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Brianna White

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Jul 30, 2019
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Getting the software right is important when developing machine learning models, such as recommendation or classification systems. But at eBay, optimizing the software to run on a particular piece of hardware using distillation and quantization techniques was absolutely essential to ensure scalability.
eBay’s head of machine learning and NLP Selcuk Kopru described how the company optimizes its machine learning models in support of its AI-driven marketplace in a presentation made earlier today at the AI Hardware Summit, a hybrid event that’s taking place virtually and at the Computer History Museum in Mountain View, California this week.
n order to build a truly global marketplace that is driven by state of the art and powerful and scalable AI services,” Kopru said, “you have to do a lot of optimizations after model training, and specifically for the target hardware.”
eBay certainly is no stranger to scale. With 1.5 billion active listings from more than 19 million active sellers trying to reach 159 million active buyers, the ecommerce giant has a global reach that is matched by only a handful of firms. Machine learning and other AI techniques, such as natural language processing (NLP), play big roles in scaling eBay’s operations to reach its massive audience.
For instance, automatically generated descriptions of product listings is crucial for displaying information on the small screens of smart phones, Kopru said.
Continue reading: https://www.datanami.com/2021/09/13/inside-ebays-optimization-techniques-for-scaling-ai/
 

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