Tech firm IBM recently collaborated with Tommy Hilfiger and the Fashion Institute of Technology on a project called “Reimagine Retail”, aiming at exploring how artificial intelligence can identify emerging trends from the fashion market faster than industry insiders, ultimately improving and fueling creative processes.
Through the use of tools like computer vision, natural language understanding and deep learning; the trio tried to uncover how artificial intelligence’s abilities could inject more agility into the Fashion Designer’s job (those tools can also be applied to the distribution field, due to the fact that the gathered insight offer the means to better anticipate demand levels of products, unlocking customization opportunities at a local and hyperlocal scale).
“The machine learning analysis gave us insights about the Tommy Hilfiger colors, silhouettes and prints that we couldn’t begin to consume or understand with the human mind. This enabled the FIT Fashion Design students to take their inspiration from Americana or popular fashion trends and marry that with the ‘DNA’, if you will, of the Tommy Hilfiger brand across those dimensions to create wholly new design concepts” Michael Ferraro, executive director of FIT’s Infor Design and Tech Lab
Students of the Fashion Institute of Technology were offered free access to IBM Research AI’s full capacity, specifically fed and trained with datas from the fashion industry. By combining the artificial intelligence’s abilities with more than 15,000 Tommy Hilfiger product images, 600,000 pictures from various runway shows and about 100,000 patterns from fabric sites ; the team managed to combine numerous shapes, colors, prints and patterns that could be used as an inspiration basis by future creatives, destined to help them create pieces respectful of the Tommy Hilfiger brand DNA and aesthetic.
“AI can assist design teams by enhancing and reducing overall lead times, and expand their creative discovery by analyzing and remembering insights from thousands of images and videos using computer vision. These designers can also more easily find how they can integrate trending colors, key patterns, and styles.” Steve Laughlin, general manager of IBM Global Consumer Industries
The masterpiece of this collection? A plaid tech jacket, conceived by by FIT senior Grace McCarty and embedded with an innovative color changing thread depending on the wearer’s vocal analysis and social media feed (powered by Watson’s Tone Analyzer tool, which analyses and reacts in near real-time to an individual’s sentiment). The creations also integrate environmentally friendly fibers, resulting in sustainable and highly customizable pieces. Finally, three of the six designs from FIT were showcased during NRF’s Big Show in New York from the 14th to the 16th of January.
“[Fashion companies’] slow-moving process hampers a brand’s ability to be in sync with today’s rapidly evolving consumers’ expectations, product trends, and external market forces… In the future of fashion with AI, designers could get insights from internal and external data sources so they can make their designs more informed and relevant. It also may give them the ability to design elements that will customize and personalize looks for certain markets or consumers.” Steve Laughlin, general manager of IBM Global Consumer Industries
Through this experiment, the trio’s long term goal is to become capable to educate a whole new generation of Fashion leaders with new skills, all while providing them with relevant and informed inspiration in their creative process, assisted by AI.
The dominant vision in the debate on AI’s arrival in the creative field, sometimes simplistic (and mainly dystopian), claims that this technology would inexorably replace human beings, while such experiments clearly demonstrate that operating in duet is more than possible, if not desirable. Indeed, AI integration’s benefits go way further than being solely time-saving, like for instance, by it’s ability to enhance and bring more relevancy to designers inspirations or to broaden creative visions. Ultimately, with the support from an AI powered by internal (fashion houses and brands extensive archives) and external data sources (consumer insights, product trends, economic indicators,…), fashion houses and brands might equip themselves with the ideal mean to bring more agility in their creative departments without the harming their teams ; counterbalancing the global industry’s cycle acceleration of the last few years and giving themselves a certain competitive advantage, considering that this innovative creative process is a powerful new mean to face up to fast fashion brands.