.png)
AI has become widely used in many applications since the launch of ChatGPT. In fact, it’s already in many mobile apps we use every day. In addition to the dozens of AI assistants that have recently become available, many of the apps we use have already implemented some form of AI.
Below we’ll be taking a closer look at some of the top applications of AI in mobile apps, the advantages and disadvantages of using it, and where we see opportunities for the future.
There are many new and exciting applications of AI in mobile app development. Ranging from language translation to interpretation and note-taking, we take a closer look at the most promising applications below:
Virtual assistants: Alexa, Siri, and Google Assistant are becoming more intelligent by the day. Making use of natural language processing, these applications are able to handle everything from voice-activated instructions to powering smart devices outside of your phone.
Education: A variety of learning apps are making use of AI. Socratic, Duolingo, and ELSA Speak all have their unique applications. Duolingo uses AI to update your course progression as you learn, while Socratic allows you to take a photo of your homework and get an instant explanation.
Personal finance: What if AI could help you with your finances directly? Cleo does exactly that. This app connects to your bank account and provides general advice, roasting or hyping you based on your spending habits.
Customer service: AI-based chatbots can handle queries and guide users at all hours. AI can now also simulate genuine emotions and contextual awareness, making the responses to users even more personalized.
Beyond general AI, Large Language Models and machine learning have made mobile apps more dynamic and responsive as a whole. This has led to highly-improved user experiences. Smartphones are now more capable than ever, and most AI models can easily be run from them. This means you receive instant insights based on real-time data.
Let’s take a look at some of the other advantages of AI in mobile apps.
Using AI-based mobile apps has many powerful benefits. Users can use AI models to generate responses in near real-time, receiving answers that are more unique and person-based than they would from your general Google Search.
Unique responses: Think about AI models like ChatGPT and Bard. Ten people can ask variations of the same question, and they will each receive answers specific to their individual requests. All that work can be close to instantaneous.
Improving language: The other promising benefit is real-time language translation and transcription. With AI apps, you can automatically detect languages and translate them to English or any other language and even have the model read the answer aloud to the user.
Object Recognition Following Eye/Movement Tracking: Integrating CoreML with eye-tracking technology can enhance user experiences in various ways. For example, it can enable applications to identify objects of interest based on where the user is looking. You can scroll between apps on your phone using sight alone.
Education and Gesture Tracking: Gesture recognition, coupled with CoreML, can be valuable for educational apps. It can track user gestures and interactions to offer personalized guidance or feedback. For instance, an app could follow a user's hand movements and provide step-by-step instructions for activities like playing golf.
Healthcare: In the healthcare sector, AI-powered mobile apps improve patient monitoring and diagnostics. These apps can analyze patient data to detect patterns or anomalies, which can be crucial for the early diagnosis of diseases. Think of the health tracker on your phone. What if a doctor could use that information to make a diagnosis directly?
The true advantage of AI is the empowerment of the user. But what about the disadvantages of using this approach in mobile apps?
AI has many benefits, but there are also things you need to take into account before developing an AI-based mobile app.
Creating Relevant Algorithms: Building and training a good AI model takes time. If you want the model to perform as needed, you need a large amount of specific data to lead the model to generate the correct responses.
The Question of Big Data: The reality is that no data is truly free. Most of the big data we use is being monopolized by corporations like Google and Amazon. Since you need so much data to train your model, you need to think of how you are going to access that data prior to building.
AI Bias and Inaccuracy: Remember that AI systems are not perfect and can have biases. If the data used to train the model is biased, it can skew the outcomes and deliver incorrect results. Continuous monitoring is needed to ensure that the results are accurate and unbiased.
Time Investment: Fine Tuning an AI-based model can take time. During this process, developers adjust various parameters and architectures to optimize the model's capabilities. This approach involves training the model on a dataset multiple times, which can take several hours, days, or even weeks depending on the complexity of the model and the size of the dataset.
AI Team Cost: If you don’t have the AI skills in-house, you need to hire an external AI consultancy team that has the knowledge to deliver your application. This can carry some upfront costs to be aware of.
Understanding and meeting these challenges is key to adding AI to any mobile app. Developers need to make use of a balanced approach that takes technical skills, security, and other issues into account.
Now we know what we’re currently working with when it comes to AI in mobile apps. But what about some predictions for the future of this type of development?
There are a few things that are making the future of AI in mobile apps exciting. At present, models can be taught to do one thing at a time - like chatbots for instance. These chatbots are trained to focus on one type of output. But as these models become more intelligent and the databases become more advanced, we’ll see models that are trained to do more at once.
The two goals for the future are speed and power. How far could we push these models to go?
Could we merge AI with the human body, or develop helper bots that can follow us? The goal of AI in mobile apps is not only to better serve the user’s needs but also to anticipate them and engage them long-term.
Think of how we now use smart fridges, driverless cars, and restaurants run by robot servers.
There’s more of this to come where we are headed. To get there, you need a partner who can bring your AI and IoT innovations to the edge. Building apps on the edge means you’ll have less costs in computing power and less time waiting for results.
By leveraging Edge AI with NineTwoThree, you can co-create experiences that transform the way we live, work, and interact with the world around us. Reach out to us to get started today!
