New England Research & Development Center (or “NERD”)? The Garage Internship seeks out students who are hungry to learn, not afraid to try new things, and able to step out of their comfort zones when faced with ambiguous situations.
Today, Alysa Taylor, Corporate Vice President of Business Applications and Industry, announced several new AI-driven insights applications for Microsoft Dynamics 365.
A connected vehicle solution must enable a fleet of potentially millions of vehicles, distributed around the world, to deliver intuitive experiences including infotainment, entertainment, productivity, driver safety, driver assistance. In addition to these services in the vehicle, a connected vehicle solution is critical for fleet solutions like ride- and car-sharing as well as phone apps that incorporate the context of the user and the journey.
Artificial intelligence (AI) workloads include megabytes of data and potentially billions of calculations. With advancements in hardware, it is now possible to run time-sensitive AI workloads on the edge while also sending outputs to the cloud for downstream applications.
Congratulations to the PyTorch community on the release of PyTorch 1.2! Last fall, as part of our dedication to open source AI, we made PyTorch one of the primary, fully supported training frameworks on Azure.
With the Bot Framework release in July, we are happy to share new releases of Bot Framework SDK 4.5 and preview of 4.6, updates to our developer tools, and new channels in Azure Bot Service. We’ll use the opportunity to provide additional updates for the Conversational AI releases from Microsoft.
With over 360,000 registered Azure Bot Service developers, we’ve seen significant growth in bots and virtual assistants built on Azure. A major trend we’re following is the growing need for these assistants to support voice-first conversational experiences.
Every day, healthcare organizations are beginning their digital transformation journey with the Microsoft Healthcare Bot Service built on Azure. The Healthcare Bot service empowers healthcare organizations to build and deploy an Artificial Intelligence (AI) powered, compliant, conversational healthcare experience at scale.