One of the most important challenges for IT experts is to teach a computer to understand human commands made in natural human language, as well as to perceive the world in the way people do.
Pursuing this end, the world’s leading corporations are developing so-called “cognitive services” based on machine learning algorithms. Using these, computers can learn to do things which only people could do before: text translation, image analysis, face and emotion recognition, speech recognition, text meaning understanding, and so on.
No doubt, at present people are continuing to perform these functions better – in most cases. But AI has the advantage of doing the job an order of magnitude faster and it can thus serve incomparably larger amounts of requests.
What Is Cognitive Technology? Explained in Simple Words
In short, cognitive technology implies software and hardware that emulate the work of the human brain. Experts consider cognitive technology to be the next – huge – step in information systems development.
Cognitive systems are constantly being trained to automatically adapt to operate with new data and tasks, and this is becoming reality due to artificial neural networks.
A shred platform, located in the cloud, is at the heart of cognitive apps. It can include all sorts of devices, APIs, platforms and technologies capable of making any apps “intelligent”, and even components of the Internet of things.
Cognitive apps are by no means the renowned artificial intelligence in its classical sense, but they are much “smarter” than any habitual software product.
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Applications of Cognitive Technology
Self-driving vehicles, drones, glasses for blind people, and any other machinery that requires processing of visual, audio, and other sensory data formats are just a small part of the wide field where cognitive technology can be implemented.
Cognitive systems are being developed to accurately recognize objects, facial expressions, and gestures, as well as meaningfully understand human languages with their semantic and emotional connotations. Consequently, in the future, we will be able to freely communicate with software the way we are used to doing with people.
Computers can recognize faces and objects, for example of your friends in photos on Facebook or Google Photos. Using facial recognition, you can find lookalikes or authorize users (biometric identification) in different services and devices.
Computer vision technologies are also used to develop driverless cars and to make various robots find their bearings.
However, that is not all. The apps can even recognize people’s emotions. This feature is utilized in entertainment (interactive lenses from Snapchat) as well as in trade and marketing: analyzing people’s emotions while they are shopping, it is possible to get a lot of useful data.
Text recognition algorithms become efficient when used for fast content pre-moderation, removing the necessity to involve people in this activity.
Each of the described technologies has its weak points. For example, facial recognition currently works badly in poor lighting. It is also insufficiently productive when comparing photos of a person who has changed over time. Speech recognition, also, cannot handle accents and dialects; and apps analyzing natural languages do not understand humor or irony.
Microsoft AI Cognitive Services: A Brief Overview of Available Solutions
Microsoft Cognitive Services is a set of intelligent software APIs working in the cloud. It recognizes and interprets requests transmitted using the communication methods habitual for physical users.
At the moment, the software is capable of working with image recognition, emotional recognition, facial recognition, and speech recognition. Many different options are available to work with texts (spell checking, linguistic analysis) and to provide many more services.
Face API can be used to find and compare human faces, group them into visual similarities, and identify previously marked people in images.
The Computer Vision API provides developers with the means to help comprehend what is shown in any image. Besides, it can recognize landmarks as well.
Check this complete list of currently available cognitive services by visiting the official Microsoft website.
To get started, you can use a free case (with a limited number of transactions) that will allow you to test the technology before you make the decision to purchase it.
Ready solutions save a lot of time for developers, and in turn, they save budget for companies when creating products.
Summary
Using Microsoft Azure cognitive services, you can develop great intelligent apps to solve your business needs. The examples, mentioned above, show well enough the capability of modern AI technologies.
You can use the advantages they provide for your company development right away. If you have any questions, contact us and our professionals will help you understand how to efficiently apply cognitive services in your business.
Flexibility, efficiency, and individual approach to each customer are the basic principles we are guided by in our work.
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