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Explore the intersection of human intuition and artificial intelligence in puzzle-solving through a detailed analysis of the New York Times Connections game in this 19-minute conference talk. Examine how AI algorithms can systematically evaluate gameplay using machine learning strategies including clustering, semantic mapping, and natural language processing. Learn about building AI-driven puzzle solvers and discover methods for quantitatively assessing gameplay complexity. Gain insights into semantic similarity analysis, relational alignment techniques, and multi-dimensional analysis approaches for understanding word relationships. Understand how Graph Neural Networks (GNNs) can be applied to puzzle-solving scenarios and explore the comparative advantages of human versus AI problem-solving approaches. Discover the potential impacts of artificial intelligence on puzzle game design and player engagement, while learning practical methodologies for analyzing word games through computational linguistics and machine learning frameworks.
