Microsoft Azure AI Fundamentals: Get started with artificial intelligence
Tags: azure, azurefunctions, ai, eventgrid
Published: 2024-03-20 15:18:31

Introduction
Artificial Intelligence (AI) is changing our world and there’s hardly an industry that hasn't been affected. From better healthcare to online safety, AI is helping us to tackle some of society’s biggest issues.

Azure AI services are a portfolio of AI capabilities that unlock automation for workloads in language, vision, intelligent search, content generation, and much more. They are straightforward to implement and don’t require specialist AI knowledge.Introduction

Artificial Intelligence (AI) is changing our world and there’s hardly an industry that hasn't been affected. From better healthcare to online safety, AI is helping us to tackle some of society’s biggest issues.

Azure AI services are a portfolio of AI capabilities that unlock automation for workloads in language, vision, intelligent search, content generation, and much more. They are straightforward to implement and don’t require specialist AI knowledge.

Organizations are using Azure AI services in innovative ways, such as within robots to provide life-like companionship to older people by expressing happiness, concern, and even laughter. In other use cases, scientists are using AI to protect endangered species by identifying hard-to-find animals in images. This was previously time-consuming and error-prone work, which the Azure AI Vision service can complete quickly and with a high degree of accuracy, freeing scientists to do other work.

In this module you will learn what Azure AI services are, and how you can use them in your own applications.

AI services on the Azure platform
Azure AI services are AI capabilities that can be built into web or mobile applications, in a way that's straightforward to implement. These AI services include image recognition, natural language processing, speech, AI-powered search, and more. There are over a dozen different services that can be used separately or together to add AI power to applications.

Let's take a look at some examples of what can be done with Azure AI services. The Azure AI Content Safety service can be used to detect harmful content within text or images, including violent or hateful content, and report on its severity. The Azure AI Language service can be used to summarize text, classify information, or extract key phrases. The Azure AI Speech service provides powerful speech to text and text to speech capabilities, allowing speech to be accurately transcribed into text, or text to natural sounding voice audio.

Azure AI services are based on three principles that dramatically improve speed-to-market:

Prebuilt and ready to use

Accessed through APIs

Available on Azure

Azure AI services are prebuilt and ready to use
AI has been prohibitive for all but the largest technology companies because of several factors, including the large amounts of data required to train models, the massive amount of computing power needed, and the budget to hire specialist programmers. Azure AI services make AI accessible to businesses of all sizes by using pre-trained machine learning models to deliver AI as a service. Azure AI services use high-performance Azure computing to deploy advanced AI models as resources, making decades of research available to developers of all skill levels.

Azure AI services are a portfolio of services, with capabilities suitable for use cases across sectors and industries.

For example, in education, Immersive Reader is being used to support students by adapting to their requirements. Learners can have varying needs, such as wanting to read more slowly, get words or text translated into another language, or see pictures to aid their understanding. Immersive Reader helps students with different needs learn at their own pace, and in their own way.

While Azure AI services can be used without any modification, some AI services can be customized to better fit specific requirements. Customization capabilities in Azure AI Vision, Azure AI Speech, and Azure OpenAI all allow you to add data to existing models.

For example, in sport, athletes, and coaches are customizing Azure AI Vision to improve performance and reduce injury. One application allows surfers to upload a video and receive AI-generated insights and analysis. These insights can then be used by coaches, medics, judges, and event broadcasters.

Azure AI services are accessed through APIs
Azure AI services are designed to be used in different development environments, with minimal coding. Developers can access AI services through REST APIs, client libraries, or integrate them with tools such as Logic Apps and Power Automate. APIs are application programming interfaces that define the information that is required for one component to use the services of the other. APIs enable software components to communicate, so one side can be updated without stopping the other from working. Find out more about development options for Azure AI services here.

Azure AI services are available on Azure
AI services are cloud-based and accessed through Azure resource. This means that they're managed in the same way as other Azure services, such as platform as a service (PaaS), infrastructure as a service (IaaS), or a managed database service. The Azure platform and Resource Manager provide a consistent framework for all your Azure services, from creating or deleting resources, to availability and billing.

Create Azure AI service resources
Azure AI services are cloud-based, and like all Azure services you need to create a resource to use them. There are two types of AI service resources: multi-service or single-service. Your development requirements and how you want costs to be billed determine the types of resources you need.

