With thousands of orders placed every hour and each order assigned to a pick list, Europe’s leading online fashion retailer Zalando is using GPU-accelerated deep learning to identify the shortest route possible to products in their 1.3 million-square-foot distribution center.
Calvin Seward, a Data Scientist focused on warehouse logistics, shares how his team is using the Caffe deep learning framework and Tesla K80 GPUs to train their deep neural network to greatly accelerate a processing bottleneck, which in turn enabled the company to more efficiently split work between workers.
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Related resources
- GTC session: Enabling Frictionless Checkout for Retailers and Beyond (Spring 2023)
- GTC session: Optimizing Distribution and Fulfillment Center Operations with Computer Vision and Digital Twins (Spring 2023)
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- Webinar: Transforming Warehouse Operation Management Using Computer Vision and Digital Twins
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