AGI本质：自动混合编程

The Nature of AGI: Automated Hybrid Programming

摘要: 近一年来，AI的能力出现了爆发式增长，业界对AGI实现时间的预测不断提前。然而，对AGI的理论探索远远跟不上AI发展的步伐。本文提出一个唯象理论性质的“AGI公式”——AI_P + LLM = AGI(ASI)，其中AI_P即AI编程，二者通过“AI自激振荡”机制螺旋式相互增强，促使AI能力呈指数式增长。本文基于该公式得出11条推论，分为解释性推论和预测性推论两类：前者解释了AGI的本质、自主性、高速进化的成因；后者给出了AGI实现的量化判断标准、预测了实现时间节点、确认了ASI的可行性等等，并展望了后AGI时代的人机关系、硬件及物联网的爆发。本文的核心结论是：AGI的本质就是“自动混合编程”，AGI有望于2027年基本实现。

Abstract: Over the past year, the capabilities of AI have experienced an explosive growth, and the industry’s predictions for the timeline of achieving AGI have been constantly advancing. However, the theoretical exploration of AGI has lagged far behind the pace of AI development. This paper proposes a phenomenological theoretical formula for AGI − AI_P + LLM = AGI(ASI), where AI_P refers to AI programming, and the two enhance each other in a spiral manner through the “AI self-excited oscillation” mechanism, promoting the exponential growth of AI capabilities. Based on this formula, 11 inferences are derived, divided into explanatory inferences and predictive inferences: the former explains the essence, autonomy, and causes of rapid evolution of AGI; the latter provides quantitative judgment criteria for the realization of AGI, predicts the implementation timeline, confirms the feasibility of ASI, etc., and looks forward to the human-machine relationship, hardware, and the explosion of the Internet of Things in the post-AGI era. The core conclusion of this paper is: The essence of AGI is “automatic hybrid programming”, and AGI is expected to be basically realized by 2027.