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Azure AI

Artificial intelligence productivity for virtually every developer and scenario

Demystifying AI

With the flexible Azure platform and a wide portfolio of AI productivity tools, you can build the next generation of smart applications where your data lives, in the intelligent cloud, on-premises, and on the intelligent edge.

Achieve more with the comprehensive set of flexible and trusted AI services - from pre-built APIs, such as Cognitive Services and Conversational AI with Bot tools, to building custom models with Azure Machine Learning for any scenario. The Azure AI platform also features enterprise-grade AI infrastructure, that runs AI workloads anywhere at scale. Modern AI tools designed for developers and data scientists help you create AI solutions easily, with maximum productivity.

Why Azure AI

Productive and powerful AI tools

Get started with our comprehensive offering to create innovative AI applications: choose from innovative Pre-Built AI to Customizable ML and Deep Learning services and tools.

Bringing AI where you are

We provide Data and AI, so you can build the next generation of applications where your data already lives – in the intelligent cloud, on-premises, and on the intelligent edge – with the skills you already have. Container based deployment of models enables AI to run anywhere a Docker container can run, in our cloud, on your servers, or on devices.

Open and flexible platform

Easily choose the technology and deep learning framework suited for our scenario and skills with an open platform. Cognitive Services can be consumed by apps written in any language, and custom models can be built with the latest frameworks like Tensorflow, MXNet, Chainer, CNTK, and more.

Benefit from decades of AI investment

From Microsoft Research to Bing, Office, Windows, Xbox, and other AI-driven products, we’ve been using AI for decades. That’s why we have so many proven pre-built AI models for you to use directly in your applications.

Enterprise Grade AI

Microsoft has been leading the industry in establishing and meeting clear security and privacy requirements. Azure meets a broad set of international and industry-specific compliance standards, such as ISO 27001, HIPAA, FedRAMP, and SOC Rigorous third-party audits verify Azure’s adherence to the strict security controls these standards mandate.

Innovative hardware at hyperscale

Microsoft optimizes for AI, from the latest in GPU technology to FPGA accelerated AI models and networks, giving developers power and flexibility for building and running models at the highest scale in 50 regions worldwide.

Customers are doing great things with AI on Azure

GrayMeta
Uber
Schneider Electric
Dixons Carphone
American Eagle
BT
Progressive
JABIL
NBA
Carnival Maritime
Snow Leopard Trust
Accenture

AI Process

Incorporating AI into your applications consists of three key steps, but depending on your requirements and capabilities, Azure AI has flexible tools to suit your needs. Select our pre-built tools like Cognitive Services for enterprise-grade, off-the-shelf technology that can enable some customization, or choose a tool like Azure Machine Learning that allows you to bring your own data to enable deeper control and customization.

Prepare data

Connect to various sources to ingest data

Build & train

Establish a model and train with the data

Deploy

Deploy the model and track performance

AI Services

Accelerate the development of your AI solutions with high-level services. Use your preferred approach, adapted to your targeted scenario, and achieve maximum productivity and reliability.

Pre-built

Tap into high-quality RESTful intelligent APIs for Vision, Speech, Language, Knowledge and Search with just a few lines of code. No need to be an expert in data science to make your systems more intelligent, engaging and discoverable, such as communicating with your users in natural language, identifying relevant content in images, recognizing users by voice, and more.)

Use the pre-built services as-is, or customize them with data you prepare that is used to automatically to build & train algorithms to fit your specific needs, and run them in your application. These services help you build custom speech models that match users’ speaking styles, comb images to identify specific content that matters to you, or create customized search experiences for your users.

Learn more

Prepare data Build & train Deploy
Already built-in or bring your own data Already built-in Add to your application
GrayMeta

"Because the Cognitive Services APIs harness the power of machine learning, we were able to bring advanced intelligence into our product without the need to have a team of data scientists on hand"

Aaron Edell, Chief Product Owner, GrayMeta

Custom

Azure Machine Learning lets you make better decisions, at any scale, when it matters. Azure Machine Learning is a fully managed cloud service for data scientists and developers that helps you to easily prepare data, build & train your own models to ensure the best result, and run them wherever you need—with the confidence that your data is protected with enterprise-grade security.

