Abstract Commonsense intelligence is a long-standing puzzle in AI. Despite considerable advances in deep learning, AI continues to be narrow and brittle due to its lack of common sense. Why is common sense so trivial for humans but so hard for machines? In this essay, I map the twists and turns in recent research adventures toward commonsense AI. As we will see, the latest advances on common sense are riddled with new, potentially counterintuitive perspectives and questions. In particular, I discuss the significance of language for modeling intuitive reasoning, the fundamental limitations of logic formalisms despite their intellectual appeal, the case for on-the-fly generative reasoning through language, the continuum between knowledge and reasoning, and the blend between symbolic and neural knowledge representations.

中文翻译：

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常识情报的奇特案例

摘要 常识智能是人工智能中长期存在的难题。尽管深度学习取得了长足的进步，但由于缺乏常识，人工智能仍然是狭隘而脆弱的。为什么常识对人类如此微不足道，而对机器却如此困难？在这篇文章中，我描绘了最近对常识性 AI 的研究冒险中的曲折。正如我们将看到的，常识的最新进展充满了新的、可能违反直觉的观点和问题。特别是，我讨论了语言对直觉推理建模的重要性，逻辑形式主义的基本局限性，尽管它们具有智力吸引力，通过语言进行即时生成推理的案例，知识和推理之间的连续统一体，以及符号之间的融合和神经知识表示。