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    How Artificial Intelligence Is Making Mobile Apps Smarter

    How Artificial Intelligence Is Making Mobile Apps Smarter

    Il'ya Dudkin


    8 min read

    Artificial intelligence app

    Thanks to artificial intelligence in mobile app development, developers can enjoy hundreds or even thousands of downloads in only a few months. By creating artificial intelligence apps, you are not simply delivering entertainment software to users, but also smart and advanced enterprise applications. For example, building an AI-powered virtual assistant means using the same software tools that are identical in structure to the central nervous system (CNS). These tools are capable of remembering and processing previously received data and then analyze and apply it in future practice. Now let’s take a look at how AI is making mobile apps smarter.

    The Basics of AI

    The main principle in artificial intelligence app development is the capability to make independent decisions. This process is influenced by both input data and, in some cases, the expected result. In order to implement this, developers create an artificial neural network, which operates according to the same algorithms like the ones that the human brain uses to memorize things. Such networks use training samples to create graphs. Then, these graphs use input data to lead to the correct answer.

    Of course, the program code, required for building such a network has an extremely complicated structure. So, it’s hard to build your own artificial intelligence app and if you ask any software developer about the easiest way to build an artificial intelligence app, they will advise you to use special APIs. The most popular APIs are Api.ai, Wit.ai, Clarifai, Tensorflow, Amazon AI and IBM Watson, which we will briefly review further.

    Artificial intelligence app development

    Choosing the Right API

    Let’s take a look at some APIs that you can use to develop your own AI-based solution:

    Tensorflow – This Google created platform is based on the artificial neural network graphs generation. At the same time, there is a condition to generate a graph not only by the information received from the knowledge base but also from the information you received from the experience with a particular user. Keep in mind that this library is not easy to master, therefore it is not recommended to be used by developers who have no previous experience with AI-based solutions.

    IBM Watson – This is one of the world’s first solutions based on artificial intelligence and one of its best features is that it will also translate voice data into text and then search for the right answer to the user’s questions via internet search engines. It uses a uses amazingly powerful filtering mechanisms i.e. they choose the correct solution among many others. The structure of this software solution is different from many other AI platforms because, instead of looking for the correct logical chain of actions leading to the desired result, it implements a multi-tasking process, in which thousands of algorithms are executed simultaneously, which is why many developers like this AI implementation type.

    Wit.ai –  If you need to intelligently analyze the input data (including data in voice format), this application programming interface is definitely for you. It is based on previously created training samples and experience gained while using ready-made applications by a given user. Thanks to this API, developers can easily make a simple AI app such as Siri since it uses only two basic mechanisms: the first one determines the central object of the user request (in the request “Where to buy a pizza?” this object is “a pizza”). The second mechanism determines the object part. For example, in our request for pizza, this role is “where to buy”.

    Api.ai – This API was also created by Google developers, with a goal of being almost identical to Wit.ai. At the same time, this solution distinguishes itself by an amazingly precise entity identification (for example, requests with phrases “computer hardware vendor” and “computer hardware supplier” will be processed in different ways and most likely will have different results). This service also has a colossal knowledge base, which is why Api.ai is one of the most useful solutions for creating software, the main purpose of which is to answer educational questions.

    Amazon AI – Amazon AI is also a well-known platform based on AI, which is able to recognize visual objects, human speech (using the mechanisms of NLU, ASR, and TTS), and implement the deep machine learning processes. This solution is fully adapted for cloud deployment and, therefore, allows you to create small-sized apps (this is an extremely important feature for mobile developers).

    Artificial intelligence apps

    New Opportunities for App Development

    Thanks to the rise of AI, there are lots of mobile app possibilities. Even though AI has been playing a crucial role in app development for quite some time now, starting with Siri, it has the potential to advance much more in the coming years. Machine learning now pretty advanced and users now expect much more flexible algorithms for seamless and intuitive experiences. Such new availability and advancement of AI and machine learning are causing a monumental shift in the way businesses, developers and users perceive intelligent interactions with mobile apps.

    Even though companies are quickly pursuing AI technologies, we have only reached the tip of the iceberg in terms of its true potential. We can describe intelligence as the ability to perceive information and retain it as knowledge to be applied towards adaptive behaviors within a context. Therefore it’s important not to over-promise the abilities of your product(s) since users expect AI interfaces to learn and many fall short of true AI and deep learning.

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