AI + machine learning

Testing is an important exercise in the life cycle of developing a machine learning system to assure high-quality operations.

This blog is part of a series in collaboration with our partners and customers leveraging the newly announced Azure Health Data Services.

A modernized cloud workload offers significant benefits—including cost savings, optimized security and management, and opportunities for ongoing innovation. But the process of migrating and modernizing workloads can be challenging.

Microsoft is committed to the responsible advancement of AI to enable every person and organization to achieve more.

Azure Neural Text to Speech (TTS), a powerful speech synthesis capability of Azure Cognitive Services, enables developers to convert text to lifelike speech using AI. Enterprises and agencies utilize Azure Neural TTS for video game characters, chatbots, content readers, and more.

Over the past few years, there has been an increasingly steady drumbeat for the need to diversify and open the telecommunications supply chain.

AI is enabling new experiences everywhere. When people watch a captioned video on their phone, search for information online, or receive customer assistance from a virtual agent, AI is at the heart of those experiences.

Welcome to our first Azure HPC + AI Day! We’re excited to host the first event, which will soon become an annual tradition.

Rightsizing is one of the key levers you have for controlling costs and optimizing resources. By understanding cloud economics, and using what Azure provides, you can identify the smallest virtual server instances that support your requirements and realize immediate savings by eliminating unused capacity.

Microsoft is helping to reshape the automotive industry in the way it serves its drivers with in-vehicle infotainment systems. Together with the car manufacturers, Microsoft is creating new driving experiences with speech based on the text-to-speech and speech-to-text capabilities within Azure Cognitive Services for speech.

As AI becomes more deeply embedded in our everyday lives, it is incumbent upon all of us to be thoughtful and responsible in how we apply it to benefit people and society.

AI is transforming business and the world. However, AI models learn from the data. Biases that exist in society will exist in the models. Human judgment must be the overriding factor, ensuring that AI models benefit and are inclusive of everyone.