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241. Gary F. Marcus with Ted Chiang How to Make AI Work for Us (And Not the Other Way Around)

Town Hall Seattle Science Series

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Understanding Causal Reasoning in AI

This chapter explores the differences between causal reasoning and statistical reasoning in artificial intelligence, illustrated through an engaging river crossing analogy. It highlights the limitations of current AI systems in grasping abstract concepts and causal relationships, with a focus on future advancements in complex fields like medical literature.

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