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Exploring Intelligence and Learning in Machines
This chapter investigates the intricate relationship between intelligence, statistics, and learning in both humans and machines. It emphasizes the importance of causal reasoning and background knowledge in creating effective artificial intelligence systems while critiquing the notion that intelligence is merely statistical mimicry. The discussion spans various themes, including self-supervised learning, strategic decision-making, and the evolutionary aspects of intelligence, ultimately revealing the complexities inherent in replicating human-like learning mechanisms in machines.