Advances in AI are changing what’s possible with human-machine collaboration and bringing digital understanding into the physical world. Pinterest brings together human curation and machine learning to deliver more than 10 billion recommendations every day. With more than 100 billion pins saved, labeled, and organized by pinners, Pinterest’s users are effectively creating one of the world’s most comprehensive image training datasets. Through cutting-edge machine learning, Pinterest uses this data to help people explore their taste and style and surface ideas they love even before they know what they’re looking for.
Li Fan shares insights into how Pinterest improves products based on usage and explains how the company is using AI to predict what’s in an image, what a user wants, and what they’ll want next, answering subjective questions better than machines or humans alone could achieve.
Li Fan is the senior vice president of engineering at Pinterest, where she leads the company’s technical direction and oversees a team of 400+ engineers building a visual discovery engine. Previously, Li was the senior director of engineering at Google, where she led image search; vice president of engineering at Baidu, where she was responsible for product design and development at China’s largest search engine; and a software developer and engineering manager at Cisco and Ingrian Networks. She holds a master’s degree in computer science from the University of Wisconsin-Madison and a BS in computer science from Fudan University in Shanghai.
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