Skip Navigation

Artificial Intelligence

Getting AI/ML and DevOps working better together

Thursday, September 20, 2018

Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms.

Software Architect, Microsoft Azure

Customizing Azure Blueprints to accelerate AI in healthcare

Thursday, September 13, 2018

Artificial Intelligence (AI) holds major potential for healthcare, from predicting the patient length of stays to diagnostic imaging, anti-fraud, and many more use cases. To be successful in using AI, healthcare needs solutions, not projects. Learn how you can close the gap to your AI in healthcare solution by accelerating your initiative using Microsoft Azure blueprints.

Principal Systems Architect, Microsoft Azure

How to extract building footprints from satellite images using deep learning

Wednesday, September 12, 2018

As part of the AI for Earth team, I work with our partners and other researchers inside Microsoft to develop new ways to use machine learning and other AI approaches to solve global environmental challenges. In this post, we highlight a sample project of using Azure infrastructure for training a deep learning model to gain insight from geospatial data.

Data Scientist, AI for Earth

Use AI to streamline healthcare operations

Wednesday, September 12, 2018

The profound impact of machine learning (ML) and artificial intelligence (AI) is changing the way heath organizations think about many of the challenges they face. Making data-informed decisions based on actionable insights is improving many aspects of healthcare from patient diagnosis and outcomes to operational efficiencies.

Principal Systems Architect, Microsoft Azure