AI + machine learning

Insurance companies that sell life, health, and property and casualty insurance are using machine learning (ML) to drive improvements in customer service, fraud detection, and operational efficiency.

In the past two years since PyTorch’s first release in October 2016, we’ve witnessed the rapid and organic adoption of the deep learning framework among academia, industry, and the AI community at large.

Conversational AI is the next user interface paradigm in computing, making human and computer interactions more natural. We’ve evolved from a world where humans have to learn and adapt to computers to one where computers are learning how to understand and interact with humans.

Intelligent experiences powered by machine learning can seem like magic to users. Developing them, however, can be anything but.

To build an effective and scalable solution, developers need technology that can be deployed around the world and still provide results with high confidence.

Microsoft has reached a milestone in text-to-speech synthesis with a production system that uses deep neural networks to make the voices of computers nearly indistinguishable from recordings of people.

Azure Databricks provides a fast, easy, and collaborative Apache Spark-based analytics platform to accelerate and simplify the process of building big data and AI solutions that drive the business forward, all backed by industry leading SLAs.

Today we are very happy to release the new capabilities for the Azure Machine Learning service. Since our initial public preview launch in September 2017, we have received an incredible amount of valuable and constructive feedback.

AI, data and cloud are bringing in the next wave of transformative innovations across industries. With Azure AI, our purpose is to empower organizations to use AI to engage customers, empower employees, optimize operations and transform products.

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.