Multi-service resource: a resource created in the Azure portal that provides access to multiple Azure AI services with a single key and endpoint. Use the resource Azure AI services when you need several AI services or are exploring AI capabilities. When you use an Azure AI services resource, all your AI services are billed together.

Single-service resources: a resource created in the Azure portal that provides access to a single Azure AI service, such as Speech, Vision, Language, etc. Each Azure AI service has a unique key and endpoint. These resources might be used when you only require one AI service or want to see cost information separately.

You can create a resource several ways, such as in the Azure portal.

How to use the Azure portal to create an Azure AI services resource
To create an Azure AI services resource, sign in to the Azure portal with Contributor access and select Create a resource. To create a multi-services resource search for Azure AI services in the marketplace.

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To create a single-service resource, search for the specific Azure AI service such as Face, Language, or Content Safety, and so on. Most AI services have a free price tier to allow you to explore their capabilities. After clicking Create for the resource you require, you will be prompted to complete details of your subscription, the resource group to contain the resource, the region, a unique name, and the price tier.

Use Azure AI services
Once you create an Azure AI service resource, you can build applications using the REST API, software development kits (SDKs), or visual studio interfaces.

Minimize image
Edit image
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Using service studio interfaces
Studio interfaces provide a friendly user interface to explore Azure AI services. There are different studios for different Azure AI services, such as Vision Studio, Language Studio, Speech Studio, and the Content Safety Studio. You can test out Azure AI services using the samples provided, or experiment with your own content. A studio-based approach allows you to explore, demo, and evaluate Azure AI services regardless of your experience with AI or coding.

Associate the AI service resource
Before you can use an AI service resource, you must associate it with the studio you want to use on the Settings page. Select the resource, and then select Use Resource. You are then ready to explore the Azure AI service within the studio.

Minimize image
Edit image
Delete image


As an example, let's look at the Azure AI Content Safety service, which identifies harmful text or images. To explore what the Content Safety service does, let's use the Content Safety Studio. First create either a multi-service Azure AI services resource, or a single-service Content Safety resource. Then, on the Content Safety Studio Settings page, select the resource, and select Use Resource. The AI service you created is now associated with the Content Safety Studio, and ready to be used.

Use Azure AI services
Once you create an Azure AI service resource, you can build applications using the REST API, software development kits (SDKs), or visual studio interfaces.

Minimize image
Edit image
Delete image


Using service studio interfaces
Studio interfaces provide a friendly user interface to explore Azure AI services. There are different studios for different Azure AI services, such as Vision Studio, Language Studio, Speech Studio, and the Content Safety Studio. You can test out Azure AI services using the samples provided, or experiment with your own content. A studio-based approach allows you to explore, demo, and evaluate Azure AI services regardless of your experience with AI or coding.

Associate the AI service resource
Before you can use an AI service resource, you must associate it with the studio you want to use on the Settings page. Select the resource, and then select Use Resource. You are then ready to explore the Azure AI service within the studio.

Minimize image
Edit image
Delete image


As an example, let's look at the Azure AI Content Safety service, which identifies harmful text or images. To explore what the Content Safety service does, let's use the Content Safety Studio. First create either a multi-service Azure AI services resource, or a single-service Content Safety resource. Then, on the Content Safety Studio Settings page, select the resource, and select Use Resource. The AI service you created is now associated with the Content Safety Studio, and ready to be used.

Summary
Azure AI services are easy to use AI capabilities made available as resources on the Azure platform. Azure AI service capabilities include Language, Speech, Vision, Decision, Search, and Azure OpenAI.

In this module we’ve used several different terms relating to AI services. Here's a recap:

API – application programming interfaces (APIs) enable software components to communicate, so one side can be updated without stopping the other from working.

Artificial Intelligence (AI) – computer programs that respond in ways that are normally associated with human reasoning, learning, and thought.

Azure AI services – a portfolio of AI services that can be incorporated into applications quickly and easily without specialist knowledge. Azure AI services is also the name for the multi-service resource created in the Azure portal that provides access to several different Azure AI services with a single key and endpoint.

Endpoint – the location of a resource, such as an Azure AI service.

Key – a private string that is used to authenticate a request.

Machine learning – the ability for computer programs to learn from large amounts of data, in a process known as "training".

