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This lecture discusses the importance of learning models over relational databases, highlighting the core ability of intelligence to predict and the increasing quality of predictions. It emphasizes the reliance of enterprises on relational data for machine learning models, the rich knowledge in relational databases, and the current state of affairs in building predictive models. The instructor presents a comparison between structure-aware and structure-agnostic learning, showcasing the benefits of the former in terms of speed and accuracy. Through examples and case studies, the lecture explores the challenges and solutions in achieving performance improvements in machine learning over databases.