Artificial intelligence, as a technique, refers to computational methods that enable machines to perform tasks that typically require human cognitive capabilities, such as perception, reasoning, learning, and decision-making. Core AI techniques include search and optimization algorithms, symbolic reasoning and knowledge representation, probabilistic inference, and machine learning approaches such as supervised, unsupervised, and reinforcement learning. These techniques often rely on statistical modeling, function approximation, and gradient-based optimization to construct models that generalize from data. AI techniques are implemented in software frameworks, integrated into pipelines for training, validation, and deployment, and are evaluated using task-specific performance metrics and robustness assessments.
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