A selection of older reports that showcase my pinpoint forecasting instincts, creative judgment and storytelling abilities. Responsible for all concept, art and writing.

2012 - 2014: Some of my more prescient trend call-outs. These slides pretty much sum up the state of marketing today.

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SPRING 2015: A scientific analysis of color on the runway based on an algorithm and application I developed.

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2012 - 2014: Some of my favorite reviews from Stylesight's award-winning Runway Daily Chronicles.

2012 - 2014: Comprehensive design capsules centering around loungewear and intimate apparel that still have resonance today.

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2014: Tech feature that explores the possibilities of artificial intelligence in the fashion industry.

IBM's Watson Could Revolutionize the Fashion Industry

While designers like Alexander Wang and Donna Karan were presenting their vision for the Spring/Summer 2015 season at one of the biggest stages in the world, New York Fashion Week, something that could have more profound, lasting ripples in the industry was happening south of the equator at Melbourne Fashion Week.

There, in front of a crowd of more developers than designers, IBM was pitching its new technology Watson to the fashion industry. The event failed to gain much press outside of a few advertising and tech publications. But then again, Watson is still in its discovery phase, with beta tools currently available to developers for free

 

What is Watson? Think of the movie "Her.“ Oh yes, the radiant mid-century color palettes and the adorably offbeat wardrobe that looks to have stepped off the Prada runway. It is the cognitive operating system introduced in the movie, however, that is actually a current reality and that may have far greater resonance in the style-related industries.

Watson operates in a similar, albeit more limited, scope. Instead of building its memory from the whole of the Internet, in addition to private user data, Watson works purely off of what is fed into its ecosystem. This means its “intelligence” can be customized to each client and the amount of memory and numbers-crunching required is relatively limited.

Meaning: no garbage in, no garbage out.

Instead of the general search query of, say, a Google, Watson works on a question-and-answer basis. For example, “What color should I be wearing this fall?” as opposed to “fall color trends.” The latter will likely offer up endless articles on the subject of dubious origin and contradictory information, whereas the former may scan in-store inventories, sales figures, color services like Pantone and fashion magazines to arrive at a few educated guesses for “the new black.” Watson will even disclose its confidence level in the answer.

 

Long before “Her” and countless other robot-versus-man flicks, IBM foreshadowed something eerily similar to Watson in a harmless little rom-com called “Desk Set” in 1957. In something of a public relations move, Big Blue collaborated with the filmmakers to create the technology at the heart of the picture, EMERAC, a mainframe computer threatening to supplant the research department at a broadcasting company. The team, led by an aptly named Bunny Watson, feeds the machine printed material from its extensive library, and EMERAC in turn spits out specific answers to specific questions. Mankind can rest easy: Of course, the technology cannot exist without some heavy handholding.

 

It remains to be seen if the same can be said of Watson.

 

In the tradition of Deep Blue versus Kasparov, Watson had its big coming out in 2011 when it won at "Jeopardy!" against walking encyclopedias Ken Jennings and Brad Rutter. The technology has since taken off in the healthcare industry, serving as a sort of advanced WebMD to medical professionals. There, the human element remains the ultimate decision maker; Watson just saves the time spent on researching diagnoses and treatments while someone’s life may hang in the balance.

In an effort to sell Watson to the masses, IBM released a “cognitive cooking” app earlier this year that promises to deliver a unique edible recipe from any list of ingredients, flavor profiles and dietary restrictions. NPR ran an amusing story on the results, which left the reporter wondering when Watson would “be able to do the dishes.”

So far, Watson’s biggest gains in fashion have been on the e-commerce end. Retail strategy company, Fluid Inc., realized the potential of Watson two years ago and is currently funneling the technology into a personal shopping application for The North Face. Watson makes sense for an activewear sector that is highly dependent on function and environment. An example query that the company provides is, “I am taking my family camping in upstate NY in October and I need a tent. What should I consider?” The Expert Personal Shopper is set to be released this year—a good guess is in time for Cyber Monday.

IBM has been aggressively investing in Watson and just opened its headquarters last month in New York—the ultimate intersection of commerce and technology. With a research and development facility centered just a few dozen blocks away from the Garment District, all the chess pieces seem to be in place for Watson to make its move in the fashion industry.

However, a Google search of “Watson + fashion” yields very few results—the connection hasn't been made yet. IBM may be selling Watson short as merely a retail tool, although the consumer insight gathered there will undoubtedly come in handy across the entire fashion vertical. Nevertheless, the supply side presents myriad possibilities for Watson.

 

For one, the system’s customizable natural language processing facility is ripe for an industry that comes with its own specialized lexicon. The clothing vocabulary of the masses, on the other hand, is less than predictable. An early version of Watson was infamously fed the entire Urban Dictionary, and what resulted was a foul-mouthed computer that defeated the more academic-minded pursuits of the technology. After similar problems with Wikipedia, the lesson learned here was: data regulation is key.

The ecosystem of the clothing business, on the other hand, is relatively controlled. It is an industry deeply rooted in tradition, from the modes of construction to the crude product data management systems typically employed. Building off of its current applications in other industries, it seems like Watson could serve as a user-friendly, macro-level supplement to fashion’s outdated PDM platforms. While it is worth exploring the unanswered questions and obstacles that the nascent technology may present, the intent of Watson is clear and shows promise.

 

So what if a fully developed Watson were in operation at a clothing company? Say this company made little black dresses. Little Black Dress Co.‘s version of Watson is populated with information from PDM software, the intranet, trend services, fashion magazines and social media outlets. What types of questions within the organization could Watson provide the easy answers to? The below infographic investigates the path of Watson along the product lifecycle.

Extrapolating from these examples, imagine the amount of time and guesswork that could be saved if Watson were implemented at every step. Its effectiveness would require close collaboration between developers and those who actually have their hands on the product.

 

But there’s a catch—contrary to its reputation for being on the cutting edge, the fashion business is remarkably slow to adopt new technology. Judging by the amount of publicity surrounding wearables such as Google Glass and the Apple Watch at the latest runway shows, however, it looks like the style industry may finally be getting over its technology phobia. Which begs the question: Dear Watson, is fashion ready for artificial intelligence?

2012 - 2014: Two ambitious websites I created to document my obsessions—style references in hip-hop lyrics and odd coincidences on the runway. Crazy, yes, but also projects I am very proud of. HAPPENSTIJL was the prototype for an analytics-based trend forecasting website that I never fully got off the ground. I still find the images and articles on the site inspiring. THE ART OF EASING came right before (Rap) Genius blew up and 90s hip hop and streetwear influences started taking over fashion. I take credit, naturally!

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Nivara

Xaykao

New York-based
trend forecaster and concept designer, fashion & home