Young fashion shoppers today are demanding personalization more than ever. According to an IBM study, 52% of female Generation Z would like to see tools that allow them to customize products for themselves.
This coincides with an ever-increasing expectation for speed in delivery of product. While several fast fashion retailers can get product to shelves in weeks, the majority of clothing items take anywhere from six to 12 months of development.
Technology is impacting throughout the supply chain to shift this forward, including in the creative process itself. Artificial intelligence (AI) for instance – incorporating computer vision, natural language understanding and deep learning – is being used to produce key insights on trends to both expedite the initial design process and better predict demand for hyperlocalized products.
IBM has teamed up with Tommy Hilfiger and The Fashion Institute of Technology (FIT) Infor Design and Tech Lab on a project called Reimagine Retail to demonstrate this. The aim is to show how AI capabilities can give retailers an edge in terms of speed, and equip the next generation of retail leaders with new skills using AI in design, according to Steve Laughlin, general manager of IBM Global Consumer Industries.
To do so, FIT students were given access to IBM Research’s AI capabilities including computer vision, natural language understanding, and deep learning techniques specifically trained with fashion data.
Those tools were applied to 15,000 of Tommy Hilfiger’s product images, some 600,000 publicly available runway images and nearly 100,000 patterns from fabric sites. They then brought about key silhouettes, colors, and novel prints and patterns that could be used as informed inspiration to the students’ designs.
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