Today we’re joined by Luna Dong, Sr. Principal Scientist at Amazon. In our conversation with Luna, we explore Amazon’s expansive product knowledge graph, and the various roles that machine learning plays throughout it. We also talk through the differences and synergies between the media and retail product knowledge graph use cases and how ML comes into play in search and recommendation use cases. Finally, we explore the similarities to relational databases and efforts to standardize the product knowledge graphs across the company and broadly in the research community. The complete show notes for this episode can be found at https://twimlai.com/go/457. Subscribe: Apple Podcasts: https://tinyurl.com/twimlapplepodcast Spotify: https://tinyurl.com/twimlspotify Google Podcasts: https://podcasts.google.com/?feed=aHR0cHM6Ly90d2ltbGFpLmxpYnN5bi5jb20vcnNz RSS: https://twimlai.libsyn.com/rss Full episodes playlist: https://www.youtube.com/playlist?list=PLILZm3MRkvH83C46bZ4rPmB-jKWBltWkP Subscribe to our Youtube Channel: https://www.youtube.com/channel/UC7kjWIK1H8tfmFlzZO-wHMw?sub_confirmation=1 Podcast website: https://twimlai.com Sign up for our newsletter: https://twimlai.com/newsletter Check out our blog: https://twimlai.com/blog Follow us on Twitter: https://twitter.com/twimlai Follow us on Facebook: https://facebook.com/twimlai Follow us on Instagram: https://instagram.com/twimlai