How Amazon’s Tackling Fashion Retail With Machine-Learning

In a rare fireside chat at SXSW on Sunday, Amazon Fashion chief technology officer Tony Bacos mapped out how the company’s using machine-learning in its bid to crack online retail’s biggest challenges. According to Bacos, the spate of initiatives spans virtual fitting, personalized recommendations and computer vision: “The opportunity to create better experiences online, both from a discovery-and-browse capability, the fit challenge and being able to, I like to say, search with your eyes, not your keyboard, all of those are challenges that may have been solved in little bits and pieces,” he said. “But we’re trying to tackle all of them.” It’s a far cry from how critics typically think of Amazon: When it comes to fashion, the marketplace is known as a place to pick up basics. And it works best when customers know what they’re looking for. Think search, not discovery. Amazon has an advantage, though: It’s a tech giant and a major developer of artificial intelligence with deep pockets. In the holiday quarter, the company posted $3 billion in net income, a jump of 66 percent over the previous year. Because of its massive consumer electronics, cloud and e-commerce operations, it can afford to splurge on efforts to boost

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