Microsoft is transforming its AI research capabilities into enterprise-grade infrastructure with the limited preview launch of enhanced agent support in Azure AI Foundry.

That means developers will soon be able to run MLX models directly on NVIDIA GPUs, which is a pretty big deal. Here’s why.

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

Also available in the Azure Machine Learning service, Prompt Flow simplifies the process of prototyping, experimenting, iterating and deploying AI applications, according to Microsoft.

Microsoft wants companies to build their own AI-powered “copilots” — using tools on Azure and machine learning models from its close partner OpenAI, of course.

With the rapid pace of change in AI and machine learning, it’s no surprise Microsoft had its usual strong presence at this year’s NVIDIA GTC.

This capability allows customers to build models with Azure Machine Learning anywhere, including on-premises, multi-cloud environments, and at the edge.

The Azure Machine Learning studio web experience is generally availabl, enabling data scientists and data engineers to complete their end-to-end machine learning lifecycle from prepping and ...