Multi-service resource – the AI service resource created in the Azure portal that provides access to a bundle of AI services.

Single-service resource – a resource created in the Azure portal that provides access to a single Azure AI service, such as Speech, Vision, Language, etc. Each Azure AI service has a unique key and endpoint.

RESTful API – a scalable web application programming interface used to access Azure AI services.

You can find out more about Azure AI services in the service documentation.

Organizations are using Azure AI services in innovative ways, such as within robots to provide life-like companionship to older people by expressing happiness, concern, and even laughter. In other use cases, scientists are using AI to protect endangered species by identifying hard-to-find animals in images. This was previously time-consuming and error-prone work, which the Azure AI Vision service can complete quickly and with a high degree of accuracy, freeing scientists to do other work.

In this module you will learn what Azure AI services are, and how you can use them in your own applications.

AI services on the Azure platform
Azure AI services are AI capabilities that can be built into web or mobile applications, in a way that's straightforward to implement. These AI services include image recognition, natural language processing, speech, AI-powered search, and more. There are over a dozen different services that can be used separately or together to add AI power to applications.

Let's take a look at some examples of what can be done with Azure AI services. The Azure AI Content Safety service can be used to detect harmful content within text or images, including violent or hateful content, and report on its severity. The Azure AI Language service can be used to summarize text, classify information, or extract key phrases. The Azure AI Speech service provides powerful speech to text and text to speech capabilities, allowing speech to be accurately transcribed into text, or text to natural sounding voice audio.

Azure AI services are based on three principles that dramatically improve speed-to-market:

Prebuilt and ready to use

Accessed through APIs

Available on Azure

Azure AI services are prebuilt and ready to use
AI has been prohibitive for all but the largest technology companies because of several factors, including the large amounts of data required to train models, the massive amount of computing power needed, and the budget to hire specialist programmers. Azure AI services make AI accessible to businesses of all sizes by using pre-trained machine learning models to deliver AI as a service. Azure AI services use high-performance Azure computing to deploy advanced AI models as resources, making decades of research available to developers of all skill levels.

Azure AI services are a portfolio of services, with capabilities suitable for use cases across sectors and industries.

For example, in education, Immersive Reader is being used to support students by adapting to their requirements. Learners can have varying needs, such as wanting to read more slowly, get words or text translated into another language, or see pictures to aid their understanding. Immersive Reader helps students with different needs learn at their own pace, and in their own way.

While Azure AI services can be used without any modification, some AI services can be customized to better fit specific requirements. Customization capabilities in Azure AI Vision, Azure AI Speech, and Azure OpenAI all allow you to add data to existing models.

For example, in sport, athletes, and coaches are customizing Azure AI Vision to improve performance and reduce injury. One application allows surfers to upload a video and receive AI-generated insights and analysis. These insights can then be used by coaches, medics, judges, and event broadcasters.

Azure AI services are accessed through APIs
Azure AI services are designed to be used in different development environments, with minimal coding. Developers can access AI services through REST APIs, client libraries, or integrate them with tools such as Logic Apps and Power Automate. APIs are application programming interfaces that define the information that is required for one component to use the services of the other. APIs enable software components to communicate, so one side can be updated without stopping the other from working. Find out more about development options for Azure AI services here.

Minimize image
Edit image
Delete image


Azure AI services are available on Azure
AI services are cloud-based and accessed through Azure resource. This means that they're managed in the same way as other Azure services, such as platform as a service (PaaS), infrastructure as a service (IaaS), or a managed database service. The Azure platform and Resource Manager provide a consistent framework for all your Azure services, from creating or deleting resources, to availability and billing.

Create Azure AI service resources
Minimize image
Edit image
Delete image


Azure AI services are cloud-based, and like all Azure services you need to create a resource to use them. There are two types of AI service resources: multi-service or single-service. Your development requirements and how you want costs to be billed determine the types of resources you need.

Multi-service resource: a resource created in the Azure portal that provides access to multiple Azure AI services with a single key and endpoint. Use the resource Azure AI services when you need several AI services or are exploring AI capabilities. When you use an Azure AI services resource, all your AI services are billed together.

Single-service resources: a resource created in the Azure portal that provides access to a single Azure AI service, such as Speech, Vision, Language, etc. Each Azure AI service has a unique key and endpoint. These resources might be used when you only require one AI service or want to see cost information separately.

