Artificial intelligence is applied in a great variety of industries nowadays— from entertainment to business decision-making, manufacturing self-driving cars and figuring complex physical processes. Here we will discuss how is it possible to integrate artificial intelligence in Flutter applications.
There are so many apps in the App Store and Google Play, and most of them could become much more attractive and useful if you choose to introduce several capabilities of artificial intelligence to them. Because after all if you do not go too deeply into the scary predictions of false futurologists, modern Artificial Intelligence is nothing more than well set and trained recognition and analysis algorithms. And their benefits in the familiar fields are already able to make our every day lives much more convenient.
Research shows that the average speed of applications does not meet the level desired by users, and this is one of the main reasons for deleting them.
What Makes Flutter the Best Choice?
Mobile development has become one of the main investment industries for businesses. Yet, what is missing is the fact that there are already 5 million applications available in a free market in various fields and it is becoming increasingly challenging to truly succeed.
Some enterprises still are governed by the traditional way of developing and investing in creating their own applications. The rest are looking to introduce the latest technologies from the world of cross-platform solutions for greater results. One such multifunctional tool is Flutter.
Flutter is a popular cross-platform framework that lets you develop mobile applications with an exceptional interface for Android and iOS devices. Not taking intro consideration that Flutter is still young, it managed to quickly secure the position of the second most popular framework in the industry.
Now let’s move on to artificial intelligence and its integration into the Flutter application. But before we do that, it would be great to understand why it was decided to alter Flutter with artificial intelligence.
Artificial Intelligence and Its Influence on Mobile Development
The development of technology was on the spot light again with the progress of artificial intelligence. Since 1950, it has grown, invested in, and now has become the main force in the field of mobile applications.
To look at some examples of successful UX augmentation practices:
Personalized recommendations: According to research, 80% of consumers are more likely to purchase from a brand that provides a personalized sample, and companies have experienced a 20% increase in sales after using this tool.
Chatbot with Artificial Intelligence: Introducing a chatbot to a website or mobile app can result in a better customer service. Therefore, the chatbot market is forecasted 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 effect of voice optimization on the development of modern mobile applications demonstrates an excellent level of accessibility and navigation improvement. Furthermore,”Voice assistants” are actively operating in the search engines of Google and Yandex, and companies like Apple and Amazon are also using them for many years now. These day, they not only recognize the spoken words, but can even search the song that interests you in their music database. This option to listen to and download music that you like is very satisfying.
Recently, Artificial Intelligence has become rather common in the mobile application development market, and its adoption will continue to expand, as it brings enormous profits, lets you manage business risks and scale the impact on the application environment.
Thus far, artificial intelligence technologies have successfully been integrated into healthcare, education, finance, and e-commerce, but there are certainly more niches for launching AI-integrated mobile applications in other promising areas.
Who Has Already Mastered Integrating Artificial Intelligence?
Before beginning development, a reasonable question arises whether the integration of AI into a mobile application will be applicable and productive. Let’s go through some existing examples of combining machine learning and artificial intelligence in a Flutter application.
It would be absolutely weird if the guys from Google were not the first to apply the power of AI and add it into their products: Gmail, Google Assistant, Google Translate and others.
Netflix
Netflix has now become the leader of video streaming apps, getting millions of dollars in revenue. Everything in the interface and endless suggestions, is trying to keep users busy for hours. But most importantly, integration with AI is the very reason for its success.
Today, many corporations that serve customers apply AI technology to run quality services. Therefore, adding AI and ML to the mobile application has become a necessary task for companies of all business missions.
AI-integration Techniques
Considering all of the above, you must have understood the advantages of using artificial intelligence in applications. Now let’s check out a few simple techniques used for creating a Flutter applications with artificial intelligence.
Firebase MLKit
MLKit is an active component of Firebase that lets developers import Google’s machine learning database straight from the firebase console. Even if you are a beginner or a professional Flutter app developer, you can easily implement ML functionality in Android and iOS apps by inserting a few lines of code.
Here are some of the latest off-the-shelf models accessable from Firebase:
- text and face recognition;
- identifying images;
- object detection and tracking;
- language identification;
- interface of the AutoML model.
When choosing this integration method, you need to make sure that your application uses Firebase or hosts the custom model on a different server.
Models as an API
This is another pattern of integrating machine learning into an application in cases where you are running servers and web interfaces, and require your model to be updated often.
When applying this method, developers include 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 opt for running the model and can operate as a web service.
Conclusion
We have reviewed how artificial intelligence affected digitalization and modern innovations industry in particular. Over the past couple of years, it has had a great impact on the mobile app development market as well. For quite some time, development companies have been incorporating artificial intelligence in their products and successfully delivering the best programs that run impeccably across many platforms.
