Introduction

AI is Making Mobile Apps Smarter: The use of the concept of artificial intelligence in the development of mobile apps, augmented or virtual reality, and the Internet of Things bring developers tens or even hundreds of thousands of downloads in just a few months. You can create entertainment software and innovative and advanced business applications with AI. Building an AI assistant involves using software tools. They are identical in assembly to CNS neurons. Moreover, these tools can store and process previously received data and then analyze and apply it in future practice. In this object, we are going to talk about how AI works. So, if you want to know how AI is making mobile apps smarter through AI technology, please read the information below.

What AI is: The Basic Principles

artificial intelligence

Let’s see how the AI-powered app works. The basic principle of AI is the ability to make decisions independently. This process is influenced by the input data and, in some cases, by the expected result. To implement it, the developers create an artificial neural network that works with the same algorithms the human brain uses to remember things. These networks use training samples to create charts. These graphs then use the input data to lead to the correct answer.

How to form an AI Application: Choose the Right API

And now, we want to present you to some APIs you can use to develop your AI-based solution.

Mit.Ai

Wit.ai is an application programming interface that provides intelligent analysis of input data (including language-formatted data) based on pre-built training examples and experience gained using your prepared application as part of a specific user. You can easily create a simple AI application like Siri with this API. Wit.ai uses two primary mechanisms. The first determines the central object of the user’s query (in the case of the question “Where to buy a cake?”, this object is “a cake”). The second mechanism determines this part of the object. For example, in our request for cake, this role is “Where to purchase.”

IBM Watson

IBM Watson is one of the world’s initial answers creäte on artificial intelligence. This stage also translates voice data into text and then scours Internet search engines for the correct answer to the user’s question. IBM Watson uses effective filtering mechanisms. You choose the right solution among many others. It should also be said that this software solution is structured differently than many other AI platforms. Instead of looking for the proper logical chain of actions that will lead to the desired result, it implements a multitasking process, running thousands of algorithms simultaneously. Some developers tend towards this type of AI implementation.

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API.Ai

The working principle of Api.ai, created by the Google development team, is almost identical to that of Wit.ai. At the same time, this solution features incredibly accurate entity identification (e.g., queries containing the phrases “IT vendor” and “IT vendor” are treat in different ways and are likely to have different results). In addition, this service has a colossal knowledge base. That is why Api.ai is one of the most valuable solutions to create software whose primary purpose is to answer educational questions.

Amazon AI

Amazon AI is also a popular AI-base platform that can recognize visual objects and human speech (using NLU, ASR, and TTS mechanisms) and implement deep machine learning processes. In addition, this solution is fully adapted to cloud deployment, thus allowing the creation of small applications (an essential feature for mobile developers).

Clarification

The Clarifai platform is something new in the field of AI. This solution analyzes data using capacitive and complicated algorithms. Therefore, applications built on this platform can be fully tailored to a specific user’s experience. This fact makes Clarifai the best option for developers who want to create an AI-based assistant. To integrate it into your application, use the REST API.

Tensor Flow

Tensorflow is also a project by Google developers whose concept is based on generating graphs of artificial neural networks. At the same time, creating a particular diagram is condition not only by the information obtain from the knowledge base but also by the data obtained during the experience with a specific user. Please note that this library is not easy to master. Therefore, its use is not recommend for developers who have not previously had any experience with AI-based solutions.

Conclusion

Mobile AI helps optimize processes, remove obstacles for users and providers, deliver relevant content, enhance end-user engagement, and improve the development process. AI makes mobile apps more extensible, modular, and dynamic and offers superior performance for both developers and users.2

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