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• Netflix faces a variety of challenges in personalization, including improving diversity, freshness, and fairness of recommendations
• Recent trends in improving personalization include using deep learning for recommendations, causality to understand the impact of recommendations, bandits to optimize recommendations, and objectives to measure success
• Deep learning involves learning embeddings for user and item IDs and using them to make predictions
• Causality involves understanding the impact of recommendations on user behavior using randomized experiments
• Bandits involve optimizing recommendations by balancing exploration and exploitation
• Objectives involve measuring success using metrics that capture user satisfaction and fairness
• Netflix is hiring for research and summer intern positions in personalization