ChatGPT and 5 More Neural Networks for Designers: Putting It to the Test

Contents:

• Context and Task
• Pre-Project Research with ChatGPT, Chatsonic by Writesonic, and the Edya Telegram Bot
• CJM in ChatGPT and SetGPT
• Developing the Application Structure, Defining the Main Screens and Their Interactions
• Developing the Application's Visual Style in Midjourney and Stable Diffusion
• Conclusion

The discussion of artificial intelligence has rapidly evolved from the question, "When will neural networks replace designers?" to a more in-depth analysis of which specific work tasks should be delegated to algorithms. It's important to consider how AI can optimize design processes, increase efficiency, and free up time for creative work. Neural networks can handle routine tasks such as image processing, template generation, or data analysis, allowing designers to focus on more complex and creative aspects of their work. Discussing the role of AI in design opens new horizons for collaboration between humans and machines, creating opportunities for innovative approaches to creative projects.

Ivan Korabelnikov, art director of the CreativePeople agency, and a senior product designer at the IT company AWG decided to test the capabilities of six neural networks. Their main task is to study how these tools can contribute to the creation of interfaces and whether they are really effective in this process.

Art Director at CreativePeople, specializing in UX/UI design, has over five years of experience in this field. His portfolio includes such clients as Ekonika, Raiffeisenbank, and Kaspersky Lab. Expertise in user interface development and user experience improvement allows him to create intuitive and attractive solutions for business.

Senior Product Designer at AWG with over six years of experience in user interface design. During her career, she has collaborated with well-known companies such as Tanuki, Leroy Merlin, VinLab, and Lenta. Specializing in creating intuitive and aesthetically pleasing interfaces that enhance user experience and facilitate successful interaction with products.

Watch time is an important metric that reflects the duration of time users interact with content. This metric is especially important for video and multimedia materials, as it helps assess audience interest and content effectiveness. Increased watch time may indicate that the content is engaging and useful to viewers, which in turn can positively impact search engine rankings. To optimize watch time, it is necessary to create high-quality content that meets the needs and interests of the target audience. Strategies aimed at user retention, such as interactive elements, interesting headlines, and visually appealing design, can significantly improve this metric. Therefore, watch time plays a key role in the success of digital content and its online visibility.

Text reworking with SEO in mind and content improvement:

The video is 1 hour and 26 minutes long. This time is ideal for deep dives into a topic, allowing viewers to gain the necessary information and absorb key points. We recommend allowing sufficient viewing time to fully appreciate the material presented. Remember to take notes to better retain important aspects.

Reading time is an important factor that influences text comprehension. It allows readers to estimate how long it will take to read the material. Optimizing reading time can improve content usability and enhance user experience. Considering the average reading speed, you can tailor the text to make it more accessible and understandable. This is especially true for online content, where users' attention often wanders.

To improve reading time efficiency, we recommend using short paragraphs, clear headings, and lists. This approach helps readers quickly find the information they need and makes the text more structured. It is important to remember that the simpler and clearer the material is, the more likely the reader is to remain interested and continue reading. Optimizing content for reading time helps increase engagement and reduce bounce rates on the website.

Thus, paying attention to reading time becomes a key aspect when creating high-quality content, which directly impacts its success in search engines and audience engagement.

Saving is an important aspect of financial planning, allowing people and organizations to effectively manage their resources. Reducing unnecessary expenses and optimizing the budget help achieve financial stability and ensure savings for the future. Effective savings strategies include analyzing current expenses, finding alternative sources of income, and integrating frugal practices into everyday life. Savings can be achieved not only at the personal level but also in business, where process optimization and cost reduction contribute to increased profits. It is important to remember that even small changes in expenses can lead to significant financial results in the long term.

Optimized text:

The video length is 1 hour 18 minutes. This time is ideal for a deep dive into the topic, allowing viewers to fully understand the content. During this hour and eighteen minutes, it is possible to explore important aspects that will help better understand the issues under discussion. This duration helps to retain the audience's attention and ensure the quality of information perception.

Context and Task

The designers chose an application for recognizing recipes from photographs as a platform for their experiments. The main goal is to explore the possibilities of integrating neural networks into the design process of this product.

