By WalkingTree  December 03,  2020

How to integrate AI in Flutter

The concept of Artificial Intelligence (AI) was first introduced during the mid 20th century, with significant advancement and innovations. Now AI has become part of mobile applications as well. 

Some of the most common AI features you can find in an app are personalized shopping recommendations, voice optimization, and AI chatbots. AI has become a buzzword now and adoption of AI is continuing to increase and generating tremendous returns. Companies like Google and Netflix are some of the recent adopters of AI in their applications. 

Flutter is one of the most popular cross-platform frameworks out there which is rapidly increasing. The good news is that AI technology can be easily integrated into a Flutter app. Let’s take a look at how. 

Firebase MLKit – ML kit is a part of Firebase that allows developers to quickly import Google’s machine learning from the firebase console. Any beginner can easily implement the ML functionality to Android and iOS applications by adding a few lines of code.

Models as APIs – It is one of the other popular methods of incorporating machine learning in apps. Developers can wrap the model in API services and host it using web-based servers. Major developers reply on popular platforms like AWS Lambda & Google App Engine.

On-Device Model – On-device models are quite effective, in case you want to perform high-speed inference directly on the devices. The primary way to use this model is to first create them as TensorFlow models. 

Read on to know more about AI and how it can be implemented in Flutter.

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