Rohan Paul@rohanpaul_ai · X该论文认为当前AI主要建立在网络数学而非知识理论上。人脑以极低功耗做出快速自适应决策，而前沿AI依赖巨大算力。生物智能高效是因为围绕目标、上下文和决策组织意义。论文将心智活动分为物理认知、情绪认知、心智认知和智能，其中智能指在情境仍有效时做出有用决策。提出的“合成智能”将使用结构化语义知识（信息与目的绑定），而非仅依赖语法、统计或神经网络权重。通过不对称信息解析模型展示如何将知识组织成决策图，以捕食者-猎物为例，每个状态仅包含少数可能动作。
Intelligence may be less about bigger models and more about better knowledge structures.
This paper argues that current AI is being built mostly on network mathematics， not on a theory of knowledge.
A human brain makes fast， adaptive decisions on roughly the power of a dim light bulb， while frontier AI often buys competence with enormous computation.
The paper says biological intelligence may be efficient because it organizes meaning around goals， context， and decisions， instead of mainly searching through language patterns.
It separates mental activity into physical cognition， emotional cognition， mental cognition， and intelligence， where intelligence means making useful decisions while the situation still matters.