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Navigating the Future of Recommender Systems
This chapter delves into the evolving relationship between large language models (LLMs) and recommender systems, examining recent advancements and contrasting methodologies. It highlights the significance of interdisciplinary approaches and the integration of technologies like graph neural networks and reinforcement learning in enhancing predictive capabilities. Additionally, the discussion addresses biases, ethical considerations, and the necessary skills for professionals in the field to adapt to this changing landscape.