News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a system can reason about content the way it reasons about language. However, that power comes with a fresh set of engineering challenges around cost, scale, and evaluation.<\/p>\n
LinkedIn<\/a> recently rebuilt its news feed to treat content recommendation as a sequence modeling problem. The general approach is to predict what a user will want next, much like an LLM predicts the next token in a sentence.<\/p>\n Tim Jurka<\/a> has worked at LinkedIn for 13 years and is currently a VP of Engineering. In this episode, Tim joins Matt Merrill to discuss how LinkedIn re-engineered its feed, how the team combines LLMs with traditional signals, managing inference costs at massive scale, steering content quality using natural language policies, and more.<\/p>\n Sponsorship inquiries: \n<\/p> The post How LLMs Are Reshaping Recommendation Systems<\/a> appeared first on Software Engineering Daily<\/a>.<\/p>","protected":false},"excerpt":{"rendered":" News feeds and recommendation systems have long relied on deep learning architectures that score each candidate item independently. As LLMs have matured, they have opened up a fundamentally different approach, where a system can reason about content the way it reasons about language. However, that power comes with a fresh set of engineering challenges around […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":[],"rop_publish_now_history":[],"rop_publish_now_status":"pending","footnotes":""},"categories":[1],"tags":[],"class_list":["post-9952","post","type-post","status-publish","format-standard","hentry","category-explore"],"_links":{"self":[{"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/posts\/9952","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/comments?post=9952"}],"version-history":[{"count":0,"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/posts\/9952\/revisions"}],"wp:attachment":[{"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/media?parent=9952"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/categories?post=9952"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/handoli.com\/index.php\/wp-json\/wp\/v2\/tags?post=9952"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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