"While the Feed has long been AI-powered, recent LLM advances gave us the opportunity to rethink what's possible. That's why we're rolling out a new advanced ranking system, powered by LLMs and GPUs, that better understands what a post is actually about and how it relates to a member's evolving interests and career goals."
"In practical terms, if you happen to be interested in electrical engineering' but engage heavily with posts about small modular reactors,' traditional keyword-based systems might miss the connection. Our LLM-based retrieval understands these topics are semantically related because the underlying language model brings world knowledge learned from its massive pre-training corpus it knows that electrical engineers often work on power grid optimization, renewable energy."
"The new system is designed to be more adaptive to evolving user interests, as opposed to being guided by historical markers. LinkedIn's algorithm uses all the information each user has uploaded to guide what they're shown in-stream, including profile info, skills, geography and the content they engage with in the app."
LinkedIn has upgraded its feed algorithm architecture to leverage large language models and GPU technology for improved content ranking and recommendations. The new system moves beyond historical engagement metrics to focus on users' current and evolving interests, career goals, and contextual relevance. By analyzing user profile information, skills, geography, and recent activity, the algorithm now provides more adaptive and fresh feeds. The LLM-powered approach enables semantic understanding of content relationships that traditional keyword-based systems miss, allowing the platform to connect related topics through deeper language comprehension. This advancement aims to deliver more compelling and personalized feed experiences that better reflect users' present professional interests.
Read at www.socialmediatoday.com
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