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Woman walking on a store scanning codes

Amazon’s first brick-and-mortar clothing store is getting ready to deliver automated outfit recommendations.

What’s new: The ecommerce giant announced plans to open a flagship Amazon Style location at a Los Angeles-area mall this year.

How it works: The 30,000 square-foot store will feature aisles and racks like a traditional clothing store, but customers will be able to scan QR codes using their phones to see variations in color and size as well as items recommended by machine learning models. A touchscreen in each fitting room will enable customers to request such items to try on.

Proposed innovations: Research papers provide glimpses of Amazon’s ideas for AI-driven fashion retailing. The company declined to comment on whether it plans to implement them. For instance:

  • CSA-Net finds items that fit an existing outfit using convolutional neural networks and attention. A customer can enter a shirt and shoes, and the model might choose a matching handbag.
  • VAL uses a transformer network to interpret an image-and-text pair and searches for matching products. A customer might, say, select a picture of a shirt and request a different color.
  • Outfit-Viton turns a full-body photo of a customer into a 3D model, then uses a generative adversarial network to generate images of the person wearing selected outfits.

Behind the news: Last summer, Amazon opened its first brick-and-mortar grocery store, where customers can take merchandise off a shelf and exit without interacting with a clerk for payment. Computer vision identifies them at the door and identifies the products to charge their account automatically.

Why it matters: The fashion retailing market is crowded, but Amazon’s considerable AI expertise puts it at the forefront of low-friction retailing.

We’re thinking: Fashion companies such as Stitch Fix and Wantable have used AI to recommend clothing and build valuable businesses. There are good reasons to believe that future fashion leaders will be sophisticated AI players.


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