Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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Artificial Intelligence IBM Tommy HIlfiger FIT Collaboration Machine Learning

Artificial Intelligence Empowers Designers In IBM, Tommy Hilfiger And FIT Collaboration

By Nand Kishor |Email | Jan 15, 2018 | 8739 Views

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.

"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 â??DNA', if you will, of the Tommy Hilfiger brand across those dimensions to create wholly new design concepts," explains Michael Ferraro, executive director of FIT's Infor Design and Tech Lab.


"So, a key impact [of the project was] new inspiration. Another important impact for the consumer is opportunities to customize and personalize the clothing, without losing the style of what they love about Tommy Hilfiger," he adds. The cognitive print generator tools and personality insights analysis provided some cool opportunities to give consumers that self-expression. In addition to exploring how AI might impact decision making in fashion design, we also explored how tools such as social media listening and voice recognition can create a more personalized shopping experience built around an interactive â??smart' supply chain strategy that optimizes waste and minimizes environmental impact."

The resulting 3D digital designs were presented to Tommy Hilfiger and IBM executives, who chose a plaid tech jacket by FIT senior Grace McCarty. When designing her look, McCarty said she drew inspiration from the AI produced insights on Tommy's brands' style and silhouettes, as well as popular and trending colors, and AI generated novel patterns.

The design also incorporated a special thread embedded in a removable, futuristic plaid panel with IBM's Watson's Tone Analyzer, which responds in near real-time to the sentiment in a customer's social media accounts.

"As a brand, we are always pushing the boundaries of what's possible through innovation and disruption. These young designers truly embody this spirit by showcasing the successful integration of fashion, technology and science," wrote Tommy Hilfiger's chief brand officer, Avery Baker, in a blogpost for IBM.

One of the big conversations around the use of AI in design, is whether it spells the death of creativity. If AI is used to shape exactly what new collections look like, is there even need for a designer in the first place? Both Ferraro and Laughlin believe this project demonstrates how it can be used as a means of augmenting human processes, rather than replacing them.

"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," Laughlin explains. It's about reducing a time-consuming, resource intensive, manual process - or blowing up that research element by providing access to much wider sources than ever before, he commented.

"It is the critical difference between systems that enhance and scale human expertise, rather than those that attempt to replicate all of human intelligence. The AI inspired us and breathed new life into the design process," Ferraro adds.

IBM previously worked with Australian designer Jason Grech on the Cognitive Couture collection for Melbourne Fashion Week. This similarly analyzed thousands of runway fashion images as well as social media content to help inform the design process in a data-driven manner.

Laughlin emphasizes that making trend prediction more accessible and getting products to market faster means fewer lost sales. "For consumers, when a desired item is not immediately available in store on online, the sale will not occur," he explains.

"[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."

Samples of three of the six designs from FIT will be showcased at NRF's Big Show in New York this week.

Source: Forbes
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