In previous posts we looked at the new role of algorithms in fashion design: in September 2016 we explored the rather botched results of a questionable project by Google and Zalando that generated digital renderings of fashion designs through an algorithm. Yet, as the months passed we got more news about algorithms in the fashion industry: last year it was announced that Amazon was working on developing an algorithm that can contribute in designing fashionable garments while Stitch Fix uses algorithms as stylists that help choosing new clothes and accessories for its customers.
Nike recently employed algorithms to design its latest running shoe: the soles of the various versions of the Nike Epic React Flyknit were indeed created in "collaboration" with an algorithm.
This is not the first time Nike works on such a project: the running shoes designed for Jamaican track and field sprinter Shelly-Ann Fraser-Pryce for the 2016 Rio Olympics (the Zoom Superfly Elites) featured mouled (and not screwed in) spikes that meant the footwear was lighter and helped the athlete improving her performance.
The shoes were followed last year by the NikeLab NIKE A.A.E. 1.0 T-shirt: to make it researchers looked at motion, airflow, sweat and heat maps, data that were then elaborated by an algorithm that provided a series of solutions.
This is actually the key to computational (generative and algorithmic) design: fashion designers can create perfectly good clothes or shoes, but, being human, they don't have the time to elaborate and analyse a vast quantity of data.
In the case of the Epic React Flyknit, the shoes - promising to be softer, lighter and more durable - feature a sole made with React foam (partially made of rubber) and characterised by grooves and dents designed with the help of algorithms that suggested such solutions and structural patterns after processing a series of data.
The difference between the algorithm that produced Google/Zalando's Haute Mess and Nike's recent experiment is that in this case, the data analysed were more complex and there was a longer research behind them (the shoes for Shelly-Ann Fraser-Pryce were the result of a research in algorithmic software design and 3-D printing prototyping that lasted for more than four years at the Nike Sports Research Lab).
Now, you may like the new shoes or not, but the most intriguing thing about them is not how they look but the implications behind them.
If computational design becomes more popular, fashion designers may find again more time to develop researches in other and more creative fields while algorithms can work on functional solutions; creative minds may develop collaborations with engineers and computational designers or may even retrain and learn how to use such new tecnologies (universities take note - maybe brand new courses should be developed along these lines...).Generative algorithms may indeed open up new job opportunities: Nike is currently looking for a product director of its computational design unit to further develop ideas in the area.
Besides, rather than improving only an athlete or an amateur's efficiency in sprinting and jumping, computational designs could be used to find innovative solutions for medical issues such as orthopedic disorders or to design accessories that implement the performance and the safety of people working in hard industries.
Last but not least, these technologies will open up new challenges in terms of materials, so we will need more material engineers: software can work on the weight, size and structure of a design, but materials will represent the new element of the algorithmic equation. In a nutshell, agorithms may not be able to function like designers, but designers should definitely be working with them.
Comments