“If AI generates a large number of fashion design drawings just like the hot topic chatGPT does, what will SdibiT, ltd do to use these drawings?” A customer who visited us today asked a question.
This question reminds me of what Michio Tomii, CTO of our company, has been saying for nearly ten years, “In the fashion industry, designers who only know how to draw a graphic design will no longer be needed.”
However, his inference ten years ago cannot be proved obviously and get understanding and recognition of people in the industry because the tool which can turn the intangible data into tangible and visual information has not emerged.
Since last year, tools like “AI Art Generator” (txt to Image: DALL-E, Midjourney, Stable Diffusion… etc.) are starting to emerge, making it easy for anyone to generate stylish design images. And this kind of technology will evolve in the future.
Currently, AI can generate Virtual Show-On, but cannot output 2D patterns that can be reconstructed to the 3D-image.
To achieve DigitalTwin-Matching, highly accurate pattern data in accordance with Fit&Size is necessary.
There is no denying that AI generates design&pattern at the same time may be possible in the near future.
The point to notice is that “Generative AI” learns from image data that already exists.
Our company SdibiT’s approach is illustrated as the chart.
Starting from module design, we call this Mix&Match→Combination→Compilation.
By editing small pieces of patterns generated by multiple designs as parts, large amounts of pattern data can be generated.
In fact, as a complete form Phygital after integration, only a very small number of it is made public, most of it is kept internally.
That is to say, we have a considerable amount of data assets in our company, which are raw data that cannot be utilized by other companies through Generative AI.
Among the massive design images generated by AI, there may be actual clothing that is not acceptable to consumers or the actual situation cannot be completed exactly the same as the picture, the next candidate design will be generated by the “average consumer”. Based on this, multiple different candidate looks are generated while creating a design data that achieves DigitalTwin-Matching.
The “average consumer” can choose among these candidates.
This process leads to true humanity and individualization.
“In the near future, everyone will not only become a fashion designer, but also be able to confirm the effect in 3D. Fashion designers who only know how to do 2D painting will almost disappear sooner or later.” Mr. Tomii always said.