How Artificial Intelligence is Transforming the World of Mobile App Development

Artificial Intelligence (AI) has been a favorite topic of science fiction writers and moviemakers for decades. It is seen as the harbinger of an apocalyptic world where robots enslave the human race. The reality is far from that, because as we’ve seen, if anything, AI helps improve our lives and businesses.

It goes without saying that the goal of artificial intelligence is to make our lives easier and more dynamic. It could be used for simple decision-making or to solve highly complex issues. No matter what kind of business one may have, there are chances for it to benefit from incorporating some form of AI into its operations either now or in the near future. This article will explain how mobile app developers can leverage artificial intelligence today with examples taken from some of our own projects.

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Why AI is Increasingly Being Incorporated Into Mobile Apps

Before getting into the details, let’s try to understand some basics first. We will use a very simple example to explain how artificial intelligence in mobile apps can work. Let’s say we have a mobile app that tracks user locations and shares them with other devices in the vicinity for a multiplayer gaming experience or some collaboration purpose. For this, we need a way to share information between multiple devices so they can all update their views of the data in real-time.

Let’s assume for now that we are using one of the more traditional technologies like Bluetooth or WiFi Direct. The exact way in which information is shared between devices depends on the developer and the particular technology being used. However, no matter what the technology, there is a simple rule: for two devices to be able to share information they need to be within range of each other and Bluetooth-enabled. This is an example of a physical limitation that we can call a dependency.

We also have software dependencies. It may be necessary for the app to have an internet connection for it to work. This is a software dependency because even if all pixels in our screen are turned off it doesn’t mean the app has stopped working – its functions will still fail when they try to access web data sources.

A third category of dependencies is behavioral. In our Bluetooth example, imagine that it isn’t possible to turn on Bluetooth from within the app without restarting it first. This is now not a physical or a software dependency but a behavioral one enforced by the app’s architecture.

Of course, all of these dependencies can be managed by developers and may have to be taken into consideration when designing and writing code. But, what if we could cut the number of dependencies and write a mobile app that was completely independent? The answer to this question is artificial intelligence!

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What does AI Mean for Mobile Developers

Mobile developers often have to face problems with dependencies during their work. AI will allow developers to do the following:

• Reduce code size.
• Improve testability and stability of the app.
• Eliminate dependencies between software components.

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Types of Artificial Intelligence

Since we have already touched upon this topic, let’s now try to understand what type of AI is relevant for us as mobile developers. There are two types that we need to know about: Weak and Strong AI. As you expect, weak AI refers to something that is not very intelligent, and strong AI refers to something that is closer to human-level intelligence, at least in specific areas.

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Weak AI and Mobile App Development

The good news for developers is that we don’t need strong AI in order to enjoy the many benefits offered by such advanced technology. The first area where we can use weak AI is user personalization. After all, it’s a known fact that every time a user runs your app they will have different needs and will interact with your app in a different way!

Your job as a developer is to find ways to adapt your app to each user. We can do this by performing simple tasks such as asking users for their name and age, location, and gender. While this may seem like a trivial example it is useful because we can make sure that the information we receive from these questions allows us to show the user personalized content – i.e., something specific to them – within our app. However, you might want to go further than this and create personalized experiences according to each user’s interests.

Another use is to provide automated responses during phone calls. If a user takes a picture within our app and then calls customer service, we can provide personalized, automated responses during the phone call. We can do this by using Natural Language Processing (NLP) so that we can receive, process, and respond to questions from users in a more efficient way.

Here’s a special example: a user calls and says “My battery is low. What can I do?”, the NLP feature in our app will automatically provide an answer such as “You can recharge your device” or “Or you can turn on Airplane Mode”. This not only improves user experience but also reduces costs for our company since we don’t have to hire people to give such simple but personalized responses in a phone call.

Another example of using NLP is to provide answers for FAQ pages. Instead of providing static answers, we can use an algorithm that will process user requests and provide them with a personalized answer. Of course, giving users the ability to ask questions related to features within our app will help us provide better customer service.

Lastly, we can use weak AI to optimize the user interface of our app. If we decide that we want to use a hamburger menu in our app we can ask NLP to determine the best way of positioning it. In fact, since this is a very common feature within mobile apps it would be worth asking several users to try our app and see where they click the most. This will help us to optimize the positioning of our hamburger menu.

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Mobile App Development using Strong AI

Cute living emojis are one of the main reasons why people love using apps such as Snapchat and Instagram. Creating hundreds of emojis isn’t very easy for companies to do, mainly because such a task requires the muscle of a huge team and lots of resources.

Snapchat has allowed users to generate custom selfies which were then turned into animated emojis. In other words, instead of hiring an army of designers and animators to add animations to the pictures sent from their app, Snapchat simply used AI algorithms and had these tasks performed automatically.

In another example, researchers from Adobe have created an algorithm that can create realistic images of people’s faces. While this may not seem like a big deal, it can be very important for certain companies that want to use images of people within their apps. If we are creating an app that allows users to share content related to celebrities then being able to create realistic images would be extremely useful.

This is just one type of algorithm available. There are hundreds of others, including those designed for object recognition, text generation, and robotics.

To read the full article, visit our website: How Artificial Intelligence is Transforming Mobile App Development (sunverasoftware.com)