Tuesday 14 July 2020
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10 Ways AI Should Be Built into Mobile Apps

10 Ways AI Should Be Built into Mobile Apps

AI is the future – but in what ways should it be used in modern mobile applications? In this article, we’ll explore the ways in which artificial intelligence should – and should not – be used in today’s apps. Let’s begin.


1. AI Should Be Used Where It Makes Sense

 First things first – AI is not a “magic bullet” or a special feature that will automatically make your application a success. It’s a tool – a feature that should be included (or excluded) only where it makes sense. Don’t fall into the trap of building AI into apps unnecessarily.


 2.  The Right Type of AI Needs To Be Used

From basic machine learning (ML) algorithms, to cognitive computing, deep learning, and AI recommendation engines, there are many different types of artificial intelligence – and you need to choose the right one for your particular needs.


3. Develop AI Using the Right Mobile Platforms

If you’re interested in machine learning, you can use tools like Apple Core ML, Caffe2, and Google TensorFlow to develop machine learning applications on both mobile and other platforms.


4.  APIs Can Be Used to Connect Third-Party AI

It’s not always necessary to create a “bespoke” AI for your application. Today’s APIs make it easier than ever to connect a third-party AI or machine-learning algorithm – which makes the development process faster, simpler, and easier for you.


5. AI Should Only Be Used with The Right Data Sets

 AI simply doesn’t work unless you have the right data to feed your algorithm. Before undertaking any AI project, ask yourself where your data will come from – and if that data will provide insights and features that are truly useful.


6.  Developers Should Know Where Their Data Comes From

 Just as important as finding the right data is knowing where your data comes from. Data should be reliable and clean – if it isn’t, AI development will stagnate until the datasets are fixed.


7. Development of AI Should Start Small

It’s a bad idea to try to create a fully-fledged, full-scale AI within just a few iteration cycles. You need to start with a small dataset, and iterate on your algorithms until they are responding properly on a small scale. Then, the algorithm can be expanded.


8.  AI Should Be “Behind the Scenes”

Your AI does not have to be front-and-center – and in many cases, it’s better to have it working in the background, as a recommendation algorithm or a sorting algorithm.


9.  AI and Machine Learning Should Boost Your App’s Best Features

Again, it’s important to only use AI where it makes sense. Don’t just tack AI onto your app because you think it would be cool, or executives want you to use machine learning. AI should work with your app to make it better – not just be an “extra” add-on.


10. Understand the Model You’re Using (Before You Use It)

There are many easy-to-use frameworks and platforms for AI and Machine Learning. And before you choose one, you should understand what it does, how it was trained, and what types of applications it was designed for. This can save you a lot of time (and headaches) in the long run.


Use the Power Of AI On Mobile With These Development Tips!

AI is more than just a buzzword – but careful consideration needs to be taken before using it in your mobile app. So consider these 10 ways to use AI in mobile applications before you get started on your next development project!

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