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How AI helped Walmart go from 700,000 to 60 million items online

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Walmart.com is bigger than you might think. The site has 60 million items for sale, Walmart CTO Jeremy King said at the VB Summit in Berkeley, California today.

That’s up from 700,000 items when he joined Walmart in 2011, and it doesn’t include Jet.com, the e-commerce site Walmart acquired last year. Online sales have also made notable gains: The company reported a 67 percent year over year increase in quarterly online sales for the three months ending in June of this year. (That revenue growth was helped by Walmart’s Jet acquisition, though the company said that the majority of its gains were organic.)

The secret to the expansion in inventory, said King, is artificial intelligence. The Arkansas-founded company uses machine learning algorithms for tasks like organizing inventory data, pricing items and fixing problems.

“How do you determine that an automated fee coming from a vendor, whether the price is right or not?” King said, by way of example.

Sales for a typically popular item could drop off a cliff, and an algorithm can spot the anomaly quickly and identify what caused it, King added. Maybe the cause was a change in price caused by a clerical error.

He said Walmart’s massive size — 10,000 stores, 2.6 million store associates — means it has a massive amount of high-quality data, an advantage if you’re trying to leverage machine learning technology.

“This is really where scale helps machine learning work,” he said.

Walmart’s e-commerce business notoriously trails the company’s biggest competitor, Amazon, but the company has been making aggressive plays to catch up. The retailer has reportedly started asking its vendors to curtail their use of Amazon Web Services, for example. On the AI side, a recent report said that Walmart is buying up a large number of NVIDIA GPUs, which are useful for performing machine learning calculations.

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