How To Create an App with AI: What You Need To Know

Lately, the role of Artificial Intelligence (AI) in app development and AI platforms has grown massively.

ChatGPT, Bard, Midjourney, and Grammarly — Just to name a few!

As we enter an era marked by exciting developments in AI and Machine Learning, it is essential to understand how these technologies are transforming the landscape of app development.

So how do we build an AI app?

During a recent interview with EB Pearls‘ AI and Machine Learning expert, Roshan Manandhar, we gained valuable insights into the most thrilling trends and advancements taking place in AI mobile apps.

From sophisticated recommendation systems to intelligent chatbots and image classification, discover how AI has revolutionised the functionalities and user experiences in mobile and web applications.

One of the most exciting recent developments in AI and Machine Learning is the move towards generative AI. Roshan Manandhar specifically mentions “Large Language Models” (LLM) and the trend of creating open-source language models:

“In terms of generative AI apps and chatbot APIs, we have been experimenting with open-source LLMs and suggested using websites like Hugging Face for open-source models.”

However, he continues, “One common misconception in AI and Machine Learning is that it can do everything, but every language model has limitations.”

Media and popular culture often portray AI as a super-intelligent entity capable of extraordinary actions. The truth is that AI, including Natural Language Processing (NLP) and AI algorithms, are designed for specific tasks and functions within mobile app development.

While it excels at certain tasks, such as language translation or chatbot interactions, it operates within predefined parameters. AI lacks a comprehensive understanding of language, context, and the ability to make ethical or moral decisions.

Furthermore, AI relies heavily on data for its operations. In mobile app development, the quality and quantity of data play a crucial role in determining the performance of an AI application. Biased or limited data can lead to biased results, highlighting the importance of quality data and the potential limitations.

Using a generative AI app builder like Gen App Builder, developers can streamline their processes, exemplifying a significant leap forward in the evolution of app development. Such platforms leverage the power of AI to assist in generating code, proposing design elements, and streamlining various development phases.

More traditionally, the incorporation of AI in app development involves a series of crucial steps. EB Pearls representative, Roshan, tells us that the key lies in understanding the application of AI techniques in different stages of the development process:

The initial stage in AI model development hinges upon meticulous data gathering, which acts as the cornerstone for the construction of a robust model. 

This critical phase involves collecting diverse datasets, including text, images, or numerical data, to provide a comprehensive basis for training and modelling.

After the comprehensive collection, the subsequent pivotal step revolves around data preprocessing. In this phase, data is subjected to transformation and validation processes, ensuring data quality and consistency.

Through these meticulous processes, the raw data is refined into a high-quality dataset, setting the stage for successful AI model development.

Roshan highlights the significance of selecting appropriate AI tools and frameworks. Selecting suitable AI tools and frameworks is pivotal for successful development. Understanding project requirements and specific goals aids in determining the most fitting AI frameworks, such as:

Consider factors like scalability, ease of integration, and compatibility with the intended tasks. Assess the capabilities of various frameworks and tools, ensuring they align with the project’s objectives, and facilitating a streamlined and efficient development process.

The process involves careful implementation, validation, and optimisation. It’s recommended to fine-tune the models to interact harmoniously with the project’s architecture. 

This phase also establishes the foundation for further testing to ensure the models perform cohesively and efficiently.

As part of the process, Roshan Manandhar suggests that preparing and evaluating data is a crucial step in the development process:

When we talk about machine learning, there are two primary methodologies: supervised and unsupervised learning. The process typically begins with data collection, followed by a rigorous evaluation and subsequent preprocessing of the gathered information.”

He continues, “Once the data is prepared, the next step involves model evaluation, which can be executed using a variety of tools. For instance, in regression analysis, tools like Root-Mean-Square Error or Max Error come in handy to assess the model’s performance.”

On the other hand, when dealing with a classification model, specific tools are employed to evaluate its effectiveness. Following the evaluation, adjustments to the data are made, and the model is refined through retraining, with the ultimate goal of achieving the highest possible accuracy”, Roshan says.

Unfortunately, achieving high accuracy in machine learning models can be challenging, as there are many variables involved, and missing an important variable can affect the accuracy. This is why fine-tuning a model can truly turn a project around.

Looking at the EB Pearls portfolio, we have apps like Intro and Baxta that leverage the power of AI to match users by filters like interests and location, offering personalised recommendations. 

The outcome is a tailored user experience that goes above and beyond to enhance user engagement and satisfaction.

The development process involves certain technical complexities associated with training AI models, including data privacy and accuracy of results. 

Our team integrated AR technology to provide interactive video experiences and an AI-based system to facilitate intelligent matching and recommendations.

Additionally, think of the many uses of AI in our everyday routines. From indispensable tools like maps, navigation apps, and text editors to search engines, recommendation algorithms, and customer support chatbots, AI makes up a significant part of our lives. 

Some may say that it’s become challenging to imagine a world where these AI-driven conveniences are not an integral part of our daily existence.

When it comes to app development, the popularity of AI is increasing at an unprecedented rate, presenting exciting opportunities for individuals and businesses alike.

AI-powered apps can offer personalised recommendations, seamless interactions, and intelligent responses, tailoring user experiences to a level of precision that was previously unattainable.

For app users, AI brings tangible benefits to daily life. From highly accurate virtual assistants that simplify tasks and answer questions to intelligent recommendation systems that curate content and services according to individual preferences, the advantages are a no-brainer.

As AI continues to evolve, it’s essential to stay updated on the latest advancements and open-source resources, ultimately harnessing the power of AI to create innovative, user-centric applications that define the future of app development.Bring your app idea to life with your trusted AI app development company, EB Pearls. Contact us today and our team will reach out shortly with a detailed quote.