Our fascination with intelligent machines goes back to ancient times with the mythical automaton Talos, Aristotle's mode of mechanical thought (syllogism) and Heron of Alexandria's mechanical machines. However, the quest for Artificial General Intelligence (AGI) has been troubled with repeated failures. Recently, there has been a shift towards bio-inspired software and hardware, but their singular design focus makes them inefficient in achieving AGI. Which set of requirements have to be met in the design of AGI? What are the limits in the design of the artificial? A careful examination of computation in biological systems suggests that evolutionary tinkering of contextual processing of information enabled by a hierarchical architecture is key to building AGI.

翻译：我们对智能机器的迷恋可追溯至古代神话中的自动机塔罗斯、亚里士多德的机械思维模式（三段论）以及亚历山大港的希罗发明的机械装置。然而，追求人工通用智能（AGI）的征程屡遭失败。近期，学界虽转向仿生软硬件设计，但其单一设计聚焦致使实现AGI效率低下。设计AGI需满足哪些需求集？人工之物的设计存在何种边界？对生物系统中计算过程的审慎考察表明，通过层级化架构实现的上下文信息处理之进化修补，乃是构建AGI的关键所在。