But the hi-tech and seemingly futuristic system can also be used to enhance your online shopping experience, which is what luxury e-marketplace Orchard Mile is doing with My Mile, an e-boutique that's constantly being updated and personalized for each individual shopper. Behind the scenes, predictive and intuitive algorithms -- not scary robots -- use your shopping habits and preferences to essentially make your browsing and buying experience more focused (and less overwhelming), easier and hopefully, more fun. Once a customer joins My Mile, they're automatically signed up for a newsletter that is personalized based on set preferences (and ongoing shopping habits) and the email magically updates its product offerings and sale updates based on the moment you open the email. The process is constantly evolving and improving, based on customer's shopping patterns and habits and consumer feedback.
James Slifierz is making the rounds of New York City investors as he prepares to move his startup -- Skywatch -- into the Communitech Data Hub in Waterloo. The federal government's Open Data Exchange will move from the Tannery building in downtown Kitchener into the Data Hub as well. IBM I3, IBM's innovation incubator project, also will be there. Since then, dozens of startups incubated in the Tannery building have moved into offices in and around downtown Kitchener, employing more than 1,000 people.
Haslet, a former dance instructor who became an advocate for amputees after her injury, wrote on her Instagram page that it was an "honor to open and close the show for Canadian designer Lesley Hampton at Vancouver Fashion Week." To help empower other amputees, Hampton partnered with the Be Body Aware project to help promote more inclusivity on the catwalk, according to a news release. In addition to casting Haslet, Hampton sought models with all different shapes and sizes for her show. "Together with the Be Body Aware project, I am hoping to set as an example for anyone affected by adversity and stand up once again to the fashion standards."
Nonetheless, WWD asked IBM to discern key colors, trends and even comparisons among New York Fashion Week fall collections that resulted in a comprehensive report on its analysis. Additionally, IBM's Research Cognitive Fashion asset -- an app developed for the purpose of this report -- determined the main colors in each runway image. "Dominant colors for a collection of images were obtained using color trends asset from IBM Research's Cognitive Fashion [app]," the report said. IBM Watson deployed a visual recognition tool that analyzed recurring colors and silhouettes among other features.
Big data, big opportunity Big data is exactly what it sounds like: information on a large scale. To obtain that data, machine learning -- and recent advancements in artificial intelligence (AI) -- can provide retailers with powerful tools to maximize the use of data to make such an impact. Models such as neural networks use supervised learning techniques to teach themselves to derive patterns and traits in complicated data by mimicking how our brains process information. These technologies can teach themselves to derive patterns and traits in complicated data by mimicking how our brains process information.
This saw 13 design teams from across North and Latin America leveraging Epson's dye-sublimation and direct-to-fabric printing technology to create small collections that were presented during an evening event held ahead of New York Fashion Week. In fact, the market for worldwide digital textile printing is expected to grow annually at almost 25% until 2019, according to WTiN Intelligence. Other benefits include the fact digital printing ensures higher quality, more unique designs at scale, greater variety of rich colors and more. "Epson has a very considerable and growing robotics business and we would like to leverage that business in this industry in the future to help designers create very industrialized designs," Usui adds.
This is exactly what Qzone, one of China's largest online social network platforms owned by Tencent, YouTu Lab, an AI research lab under Tencent focusing on machine learning, and Vipshop Holdings Limited, China's leading online discount retailer for brands, have joined hands to accomplish. The three platforms have produced a new AI powered report that reveals the fashion preferences of China's "post-95" generation in terms of most popular colors, fabrics and patterns and inspired a new collection by famous Chinese designer Chi Zhang, named Designer of the year by Esquire China, to be launched at New York Fashion Week 2017. By applying facial recognition technology to big data aggregated on Tencent's Qzone platform, YouTu Lab's algorithm identified the ages of "post-95" users accurately within three years. YouTu Lab leverages Tencent's leading social platforms to develop advanced technologies and applications in areas including computer vision, pattern recognition, machine learning, data mining, deep learning and audio analysis.
Stitch Fix, a fashion startup that aims to provide a personal shopping experience remotely, already uses machine learning to understand its customers' tastes. Last week, Stitch Fix data scientist TJ Torres poked into the potential future of computer-generated clothing designs. For fashion, Torres took neural networks, and fed them pictures of clothing. Finding predictive signal in extracted stylistic concepts from images of clothing would represent a big leap forward in the modeling possibilities for our recommendation systems.
Using data analysis software and machine learning to match users with personalized clothing choices, Stitch Fix is ushering the fashion industry into the age of Big Data. "All they're seeing is they order a box of clothes, and presto -- it appears," said Eric Colson, Stitch Fix's chief algorithms officer. Stitch Fix, which in September expanded into men's fashion as part of its ongoing effort to revolutionize the clothing industry, uses that same technology to deliver curated boxes of clothing to customers' doors. While the convenience of on-demand delivery makes services like Stitch Fix increasingly popular, it comes at a cost to traditional brick-and-mortar retail stores.
But can Machine Learning help the creative side of fashion? Fashion magazines spend a significant amount of effort to provide pictures from the latest fashion shows with predictions for the next season's fashionable colours and styles. For example, below is the histogram for the 50 most prominent colours based on Giambattista's picture above. The R code is only a few lines long and processing time for each picture on my laptop is about 3 seconds, 5 show, 15 outfits and 45 seconds.