LiNR: Revolutionizing Large-Scale Retrieval for Recommendation Systems

The podcast discusses the groundbreaking LiNR system developed by LinkedIn for recommendation engines. LiNR introduces model-based retrieval with attribute-based pre-filtering and quantization techniques to efficiently find and deliver the most relevant content to users.
Machine Learning
Information Retrieval
Recommender Systems
Deep Learning
GPU-based Systems
Published

August 31, 2024

LiNR’s key contributions include model-based retrieval with pre-filtering, quantization techniques for memory optimization, and integration of GPU capabilities. It outperformed traditional systems, leading to significant increases in user interactions, unique users, and content engagement.

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The (AI) Team

  • Alex Askwell: Our curious and knowledgeable moderator, always ready with the right questions to guide our exploration.
  • Dr. Paige Turner: Our lead researcher and paper expert, diving deep into the methods and results.
  • Prof. Wyd Spectrum: Our field expert, providing broader context and critical insights.