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Large Language-Style Universal Models for Short Video Recommendations

n this talk we are going to provide details on a new ray-based solution for a large-scale recommender system for Josh, the leading short video platform in India having 85M DAU, 170M MAU and 100M+ Videos. Our design is motivated by the progress in large language modeling and comprises a single big model with sparse inputs and outputs with both early and late fusion for different outputs (like retrieval and ranker outputs). These models are scaled with a universal graph search algorithm which is a generalization of HNSW. We will discuss the advantages of this approach, such as simplified vertical integration and end-to-end content training from raw user actions and present empirical results. This solution led to double digit improvements in engagement metrics on the platform Find the slide deck here: https://drive.google.com/file/d/102pF... About Anyscale --- Anyscale is the AI Application Platform for developing, running, and scaling AI. https://www.anyscale.com/ If you're interested in a managed Ray service, check out: https://www.anyscale.com/signup/ About Ray --- Ray is the most popular open source framework for scaling and productionizing AI workloads. From Generative AI and LLMs to computer vision, Ray powers the world’s most ambitious AI workloads. https://docs.ray.io/en/latest/ #llm #machinelearning #ray #deeplearning #distributedsystems #python #genai