In the process of designing an application, especially in the field of artificial intelligence testing, it is important to distinguish three key stages. These stages help ensure high quality and efficiency of AI performance. The main processes include requirements analysis, test case development, and results evaluation. Requirements analysis provides a deeper understanding of the tasks that the AI ​​must solve, which contributes to more accurate testing. Test case development provides a systematic approach to testing the functionality and performance of the system. Finally, results evaluation helps identify problems and improve algorithms, which ultimately increases the overall effectiveness of the application. These three stages are fundamental to the successful testing of AI during the design process.

• pre-design analytics,
• user journey design,
• design concept visualization for the client.

Pre-design research with ChatGPT, Chatsonic by Writesonic and the Edya Telegram bot

Before starting to develop design solutions, it is important to deeply study the product, conduct thorough analysis and research. It is necessary to ask the client the right questions during the brief and find out the current trends and needs in a specific market niche. This will allow you to create more effective and targeted solutions that meet user expectations and market requirements. A deep understanding of the product and its environment is the key to a successful design.

When developing an application, it is important to ask the client a number of key questions to understand their needs and expectations. Start by clarifying the purpose of the application: what problem should it solve and what value will it bring to users? Discuss the target audience: who will be the primary user of the app and what are their preferences? Clarify what features and capabilities must be included in the app to achieve the stated goals.

It is also important to determine the platform the app will run on: will it be a mobile, web, or cross-platform solution? Discuss the design and user interface: are there any preferences for style, color scheme, and overall feel? Be sure to clarify the project's budget and timeline to assess its feasibility.

Ask questions about competitors: which apps does the client consider successful and why? What are the key factors that will help their app stand out from the crowd? Finally, discuss plans for promoting and marketing the app after its launch to ensure its success in the market. These questions will help create a clear understanding of the project and lay the foundation for successful app development.

• ChatGPT returned a comprehensive list of open-ended questions, breaking them down into categories.

App Monetization: Do you intend to generate revenue from this app? If so, what methods do you plan to use – paid downloads, subscriptions, or other options?

App Goal: What is the key goal you want to achieve with this app? What actions do you expect users to take?

• Writesonic returned similar questions to ChatGPT, but in addition to open-ended questions, offered choice options and hypotheses.

The purpose of the app is to understand what exactly the client wants to achieve with it. This could be creating a simple recipe book or adding additional features such as shopping planners, a dish rating system, and other amenities that will improve the user experience. It is important to consider the user's needs and offer solutions that will help them effectively use the application to achieve their goals.

• Edya produced the same result in meaning as the other two neural networks.

Testing results are an important step in the evaluation and analysis process. They provide objective data on the performance, reliability, and functionality of the tested objects. Correct interpretation of test results helps identify weaknesses and highlight the product's strengths.

Test results analysis involves comparing the obtained data with established standards and requirements. This allows not only to assess the current state but also to develop recommendations for further improvement. It is also important to consider the context in which testing was conducted to make conclusions more accurate and substantiated.

Effective use of test results can significantly improve product quality and user satisfaction. Regular testing and analysis of its results help identify potential problems early in development, ultimately saving time and resources.

ChatGPT has provided the most comprehensive list of questions that can be useful for UX/UI designers. Designers can use these suggestions in their practice and supplement them with their own questions to create a more detailed brief.

The design process is a transition from chaos to clarity, where we identify clear requirements for the product and its solutions, and determine visual aspects. To improve the quality of pre-design research, it is useful to use neural networks. Their structured responses serve as an effective tool that helps capture all important details and ensure no crucial information is missed. Using neural networks in the design process helps systematize data and improve the final product.

To obtain the most comprehensive and engaging set of questions for a brief, it is recommended to consult with multiple artificial intelligence systems. This will allow for a diverse pool of ideas and approaches, significantly enriching the brief's content and improving its quality. Using different AI systems will help to identify key aspects and nuances that may be missed when working with a single source.

ChatGPT, Writesonic, and Edya provided interesting questions, but I do not recommend using them in their original form during the briefing. It's better to tailor them to the specific goals and context of the discussion to obtain more valuable results.

