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Explore the development of LinkedIn's 150-billion-parameter foundation model designed for personalized ranking and recommendation systems in this conference talk. Learn from Principal AI Scientist Hamed Firooz and Principal Scientist Maziar Sanjabi as they share their journey of building large-scale AI solutions that personalize experiences for hundreds of millions of LinkedIn members. Discover the technical challenges and innovations involved in creating foundation models specifically tailored for ranking and recommendation tasks, drawing from the speakers' extensive experience in large-scale AI systems at both LinkedIn and Meta. Gain insights into the practical implementation of LLMs for personalization, the architecture decisions behind massive parameter models, and the real-world applications of these systems in serving personalized content at scale. Understand how cutting-edge AI research translates into production systems that handle billions of daily requests and learn about the evolution from traditional recommendation systems to LLM-based approaches for personalization.
