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Design your own wardrobe with AI
I want to buy these denim t-shirts. Not much of a fashionista but I haven’t seen these designs before. Can someone make it?
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These patterns reflect the latest consumer interest and are automatically designed by AI. Autonomous is a better word… a self-driven machine!!
How?
The machine has 3 primary components as seen below. It has no manual input. There is a deluge of data on the internet. People search, transact and leave huge data trials.
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Unearth Trends: the first step is to mine these internet data trails. The machine programmatically understands what consumers are searching for, design patterns, colors, fabric, graphic styles, etc. One can in addition mine trends in music, movies & entertainment on a given day and overlay those trends to enlarge the style set.
There are tools available like decode’m (www.decodem.ai), MeetGlimpse (meetglimpse.com), Treendly (treendly.com), etc that do this today. They autonomously track trends, synthesize insights using Natural Language Processing (NLP), generate reports and some even expose APIs to leverage in use cases such as the one we are discussing. Below are the current trends for denim t-shirts
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Prompt Engineering: The second step is to use these trend keywords to generate prompts that describe what we want to see. There are many large AI language models that have been trained on 100s of billions of words like GPT3, GPT-J, etc. They possess a lot of knowledge and connections that can be fine-tuned for a particular task. This is accomplished via a technique called prompt engineering. You basically show the AI a few examples of what you will give and what you expect out of it. In this case, we tell it that we will give you a few words and you have to give us a descriptive sentence that can be used to generate an image. That’s exactly what was done. We provided the prompt to the left (figure below) and the AI is intelligent enough to understand the task. When you feed more words it gives you prompts like the ones to the right. “A denim oversized t-shirt with high collar and graphic on the chest” is an example output generated by the AI model. The technique is called “few-shot learning” as you learn from a few examples (3 in this case).
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Image Generation: We have the prompts and are now ready for the magic. A prompt like “product photography of a t-shirt, denim, with half sleeve, highly indicate, professional photography” provided to a different AI model would generate the images you saw at the beginning of the article. Some amazing AI models have been released recently like Dall-e, Stable Diffusion (by Stability.ai), MidJourney, etc that can take an image prompt and generate stunning images. These are essentially text-to-image converters. We use stable diffusion here.
We have many combinations of trends (color, fabric, other entertainment categories, etc) and hence can generate a huge number of prompts in one go. For example, when the prompt generator picks a different color (in this case red which is also trending) you get the below designs
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The prompt generator uses the music, movie & entertainment trends and spots a movie Katputhli trending in India and generates the below designs
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It is a machine. No egos no laziness. Prompt again and get more
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It produces designs for women. You can see some different types of denim dresses generated too.
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And even logo concepts. Remember we are going through a massive loop of prompts with trending consumer concepts.
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Are you wondering if this was by chance? And whether it will work for other apparel? Here is a USA-focused machine that captures trends from that geography and applies them to Jackets. Note that all trends have changed from before. For example, you can see Rings of Power & House of Dragons trending. Different fabrics and colors are trending.
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Perform the same steps of prompt engineering and image generation and this is what we get.
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“Design to inspire” from different fabrics, styles, gender, and even futuristic-looking designs.
At one shot 100s -1000s of designs are generated. The machine in our case runs autonomously every day and the designs are unique. The frequency can be what you choose including on-demand. This can fundamentally change the ideation & design process in fashion brands & marketplaces. There will be no dearth of ideas and the designs are driven by the latest trends that consumers want.
As one generates designs the learning loop for prompt engineering can be closed. For example we realize that the order of words matters. “t-shirt, denim” is better than “denim, t-shirt”. Using NLP techniques prompts can be engineered to better represent these learnings.
We can change the category further and extend the concept to shoes for example. Enjoy the variety of designs below.
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And more designs by further prompt engineering. The words that we choose and how it has to be presented can be changed. For example, do you want the output like a product photo, a catalog, a painting or a poster will change the output styles.
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Imagine this. You have to go to an event. You run this machine, get multiple designs basis the latest trends, 3d-print the design and wear it. The day is getting here. How will designers, product manufacturers, and e-commerce players adopt to that?
And if you thought apparel industry is ripe for disruption… enjoy these designs
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Multiple sectors that leverage visual design like automotive, consumer durables, D2C & B2C merchandise, interior design, etc should be thinking machines rather than human-driven designs.