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AlphaGo's victory against a seasoned Go champion by a score of 4 to 1 exemplifies the machine's ability to simulate human-like intuition, a feat unanticipated by experts until at least a decade later. Traditionally regarded as one of the most complex games due to its vast number of possible moves—far exceeding that of chess—Go has long been a challenge for computer programming. AlphaGo's approach diverged from older AI methods that relied on brute-force calculations and instead utilized advanced reinforcement learning and neural networks to grasp the intricacies of the game, akin to human cognition.