They need to be carefully tested and compared with the actual scenario and the client's key points. This will ensure the content is accurate and meets expectations and requirements.

Are there currently similar apps that allow you to recognize recipes from photos? Such apps offer a number of advantages, including the ability to quickly find recipes, ease of use, and availability of ingredient information. However, despite their advantages, they face certain challenges. One of the main difficulties is image recognition accuracy, which can vary depending on the quality of the photos and lighting. In addition, such apps often fail to correctly identify complex dishes or ingredients, making it difficult to obtain an accurate recipe. It is also worth noting that some apps may be limited to only certain cuisines or cooking styles, which reduces their versatility. It is important to continue developing image recognition technologies to improve the quality and expand the functionality of such apps.

• ChatGPT has shown a list of recipe collection apps. But they are not competitors and adequate analogues of the application for recognizing recipes from photos.

Some of the mentioned problems turned out to be useful and informative. Artificial intelligence highlighted important aspects such as recognition accuracy, difficulties in identifying dishes, language limitations, and regional differences. These factors play a key role in improving algorithms and enhancing the performance of recognition systems.

• Writesonic provided identical and limited information. The problems he listed are not 100% relevant for a food recognition app: limited database, limited variety of available recipes.
• Edya cited the Paprika and Spoonacular apps as examples, and some of his answers turned out to be inappropriate.

Test Results

Testing is an important stage in any project, allowing you to evaluate its effectiveness and identify potential shortcomings. Test results provide valuable data that aids in further product improvement. Analyzing the results helps determine how well the project meets the specified requirements and identify areas requiring improvement. It is important to document the test results to ensure transparency and enable subsequent analysis. Testing can not only confirm the system's functionality but also provide recommendations for its optimization and improved user experience.

Artificial intelligence provided an irrelevant list of similar applications. You shouldn't rely on such information, so it's important to do your own research.

ChatGPT may sometimes provide inaccurate information because of the way its algorithms are designed. It can generate ideas, but it can't always gather reliable facts.

In this experiment, we found that AI bots were less effective in helping us with market research compared to using a list of questions to generate a brief.

Neural networks often provide vague and general answers that may not reflect reality. Therefore, relying on neural networks to gather factual information is not recommended. Artificial intelligence can generate fictitious names of competing apps that cannot be found in the App Store or Google Play because they simply don't exist. This highlights the importance of taking a critical approach to AI-powered information and verifying data from reliable sources.

It is important not only to consider customer requests but also to conduct thorough market research. It is necessary to analyze existing applications, their advantages and disadvantages. This will help avoid repeating competitors' mistakes and create a unique and high-quality product. This approach not only improves functionality but also enhances market competitiveness.

Neural network responses in this case are less high-quality and relevant. ChatGPT, for example, only offers recipe collections and lists general benefits without in-depth analytics. A similar situation is observed with Writesonic and Edya: although their texts differ, they also do not provide useful information, remaining superficial and uninformative.

General and uninformative phrases about "simplicity," "convenience," and "adaptability" will not provide real benefit to an interface designer. It is important to focus on specific aspects that truly impact the user experience and interaction with the interface. Effective interface design requires considering usability principles, visual hierarchy, and adaptation to different devices. Specific examples and practical recommendations will help designers create more intuitive and functional solutions.

An app for recognizing recipes from photos can be useful for various categories of users. Firstly, these are amateur cooks who seek inspiration for new dishes and want to experiment in the kitchen. Secondly, these are professional chefs who want to expand their culinary horizons and discover interesting recipes. Thirdly, these are parents who want to diversify their children's menus and can easily find recipes using familiar ingredients. These are also students living away from home who need to cook for themselves and want to quickly find simple and quick recipes. Finally, gourmets seeking new culinary discoveries can use the app to find original recipes and explore new cuisines. Thus, the photo recipe recognition app is suitable for anyone interested in cooking and looking to simplify the process of finding and preparing dishes.

• ChatGPT listed seven user categories. These are not full descriptions of personas, but basic data that can be worked with further.

• Writesonic provided pictures when asked to generate personas.

• Edya issued a description of the person. Its text is quite watery, but you can find useful details in it.

