Improving Recommendation Systems & Search in the Age of LLMs
Read OriginalThis technical article analyzes the evolution of industrial search and recommendation systems with the advent of large language models (LLMs). It details LLM-augmented model architectures, such as YouTube's Semantic IDs for cold-start problems, LLM-assisted data generation, training paradigms like distillation and LoRA, and the move toward unified frameworks for search and recommendations.
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