通用智能需要什么：跨描述层次的不可约约束
What General Intelligence Requires: Non-Reducible Constraints Across Levels of Description
AI总结：
探讨通用智能所需条件，提出其结构约束存于不同层次且不可约，单一架构进展或规模扩展无法产生AGI。通过多视角审视得出结构约束分类法并深入研究部分约束，还给出可证伪预测，将描述框架转为研究计划。
AI中文摘要：
支撑人类全方位认知成就的通用智能并非仅计算架构的属性。本文提出一个论点：通用智能的结构约束存在于不同描述层次且相互不可约。这意味着单一架构进展或规模扩展计划本身无法产生通用人工智能（AGI），研究计划须依据完整约束概况评估。通过从人工智能系统研究、人类学、法律和经济学四个证据视角审视通用智能，并辅以科幻小说作为启发式方法，得出23个结构约束的分类法并深入研究6个。最后得出五个可证伪预测，将描述框架转化为研究计划。
英文摘要：
General intelligence, of the kind that underwrites the full range of human cognitive achievement, is not a property of computational architecture alone. This paper advances a single thesis: the structural constraints on general intelligence occupy distinct levels of description and are mutually non-reducible, in the sense that the special-sciences tradition gives to that term. It follows that no single architectural advance, and no continuation of the scaling programme by itself, can produce artificial general intelligence (AGI), and that research programmes must be evaluated against the full constraint profile rather than against performance on any one benchmark. The thesis is developed through a method that reads general intelligence through four evidential lenses, AI systems research, anthropology, law, and economics, each anchored to a distinct level of description, supplemented by speculative fiction used as a disciplined heuristic in the context of discovery rather than the context of justification. Applying the method yields a taxonomy of twenty-three structural constraints organised into eight clusters; six are examined in depth and ordered as an ascending ladder of levels, with explicit bridges showing why progress at one level cannot carry to the next. The argument issues in five falsifiable predictions, each stated with a named benchmark family and a disconfirmation condition, converting a descriptive framework into a research programme with a longer horizon than the scaling hypothesis implies.