Test results are an important step in the evaluation and analysis process. They provide valuable data about the performance, functionality, and reliability of a system or product. Testing utilizes various methodologies, such as functional, load, and regression testing, to identify potential flaws and confirm compliance with requirements. The results obtained should be clearly documented and analyzed to ensure transparency and the possibility of further improvement. Analyzing test results helps identify the strengths and weaknesses of the system, as well as identify areas for optimization and improvement. It is important to correctly interpret the results so they can be used to make informed decisions. Ultimately, high-quality testing results contribute to increased confidence in the product and user satisfaction.

Deep analytics and creating accurate user profiles for neural networks can be complex tasks. However, neural networks can be effectively used to collect primary data. It is important that the designer carefully check each generated sentence for relevance and appropriateness. This will ensure high quality and relevance of the resulting content, which is a key aspect when working with neural networks.

Customer Journey Map in ChatGPT and SetGPT

Creating a customer journey map (CJM) in a table format for an app designed to recognize dishes from photos is an important step in user experience development. A CJM helps understand how users interact with the app, identify key moments, and improve functionality.

Initially, the user installs the app and registers. Next, they upload a photo of the dish, and the app analyzes the image, providing information about the name, ingredients, and calorie content. Displaying recognition results is crucial; it should be intuitive and visually appealing. Users can save their favorite dishes to their favorites or share them on social media. It's important to provide the ability to leave reviews of recognized dishes, which will help improve the app's algorithms. It's also worth adding a recommendation feature based on user preferences to increase engagement. Finally, the CJM should include feedback and support stages where customers can seek help or suggestions for improving the app. This will build trust with users and increase loyalty to the product. Using a CJM in a table format will clearly structure the information and make it accessible for analysis and modification.

• ChatGPT created a table listing and describing the sequence of actions: familiarization with the app, searching for dishes, browsing recipes, preparing a dish, rating and feedback.

During the development process, additional and overly specific steps were included, such as registration to increase confidence in data security, preparing a dish, and rating the app. These elements can distract from the core concept and flow, which can negatively impact the user experience. Optimizing these steps will improve overall efficiency and focus on the main tasks of the project.

• SetGPT made the table better than ChatGPT - it listed only the main actions: open the app, view the screen, press a button, select a photo, analyze a photo, save a recipe, share a recipe.

The created clear flow will become the basis for the functionality of the app.

Test results are an important aspect of assessing the quality and effectiveness of a product or service. They provide objective data that helps understand how well a product performs its functions and meets user requirements. Analyzing test results helps identify strengths and weaknesses, as well as areas for improvement. Understanding these results helps teams develop higher-quality and more competitive solutions, which in turn contributes to increased customer satisfaction and business growth. It is important to conduct tests regularly and carefully analyze their results to achieve optimal results.

Using artificial intelligence to create a customer journey map (CJM) is an effective solution. Based on the collected data, a designer can shape the structure and develop a prototype of the application, which contributes to an improved user experience and increased customer satisfaction. This approach allows us to optimize the development process, making it faster and more focused.

In our experiment, the SetGPT neural network demonstrated higher efficiency in completing the task compared to ChatGPT.

Read also:

User flow, or user flow, is a sequence of steps that a user goes through when interacting with an application or website. Creating an effective user flow is crucial because it allows you to understand how users interact with a product, what actions they take, and what obstacles they may encounter along the way. Without a well-designed user flow, developing apps and websites becomes more complex and less effective.

A user flow helps identify key points where users may get stuck or abandon actions such as registration, purchase, or form filling. A well-designed flow provides an intuitive interface that guides users toward their goals while minimizing potential bottlenecks.

Furthermore, analyzing user flows helps optimize conversions and improve the overall user experience. Understanding how users navigate the interface allows developers and designers to make changes that will improve the usability and functionality of the product.

In conclusion, a user flow is an integral part of app and website development. It allows you to create logical and pleasant navigation, which in turn contributes to increased user satisfaction and conversions. Without considering the user flow, a project can face many problems, which will negatively impact its success.

Develop the application structure, define the main screens and their interactions

Request for AI: "Define the structure of the application for recognizing dishes from photos."