You can create a resource several ways, such as in the Azure portal.

How to use the Azure portal to create an Azure AI services resource
To create an Azure AI services resource, sign in to the Azure portal with Contributor access and select Create a resource. To create a multi-services resource search for Azure AI services in the marketplace.

Minimize image
Edit image
Delete image


To create a single-service resource, search for the specific Azure AI service such as Face, Language, or Content Safety, and so on. Most AI services have a free price tier to allow you to explore their capabilities. After clicking Create for the resource you require, you will be prompted to complete details of your subscription, the resource group to contain the resource, the region, a unique name, and the price tier.

Use Azure AI services
Once you create an Azure AI service resource, you can build applications using the REST API, software development kits (SDKs), or visual studio interfaces.

Minimize image
Edit image
Delete image


Using service studio interfaces
Studio interfaces provide a friendly user interface to explore Azure AI services. There are different studios for different Azure AI services, such as Vision Studio, Language Studio, Speech Studio, and the Content Safety Studio. You can test out Azure AI services using the samples provided, or experiment with your own content. A studio-based approach allows you to explore, demo, and evaluate Azure AI services regardless of your experience with AI or coding.

Associate the AI service resource
Before you can use an AI service resource, you must associate it with the studio you want to use on the Settings page. Select the resource, and then select Use Resource. You are then ready to explore the Azure AI service within the studio.

Minimize image
Edit image
Delete image


As an example, let's look at the Azure AI Content Safety service, which identifies harmful text or images. To explore what the Content Safety service does, let's use the Content Safety Studio. First create either a multi-service Azure AI services resource, or a single-service Content Safety resource. Then, on the Content Safety Studio Settings page, select the resource, and select Use Resource. The AI service you created is now associated with the Content Safety Studio, and ready to be used.

Use Azure AI services
Once you create an Azure AI service resource, you can build applications using the REST API, software development kits (SDKs), or visual studio interfaces.

Minimize image
Edit image
Delete image


Using service studio interfaces
Studio interfaces provide a friendly user interface to explore Azure AI services. There are different studios for different Azure AI services, such as Vision Studio, Language Studio, Speech Studio, and the Content Safety Studio. You can test out Azure AI services using the samples provided, or experiment with your own content. A studio-based approach allows you to explore, demo, and evaluate Azure AI services regardless of your experience with AI or coding.

Associate the AI service resource
Before you can use an AI service resource, you must associate it with the studio you want to use on the Settings page. Select the resource, and then select Use Resource. You are then ready to explore the Azure AI service within the studio.

Minimize image
Edit image
Delete image


As an example, let's look at the Azure AI Content Safety service, which identifies harmful text or images. To explore what the Content Safety service does, let's use the Content Safety Studio. First create either a multi-service Azure AI services resource, or a single-service Content Safety resource. Then, on the Content Safety Studio Settings page, select the resource, and select Use Resource. The AI service you created is now associated with the Content Safety Studio, and ready to be used.

Summary
Azure AI services are easy to use AI capabilities made available as resources on the Azure platform. Azure AI service capabilities include Language, Speech, Vision, Decision, Search, and Azure OpenAI.

In this module we’ve used several different terms relating to AI services. Here's a recap:

API – application programming interfaces (APIs) enable software components to communicate, so one side can be updated without stopping the other from working.

Artificial Intelligence (AI) – computer programs that respond in ways that are normally associated with human reasoning, learning, and thought.

Azure AI services – a portfolio of AI services that can be incorporated into applications quickly and easily without specialist knowledge. Azure AI services is also the name for the multi-service resource created in the Azure portal that provides access to several different Azure AI services with a single key and endpoint.

Endpoint – the location of a resource, such as an Azure AI service.

Key – a private string that is used to authenticate a request.

Machine learning – the ability for computer programs to learn from large amounts of data, in a process known as "training".

Multi-service resource – the AI service resource created in the Azure portal that provides access to a bundle of AI services.

Single-service resource – a resource created in the Azure portal that provides access to a single Azure AI service, such as Speech, Vision, Language, etc. Each Azure AI service has a unique key and endpoint.

RESTful API – a scalable web application programming interface used to access Azure AI services.

You can find out more about Azure AI services in the service documentation.