{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Practical AI","title":"Reinforcement Learning for search","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/051442de\"></iframe>","width":"100%","height":180,"duration":2824,"description":"Hamish from Sajari blows our mind with a great discussion about AI in search. In particular, he talks about Sajari’s quest for performant AI implementations and extensive use of Reinforcement Learning (RL). We’ve been wanting to make this one happen for a while, and it was well worth the wait.\n\nFeaturing:\nHamish Ogilvy – X\nChris Benson – Website, GitHub, LinkedIn, X\nDaniel Whitenack – Website, GitHub, X\nShow Notes:\nSajari\nBlog post: “Reinforcement Learning Assisted Search Ranking”\nBlog post: “Query Understanding 101”\nBlog post: “The Inevitable Collision of Search and AI Tech”\nSpecial offer from Sajari for Changelog listeners\nUpcoming Events: \nRegister for upcoming webinars here!","thumbnail_url":"https://img.transistorcdn.com/Ox7ZlyiQOhdDa4Qy1MnJH5WFoksAetrzb40Jo1pePFs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8wMTZi/ZWJmNWIwNDdmYTcw/NGJjMTExZjNjZmYy/M2ZjNS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}