How to design an artificial intelligence interface?

In this article, I’ll teach you how to design an artificial intelligence interface but first, let’s find the right model for your platform and then implement it. Currently, there are many models wanting to acquire users. If only someone would build them an aesthetic and intuitive interface to interact with them…

Meta with the Llama family, Google with Gemma and Mistral AI are examples of companies that offer you their AI so that you can integrate them into your platforms. If you want to know about the larger models, I recommend this blog.

1. Explore and select a model on Hugging Face

Steps:

First, you need to choose the right model for your application. I recommend using the Hugging Face platform, which is one of the largest repositories of pre-trained models.

• Defines the model requirements: type of task, precision, and necessary computation.
• Explore available models: use filters to search for models that fit your goals.
• Try the Hugging Face playground: xperiment with the selected models.
• Check documentation and license: make sure you understand how to use each model and its license restrictions.

2. Rigorous evaluation

To decide which model to use:

• Defines evaluation metrics.
• Test dataset: use a test data set to evaluate the performance of each model.
• Model comparison: run tests and compare the results. If necessary, retrain the models with your datasets.

3. Design the UX and UI

Once you have selected the artificial intelligence model that best suits your needs, the next step is to design a user interface that is both intuitive and functional. The goal is to design an artificial intelligence interface that makes it easy for users to interact with the model.

Use modern design tools

To design the artificial intelligence interface, tools like Figma will allow you to create functional prototypes that you can share and test in real time. If you are interested in delving deeper into intuitive interface design techniques, we invite you to explore the additional resources we have at Kryztal.

Understand your user

Before diving into the concrete design, it’s vital to understand your app’s users:

• Identify users: define who your end users are. Are they technicians, data scientists, or general public?
• Investigate their needs: understand the problems and challenges your users face. What do they hope to achieve using your platform?
• Define user bbjectives: clearly establish what your users want to achieve when using your interface.

Design the information structure

Once you understand your users, organize the information in a way that feels natural and efficient for them.

1. Interface map: design how the elements will be organized in your application. Make sure users can navigate intuitively and achieve their goals with as little effort as possible.
2. Wireframe: develop an initial wireframe that includes the main components of the interface. This includes how and where key elements such as text fields, buttons, and display areas will be placed.

Prototypes and copywriting

1. Prototype in Figma: based on your wireframe, develop a detailed prototype in Figma. Here, you can experiment with colors, fonts, and other visual elements.
2. Write clear texts: write texts that clearly guide the user through the interface. Includes descriptive labels, help messages, and other instructional text.

Essential user interface elements

Each interface can vary depending on the AI ​​model selected, but there are common elements that you should include to improve usability:

• User input text field: where users can enter data or ask questions.
• Submit query button: a clear and visible button that users can press to submit their input to the AI ​​model.
• Response display area: a dedicated space to display the responses provided by the AI ​​model.
• Process indicators: elements such as spinners or progress bars that indicate that the query is being processed.

4. Develop the front end

Once the interface has been designed in Figma, it is time to transform those designs into a real application.

• Choose a framework: use modern frameworks such as React, Vue.js, or Angular to develop your interface. These frameworks make it easy to create dynamic and responsive web interfaces.
• Connect to the AI ​​model: your application needs to communicate with the AI ​​model to send questions and receive answers. It implements this communication using API tokens to authenticate and authorize requests to the model.
• Collaborative development: this step is technically demanding and can significantly improve your skills as a frontend developer. Consider collaborating with other developers to share knowledge and divide work.

5. Deployment

Finally, when your app is ready:

• Deploy your application: use platforms such as Vercel, Netlify, or AWS to deploy your application. These platforms offer facilities to put your application online quickly and securely.
• Monitor and update: watch how users interact with your app and make updates based on their feedback. The goal is to quickly iterate and continually improve based on user feedback…

Summary

Start by evaluating which model suits you, do a lot of testing, once you have it, design the artificial intelligence interface and then implement it. Put it on the market as quickly as you can to do many iterations.

It is a complex process; In addition to being technically demanding, you need to choose a model that provides something new and is in demand. However, the fact that the barrier to entry is high means that the opportunity is real. If you are a front end developer looking to undertake this methodology, it is really useful for you.

Read this blog in spanish here.