In today’s era, artificial intelligence plays a unique role in our lives. From self-driving cars to smart voice assistants, this technology is constantly evolving and is used as an important tool in the development of software and applications.

The programmer and software developer may want to benefit from the capabilities of artificial intelligence in the development of software but do not have the time, knowledge, and resources necessary to develop these complex technologies.

This is where the Azure Cognitive Service tool comes in handy. A platform that makes it easy to add AI capabilities to software with just a few simple lines of code.

Azure Cognitive Service provides developers and programmers with a set of intelligent tools that can use the power of this advanced technology without the need for deep specialized knowledge in the field of artificial intelligence.

In this article, we are going to talk about Azure Cognitive Services and show how you can use this platform to develop intelligent software.

What is Azure Cognitive Services?

Azure Cognitive Services is a set of artificial intelligence services in the cloud provided by Microsoft. These services allow developers and programmers to add AI capabilities to their apps and software. Using Azure Cognitive Services, the power of artificial intelligence can be used for face recognition, speech recognition, text translation, text analysis, decision-making, and many other tasks.

With the help of Azure Cognitive Services, you no longer need to write complex AI algorithms from scratch yourself. Instead, you can use this service to add AI capabilities to apps by adding a few simple lines of code.

Azure Cognitive Services gives you facilities that until now, you needed specialized knowledge and access to complex servers to develop intelligent software. But by using these services, you can use artificial intelligence capabilities in different fields.

Types of Azure Cognitive Services

Cognitive services are divided into five general categories:

  • Vision: includes services that can recognize and analyze images and videos.
  • Speech: includes services related to speech recognition, conversion, and analysis.
  • Language: includes services related to language and text processing and analysis.
  • Decision: includes services that help make smart decisions and analyze data.
  • Azure OpenAI Service: Powerful language models such as GPT-3, Codex, and Embeddings are used for content creation, summarization, semantic search, and text-to-code translation.

How does Azure Cognitive Services work?

To better understand how Azure Cognitive Services works, it is better to describe this process in three main steps: input, processing, and output.

  1. Input: In the first step, the software developer sends to the service what he wants the artificial intelligence to be applied to as input. For example, this input may be an image that you want the system to recognize, or text that you want to translate.
  2. Processing: After receiving the input, Azure Cognitive Services processes it. This processing includes image analysis, face recognition, entity recognition in the image, speech-to-text conversion, text translation, text analysis for information extraction, etc. For this, the service uses artificial intelligence algorithms and models trained by expert teams in the field of artificial intelligence and machine learning.
  3. Output: In this step, the Azure Cognitive Services service returns the output related to the processing.

In short, Azure Cognitive Services processes input using AI algorithms and models and returns corresponding output to the software designer.

Features and capabilities of the Azure Cognitive service

1. Face Recognition

Using this feature, you can recognize that there are faces in the image or video and extract their features. For example, you can use this feature to recognize faces in photos, embed changes in images, or even recognize people in videos.

2. Speech recognition

Speech recognition makes it possible to recognize human speech and then convert it into text. They use this feature to recognize and convert speech to text in videos, audio files, and smartphone systems.

3. Natural Language Processing (NLP)

Using natural language processing, they analyze the text, recognize the emotions in the text, and translate the text. This feature can be used to analyze user comments on social media, translate texts into different languages, or improve user experience in programs.

4. Image analysis

By using the image analysis feature, you can automatically extract various information from the images using advanced algorithms. This different information can be the following:

  1. Object recognition: This feature helps to automatically identify different objects in images.
  2. Similar image detection: Using this feature, you can search for similar or similar images in the image database, which can be useful in areas such as fraud detection, identity determination, and image matching.
  3. Recognition of famous places: by using image analysis algorithms, you can recognize famous places and tourist places.
  4. Image content description: Image analysis algorithms can identify and describe the elements in the image such as the person, other objects, activities, and the image environment.

5. Semantic search

Semantic Search allows you to perform a more advanced search for text and images.

How can you use Azure Cognitive Services?

To use Azure Cognitive Services, it is necessary to follow the following steps:

1. Create an Azure account

First, you need to create an Azure account. You can go to the Azure website and start the service subscription process. After registration, you will log in to the Azure panel using your account information.

2. Create a Cognitive Services resource

Create your Cognitive Services resource in the Azure panel. Click on Create a Resource and search for Cognitive Services in the resource search box. Then select a Cognitive Services resource and click Create.

3. Cognitive Services settings

In the settings step, you need to specify details such as the resource name, geographic location, and the features you want to use. For example, if you want to use face recognition and speech recognition, select these features in the settings.

4. Get the API key

After creating the Cognitive Services resource, you will have an API key. This API key serves as your authentication in using Cognitive Services. You should keep this key because you will use it in API requests.

5. Using Cognitive Services APIs

Now that you have access to the API key, you can use the Cognitive Services APIs in your apps and software. You can use these APIs to analyze images, translate text, convert speech to text, and perform many other intelligent functions.

As a result, whenever you need Cognitive Services, you can send API requests and receive intelligent output using the required API key.

Competing Azure cognitive tools

Although Microsoft’s Azure Cognitive is a powerful tool for implementing artificial intelligence algorithms in the software and application environment, other major companies in the world have tried to keep up with their competitors by producing similar tools. Some important competitors for Azure Cognitive are:

  • Google Cloud Vision API
  • Amazon Rekognition
  • IBM Watson Visual Recognition
  • Clarifai


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