How to Integrate Artificial Intelligence in Flutter Applications?

How to Integrate Artificial Intelligence in Flutter Applications

Artificial intelligence is used today in a wide variety of industries — from entertainment and advertising to business decision-making, driving self-driving cars and modeling complex physical processes. Today we will talk about how to integrate artificial intelligence in Flutter applications.

There are hundreds of thousands of apps in the App Store and Google Play, and oddly enough, most of them could become much more interesting and useful if you apply the capabilities of artificial intelligence to them. After all, in fact, if you do not dive too deeply into the forecasts of futurologists, modern Artificial Intelligence is nothing more than well trained recognition and analysis algorithms. And their application to the familiar fields are already able to make our lives much more comfortable.

Studies say that the average speed of applications does not meet the level expected by users, and this is one of the main reasons for abandoning them.

Why Flutter is the Best Choice?

Mobile development has become a serious need for businesses. However, what is missing is the fact that there are already 5 million applications available in a competitive market in various fields and it is becoming increasingly difficult to succeed.

Some companies still believe in the traditional approach to developing and investing in building their own applications. The rest are looking to adopt the latest technologies from the world of cross-platform solutions for greater reach. One such multifunctional product is Flutter.

Flutter is a cross-platform framework that allows you to develop mobile applications with a beautiful interface for Android and iOS devices. Despite the fact that Flutter is still young, it quickly secured the position of the second most popular framework in the world.

Now we will move on to artificial intelligence and its integration into the Flutter application. But before that, we will understand why it was decided to combine Flutter with artificial intelligence.

Artificial Intelligence and Its Growing Impact on Mobile Development

The development of technology has gained momentum again with the advent of artificial intelligence. Since 1950, it has evolved, innovated, and now has become a rising star in the field of mobile applications.

Here are some examples of successful UX augmentation practices:

Personalized recommendations: According to research, 80% of consumers are more likely to buy from a brand that offers a personalized sample, and companies have seen a 20% increase in sales after using this approach.

Chatbot with Artificial Intelligence: Adding a chatbot to a website or mobile app can lead to better customer service. Thus, the chatbot market is projected to grow from $2.6 billion in 2019 to $9.4 billion by 2024, with an annual growth rate of 29.7%.

Voice optimization: The impact of voice optimization on the development of modern mobile applications can provide an excellent level of accessibility and navigation development. Moreover,”Voice assistants” are actively working in the search engines of Google and Yandex, and companies like Apple and Amazon are also using for many years. Today, they not only recognize the spoken words, but also find the song that interests you in their music archives. The opportunity to listen to and download music that you like is very pleasant.

In recent years, Artificial Intelligence has become popular in the mobile application development market, and its adoption will continue to grow, as it brings huge profits, allows you to manage business risks and scale the impact on the application environment.

So far, artificial intelligence technologies have successfully developed in healthcare, education, finance, and e-commerce, but there are niches for launching AI-integrated mobile applications in other promising areas.

Who Has Already Succeeded in Integrating Artificial Intelligence?

Before starting development, a logical question arises whether the integration of AI into a mobile application will be relevant and cost-effective. Let’s study the existing examples of implementing machine learning and artificial intelligence in a Flutter application.

Google

It will be strange if the guys from Google are not the first to use the power of AI and integrate it into their numerous products: Gmail, Google Assistant, Google Translate and others.

Netflix

Netflix has become the leading video streaming app, generating millions of dollars in revenue. Starting with the interface and ending with endless buns, the app keeps users busy for hours. But above all, integration with AI is the main reason for success.

Today, many organizations that serve customers use AI technology to provide quality services. Thus, adding AI and ML to the mobile application has become an ambitious task for companies of all business lines.

AI-integration Methods in Flutter applications

Given all of the above, you may have realized the benefits of using artificial intelligence in applications. Let’s look at simple methods for creating a Flutter applications with artificial intelligence.

Firebase MLKit

MLKit is a part of Firebase that allows developers to quickly import Google’s machine learning experience from the firebase console. Whether you are a beginner or an experienced Flutter app developer, you can quickly implement ML functionality in Android and iOS apps by adding a few lines of code.

Here are some of the best off-the-shelf modern models available on Firebase:

  • text and face recognition;
  • marking images;
  • object detection and tracking;
  • language identification;
  • interface of the AutoML model.

When using this integration method, make sure that your application uses Firebase or host the custom model on a different server.

Models as an API

This is another method of integrating machine learning into an application in situations where you are working with servers and web interfaces, and expect your model to be updated very often.

When using this method, developers wrap the model in an API and host it on web servers. Popular platforms such as AWS Lambda, Google App Engine, Heroku, or Virtual Machine are often involved, because they support running the model and can work as a web service.

Summary

We have analyzed how artificial intelligence “explodes” digitalization and makes smartphones more useful. Over the past few years, it has had a significant impact on the mobile app development market. Therefore, for a long time, development companies have been implementing artificial intelligence in their solutions and successfully producing the best programs that work flawlessly on cross-platforms.


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