Rapidly prototype on your desktop, then easily scale up on virtual machines or scale out using Spark clusters. Proactively manage model performance, identify the best model, and promote it using data-driven insights. Deploy and manage your models everywhere. Use Docker containers to deploy models into production faster in the cloud, on-premises, or at the edge. Promote your best performing models into production and retrain them whenever necessary.

Prepare data Build & train Deploy
Use your own data, prepare locally or in the cloud Use any Python based toolkit, or use Azure Machine Learning Packages to quickly solve Vision, Text, and Forecasting problems Add to your application or service
Schneider Electric

"Traditionally, machine learning is something that has only run in the cloud, but for many IoT scenarios that isn’t good enough… Now we have the flexibility to run it in the cloud or at the edge—wherever we need it to be."

Matt Boujonnier: Analytics Application Architect, Schneider Electric

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Conversational

Build, connect, deploy, and manage intelligent bots to naturally interact with your users on a website, app, Cortana, Microsoft Teams, Skype, Slack, Facebook Messenger, and more. Get started quick with a complete bot building environment, using C#, JavaScript, Python, and Java.

Learn more

Progressive

"By using Microsoft Azure Bot Service and Cognitive Services … we’ve been able to continue our own Progressive journey of digital innovation and do it in an agile, fast, and cost-effective way."

Matt White: Marketing Manager, Personal Lines Acquisition Experience - Progressive Insurance

Data Science VMs

DSVMs are Azure virtual machine images that are pre-installed, configured and tested with popular tools commonly used for data analytics, machine learning and AI. DSVMs offer on-demand elastic capacity for large-scale projects—scale vertically and horizontally on all Azure hardware. Pay only for what you use, when you use it. Deep Learning with GPUs is readily available with pre-configured deep learning tools for GPU clusters.

PyImageSearch

"If you're in the market for a deep learning cloud-based GPU instance, I would encourage you to try out Microsoft's DSVM… I would recommend it to anyone interested in a cloud-based deep learning solution."

Adrian Rosebrock, PyImageSearch

Open and comprehensive platform

AI tools

Equip your team with comprehensive and productive tooling for AI coding and management.

Visual Studio Code Tools for AI

Build, test, and deploy deep learning and AI solutions.

Azure Machine Learning Packages

Python extensions to quickly build and deploy highly accurate models.

Machine Learning Studio

Easily build, deploy, and manage predictive-analytics solutions.

AI Toolkit for Azure IoT Edge

Deploy deep learning models and AI to run locally on IoT devices through pre-built models.

ML.NET

.NET based solution for building Machine Learning models

MMLSpark

Highly-scalable deep learning tools for Apache Spark.

AI frameworks

Harness intelligence with massive datasets through popular deep-learning frameworks on a platform with comprehensive support.

TensorFlow

Open source software library for high performance numerical computation.

Onnx

An open format to represent deep learning models.

Azure Cognitive Toolkit

Free, open-source, commercial-grade toolkit to train deep learning algorithms optimized for speech.

Caffe2

Lightweight, modular, and scalable deep learning framework.

Pytorch

Scientific computing framework that puts GPUs first.

MxNet

A flexible and efficient library for deep learning.

scikit-learn

Simple and efficient tools for data mining and data analysis

Chainer

A powerful, flexible, and intuitive framework for neural networks.

AI related infrastructure

Use the power of AI infrastructure with virtually limitless scale and integrated AI services.

Azure Databricks

Accelerate innovation by enabling data science with high-performance analytics that’s optimized for Azure.

Azure Kubernetes Service

Scale and orchestrate containers using Kubernetes, DC/OS, or Docker Swarm.

Azure Cosmos DB

Integrate AI with a globally distributed, multi-model database service.

Azure SQL Database

Use R, Python, and native machine learning in an industry-leading SQL DB.

Azure Batch AI

Experience unlimited, elastic scale-out deep learning. Run large-scale, massively parallel GPU-enabled AI development.

Azure Data Lake Storage

Run data transformations and AI at petabyte-scale.

Data Science Virtual Machines

Use a friction-free data science environment that contains popular tools for data exploration, modeling, and development activities.

Apache Spark for Azure HDInsight

Take advantage of Apache Spark in the cloud for mission-critical deployments.

IoT Edge

Extend cloud intelligence to edge devices or run advanced models directly on the edge.

Popular Scenarios built with Azure AI

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