A recipe recognition application must include several key components. First, an image upload module is needed, which will allow the user to upload photos of dishes. Then, an image processing system should be integrated, which will analyze the uploaded photos to identify the ingredients and characteristics of the dish.

Next, an important element is a recipe database, which will store recipes with corresponding images. This will allow the application to match recognized ingredients with actual recipes. It's also worth considering a recommendation feature that will suggest similar dishes to the user based on their preferences.

Machine learning algorithms should be implemented to improve recognition accuracy over time as they learn from more data. For user convenience, it's important to implement an interface with clear navigation and search functions so users can easily find the recipes they're looking for.

To optimize app performance, consider integrating with third-party services, such as online grocery stores for ordering ingredients. Finally, the app should be accessible across multiple platforms, including mobile and web, to ensure broad functionality.

• ChatGPT used the same data that CJM proposed and generated detailed descriptions of key features across a series of screens.
• SetGPT generated a clearer and more concise description of the structure.

Test results are an important aspect of analyzing a product's effectiveness and quality. Testing identified key metrics that help evaluate performance, reliability, and compliance. The focus was on identifying errors and shortcomings, which allows for product improvements before launching. Systematizing and documenting test results will help in future change tracking and quality improvement. This data can also form the basis for management decisions and optimization of development processes.

Every element and every sentence created using artificial intelligence must be carefully reviewed. This will help avoid errors and improve the quality of the content. Double-checking AI-generated materials ensures the accuracy and relevance of information, which is especially important in a rapidly changing digital world. It is necessary to pay attention not only to the actual content but also to the style of presentation to ensure that the text meets the expectations of the target audience.

Generated content using SetGPT can be used as the basis for creating the first prototype. Then it's worth supplementing this content with useful elements obtained from ChatGPT. This approach will allow us to create a higher-quality and more functional prototype that will meet the requirements of users and search engines.

Development of the visual style of the application in Midjourney and Stable

Creating visualizations in Stable Diffusion is possible in two main ways. The first involves using text prompts, where the user enters a description of the desired image, and the system generates a visualization based on that text. The second method is based on uploading existing images, which can be modified or enhanced using Stable Diffusion algorithms. These methods allow you to get unique and high-quality visual results, which makes Stable Diffusion a popular tool in the field of image generation.

• With references, that is, by the image2image command.
• Without references, that is, only by text prompt.

Rework the text, preserving its essence and subject matter, while optimizing it for Search engines. Avoid adding unnecessary information, symbols, and emoji. Don't use structured sections like numbers or bullets. Pay attention to keywords and phrases to improve the visibility of your text in search engines and make it more appealing to readers.

Read also:

Stable Diffusion: What is this neural network and how to use it effectively

Stable Diffusion is a powerful neural network designed to generate images based on text descriptions. This technology uses deep learning algorithms to create visual content, making it useful for artists, designers, and developers.

Stable Diffusion can be used in a variety of areas, from creating illustrations to generating unique images for marketing and advertising. To get started with this neural network, you need to install the necessary software tools and libraries, such as Python and TensorFlow.

After installation, you can download pre-trained models and use them to generate images. It's important to formulate text queries correctly to achieve the best results. Experimenting with generation parameters can also help create more accurate and satisfying images.

Stable Diffusion opens up new possibilities for creative professionals, allowing them to quickly implement ideas and generate original content.

The neural network generated additional design elements based on the uploaded app prototype. The result demonstrates how artificial intelligence can be used to improve the user interface and interaction with an app. This technology opens up new horizons in development, allowing you to quickly generate ideas and visualize concepts, which significantly speeds up the process of creating a high-quality product.

The Stable Diffusion algorithm offered a unique visual style based on a given prompt. This image generation approach enables the creation of original, high-quality visual solutions that align with a given theme. Stable Diffusion uses sophisticated machine learning models to process text descriptions and transform them into vibrant, detailed images. This allows users to create creative visualizations that accurately reflect their ideas and concepts. This method of content generation opens new horizons for artists, designers, and creatives striving for innovation in the visual arts.

The Midjourney bot, in response to the request "Application for recognizing food from a photo," provided images of higher quality and detail. However, it is worth noting that this is not a user interface (UI), but artistic illustrations.

