Design activity -- constructing an artifact description satisfying given goals and constraints -- distinguishes humanity from other animals and traditional machines, and endowing machines with design abilities at the human level or beyond has been a long-term pursuit. Though machines have already demonstrated their abilities in designing new materials, proteins, and computer programs with advanced artificial intelligence (AI) techniques, the search space for designing such objects is relatively small, and thus, "Can machines design like humans?" remains an open question. To explore the boundary of machine design, here we present a new AI approach to automatically design a central processing unit (CPU), the brain of a computer, and one of the world's most intricate devices humanity have ever designed. This approach generates the circuit logic, which is represented by a graph structure called Binary Speculation Diagram (BSD), of the CPU design from only external input-output observations instead of formal program code. During the generation of BSD, Monte Carlo-based expansion and the distance of Boolean functions are used to guarantee accuracy and efficiency, respectively. By efficiently exploring a search space of unprecedented size 10^{10^{540}}, which is the largest one of all machine-designed objects to our best knowledge, and thus pushing the limits of machine design, our approach generates an industrial-scale RISC-V CPU within only 5 hours. The taped-out CPU successfully runs the Linux operating system and performs comparably against the human-designed Intel 80486SX CPU. In addition to learning the world's first CPU only from input-output observations, which may reform the semiconductor industry by significantly reducing the design cycle, our approach even autonomously discovers human knowledge of the von Neumann architecture.

翻译：设计活动——构建满足给定目标和约束的人工制品描述——将人类与其他动物及传统机器区分开来，赋予机器达到或超越人类水平的设计能力一直是长期追求的目标。尽管机器已借助先进人工智能技术展现出设计新材料、蛋白质和计算机程序的能力，但这类对象的搜索空间相对较小，因此"机器能否像人类一样设计？"仍是一个未解问题。为探索机器设计的边界，本文提出一种新的人工智能方法，可自动设计中央处理器（CPU）——计算机的"大脑"，也是人类迄今设计的最复杂器件之一。该方法仅通过外部输入-输出观测而非形式化程序代码，生成以二元推测图（BSD）图结构表示的CPU电路逻辑。在BSD生成过程中，分别采用基于蒙特卡洛的扩展方法和布尔函数距离保证准确性与效率。通过高效探索前所未有的10^{10^{540}}量级搜索空间（据我们所知，这是所有机器设计对象中最大的），从而推动机器设计极限，我们的方法仅用5小时便生成了工业级RISC-V CPU。流片后的CPU成功运行Linux操作系统，性能与人类设计的Intel 80486SX CPU相当。除了学习世界上首个仅通过输入-输出观测生成的CPU（这可能通过显著缩短设计周期而革新半导体行业），我们的方法还自主发现了冯·诺依曼架构的人类知识。