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Nvidia wants to be retailers’ right-hand man when it comes to implementing artificial intelligence.
John Furner, CEO of Walmart U.S., hosted a keynote session with Azita Martin, vice president and general manager, retail & CPG at Nvidia at the National Retail Federation (NRF) conference in New York City on Sunday.
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During the session, Martin explained that while the implications of last year’s buzziest technology—AI—are wide-reaching for retail, supply chains may see the highest degree of impact.
To upgrade retail systems with AI, Nvidia is combining its hardware—perhaps what most know it for—with acceleration software, then distributing the technology through its partners, Martin said. And in doing so, the technology company has helped brands and retailers achieve a variety of updates related to their individual goals.
L’Oreal, for instance, has used Nvidia technology to use generative AI for marketing tools. An employee might input a standard product image and use natural language to create a dynamic background with a prompt like, “Add pink-hued, reflective geometric shapes into the background of this image.” The resulting photo can then be used on the brand’s social media or marketing materials.
Walmart, on the other hand, has used AI to help amp both its customer-facing experiences and its back-end capabilities.
On the forward-facing end, the retailer has begun testing an AI-powered shopping assistant it calls Wallaby, which aims to help consumers with search and discovery using natural language terms on the Walmart site.
“[A] shopping assistant is basically taking your best and most knowledgeable sales associates and replicating that 24/7 at scale on your e-commerce site and on your mobile site,” Martin said.
Simultaneously, Walmart uses Nvidia’s technology to bolster the operations that customers don’t always think of—particularly around inventory and allocation. The company has used Nvidia’s data science acceleration libraries to enrich its forecasting functions.
“It’s enabled [Walmart] to basically ingest [a] large amount of data and be able to forecast on a weekly basis hundreds of millions of combinations of SKUs and stores, and by forecasting and running those algorithms more frequently, your forecast accuracy [improves],” Martin said. “For a company of Walmart’s scale, we know that even a 1 percent improvement in forecast accuracy represents significant [opportunity].”