A year of bringing AI to the edge
In an age where low-latency and data security can be the lifeblood of a business, containers make it possible for enterprises to meet these needs when harnessing artificial intelligence (AI).
In an age where low-latency and data security can be the lifeblood of a business, containers make it possible for enterprises to meet these needs when harnessing artificial intelligence (AI).
Multi-language speech transcription was recently introduced into Microsoft Video Indexer at the International Broadcasters Conference (IBC). It is available as a preview capability and customers can already start experiencing it in our portal.
Organizations face challenges when it comes to extracting insights, finding meaning, and uncovering new opportunities in the vast troves of content at their disposal.
It’s exciting to see the PyTorch Community continue to grow and regularly release updated versions of PyTorch! Recent releases improve performance, ONNX export, TorchScript, C++ frontend, JIT, and distributed training. Several new experimental features, such as quantization, have also been introduced.
This week at Microsoft Ignite, we announced updates to our products to make it easier for organizations to build robust conversational solutions, and to deploy them wherever their customers are. We are sharing some of the highlights below.
Azure Cognitive Services brings AI within reach of every developer without requiring machine learning expertise. All it takes is an API call to embed the ability to see, hear, speak, understand, and accelerate decision-making into your apps.
Enterprises today are adopting artificial intelligence (AI) at a rapid pace to stay ahead of their competition, deliver innovation, improve customer experiences, and grow revenue.
Over the past few years, we’ve seen incredible transformation across industries as companies harness the power of AI to transform business processes and drive impact for their customers.
Congratulations to the TensorFlow community on the release of TensorFlow 2.0! In this blog, we aim to highlight some of the ways that Azure can streamline the building, training, and deployment of your TensorFlow model.
Azure Stream Analytics is a fully managed Platform as a Service (PaaS) that supports thousands of mission-critical customer applications powered by real-time insights.
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.
Innovate at no cost to you with out-of-the box AI services that are newly available for Azure free account users. Join the 1.3 million developers who have been using Cognitive Services to build AI powered apps to date.