For the query "Food app, recipe mobile app design, web design", the Midjourney bot presented high-quality results. This demonstrates the potential of artificial intelligence in creating visual concepts for mobile apps and web design related to cooking. Visualizing interfaces for apps that help users find, save, and share recipes is an important aspect of successful design. Effective design of cooking apps not only attracts users but also improves their experience of interacting with the content.

An alternative generation option from Midjourney offers a color palette, various compositional solutions, and an approximate appearance of user interface elements. This functionality allows users to create unique visual solutions that take into account their preferences and requirements. Using these tools, designers can significantly improve the quality of their projects and optimize the content creation process.

Learn more:

Working Properly in Midjourney: Effective Commands, Prompts, and Tips from Professional Designers

Midjourney is a powerful tool for creating visual content, and to achieve the best results, it is important to know how to use it correctly. Effective commands and well-thought-out prompts play a key role in this process. Experienced designers recommend using specific and clear commands to maximize the algorithm's potential.

When creating prompts, try to be as precise as possible in describing the desired image. Clarify the style, color palette, and atmosphere. This will help Midjourney better understand your intentions and create a high-quality visual.

Don't forget to experiment. Try different combinations of words, add unique details, and change the wording to see how it affects the result. It's also helpful to study the work of other users for inspiration and new ideas.

By following these recommendations, you can significantly improve the quality of your visual projects in Midjourney and unlock the full potential of this tool.

To improve the quality and accuracy of generation in neural networks, use multiple iterations. This improves results, as each cycle facilitates deeper data analysis and adjustments to the model parameters. It's important to keep in mind that multiple passes through the data help identify hidden patterns and optimize the learning process. Using multiple cycles can also include algorithm adaptation, which contributes to more accurate predictions and the creation of higher-quality content. Thus, multiple iterations are a key element in the generation process using neural network technologies.

• Get a response image from Stable Diffusion or Midjourney using a text prompt.
• Load this result from Stable Diffusion into Midjourney — or vice versa — and use the img2img command.
• If the generation is not satisfactory, try again or even make several iterations.

You will get several different design options that can be used as a basis for your project.

• Choose the two best from all the generations.
• Render two design concepts of the application using them as references.
• Present to the client.

As a result

Neural networks cannot perform tasks for you. They can suggest solutions and generate certain results, but these results are not final. It is important to understand that achieving a high-quality result requires your active participation and expertise.

Work will still be necessary. The use of generative technologies does not eliminate the need for active participation and effort in the process.

Experimental work on developing an application design using artificial intelligence yielded valuable results. The study found that integrating AI into the design process significantly improves user experience, making the interface more intuitive and adaptive to user needs. Furthermore, the use of machine learning algorithms allows for more accurate predictions of user behavior and optimization of app functionality. These findings highlight the importance of using modern technologies in design, which contributes to the creation of more effective and engaging solutions for end users.

• Neural networks save time. Analyzing and critically evaluating something that has already been created is much easier and faster than searching for information and creating everything from scratch.

Creating visualizations using AI reduced the time to 30 minutes, while traditional methods required 2-4 hours. Developing a draft design concept takes only 5-10 minutes thanks to modern technologies. This significant reduction in time allows designers to focus on more creative aspects of their work, increasing the overall efficiency of the development process.

• All AI responses must be verified, as they are not real data, but a game of values.

The use of neural networks significantly accelerates the work process compared to independently collecting factual information. This allows for optimization of time and increased efficiency, which is especially important in the context of modern demands on data processing speed. Neural networks are capable of automatically analyzing and processing large volumes of information, making them indispensable tools in various fields, including marketing, data analysis, and scientific research.

• Neural networks should not be used beyond conceptual work. This is not only due to legal complexities: they do not generate pure design, but only an aid to the process—informational or visual.

Learn more about design by subscribing to our Telegram channel. We share relevant news, useful tips, and inspiring ideas. Join our community and stay up to date with the latest design trends.

• "The Mental Hospital is in the Hands of the Patients." How to design interfaces correctly
• "Interface": the basics of designing humane systems
• 5 basic rules of good design