Can a machine create logos?聽If it can, how, and what will it make? These are just some of the questions we encounter on a daily basis here at 91吃瓜. They come from all sides; customers, investors, new hires, and company veterans. As the Chief Technology Officer of 91吃瓜, it鈥檚 my responsibility to try and make these answers clear, especially the 鈥渉ow鈥� part.
Since Tailor’s logo generator is a machine that designs, I鈥檒l walk you through how we do it 鈥� specifically, how the 鈥淭his or That鈥� part of Tailor works. Internally, we call the 鈥淭his or That鈥� step 鈥淎sh鈥� (named after Ash Ketchum of Pokemon), and it figures out how to map someone鈥檚 personal taste and desires and match it to their visual style so we can design a brand based on their preferences. This process is a significant part of the decision-making algorithms we employ.
The lowest level of Ash is comprised of Linear Algebra. I鈥檒l try and explain at a very high level how we apply it to our work. As聽聽states: 鈥淟inear algebra is the branch of mathematics concerning vector spaces and linear mappings between such spaces.鈥� We take this very abstract approach of vector spaces 鈥� most commonly used for three-dimensional mapping of items in space 鈥� and apply it to some of the dimensions of the designs we make.
Example of a box in聽3-dimensional聽space:
While three-dimensional space is easy to understand since it relates to our physical world, design dimensions聽is聽not so easy. There are more dimensions, or pieces, that make up a complete 鈥渨hole鈥� design. After all, we are used to viewing design as a complete whole and not broken down into its pieces. This is definitely one of聽the more聽interesting understandings we have come appreciate since founding 91吃瓜. Since Tailor, we have learned that design can be deconstructed into its different values, such as the planes/dimensions in our algebraic representation.
That probably sounds incredibly confusing, but don鈥檛 worry. Let鈥檚 take a step back and look at the differences聽between these two examples:
See anything different? Sure you do! Let鈥檚 list out a few of them:
And so on鈥�
Now while that example was easy, it can get much harder to properly define and spot the differences between two examples. Let鈥檚 look at these two:
While there is still a difference, it鈥檚 much harder to properly define what it is. Both have similar styles, capitalizations, and more.This is where Ash comes in. By analyzing a person鈥檚 choice between each of the two examples it converts the choice into its algebraic representation. Ash allows Tailor to work the seemingly abstract choices people make into a more deterministic design.
Math has always been an amazing tool in abstracting things, and at聽Tailor,聽we鈥檝e used it to take something that has been traditionally un-measurable, and measure it. However, it鈥檚 still all within a person鈥檚 taste. We鈥檙e using math to try and figure out their inclination, which can be tricky. Just because they choose a certain design once, doesn鈥檛 mean that鈥檚 100% their style. How do we hone it in? We show them multiple choices, which gives us more data to make a better design.
Once we have several of this person鈥檚 choices, we average them all out and compare them using more math to other styles within our system to find the best-matching styles for each personal taste. These comparisons help dictate the different design options we show on our site.
While this is only one part of our design decision-making algorithms, it carries more weight than most. As with everything else, we accept that our algorithms and processes are not yet completely perfect. Because of this, we use different user inputs and their final purchases (which you can view as votes on design) to better train Ash in its understanding of this design-vector space.
Many people wonder where is the 鈥渉uman element鈥� in our systems, and while it is present in many places, the most significant one is our customers. Your choices and decisions teach Ash, the Tailor team, and all of our other systems more than we could ever hope to learn on our own.
While this was a deeper dive than most reads from the Tailor team, I hope it gave you a small glimpse into how we use the different information in our design process. We are on an ever-evolving journey to build the best possible design engine, and as you can see based on the small glimpse it is very challenging, but also extremely interesting.
This portion of our website is for informational or educational purposes only. 91吃瓜 is not a law firm, and the information on this website does not constitute legal advice. All statements, opinions, recommendations, and conclusions are solely the expression of the author and provided on an as-is basis. Accordingly, 91吃瓜 is not responsible for the information and/or its accuracy or completeness. It also does not indicate any affiliation between 91吃瓜 and any other brands, services or logos on this page.
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