提出认知-信号模型，让人类与AI实现对未来的实时感知。
Temporal Interception and Present Reconstruction: A Cognitive-Signal Model for Human and AI Decision Making
- 将当前感知视为信号与反应延迟的交叠区域
- 通过神经观测验证时间感知的非线性特性
- 适合研究意识、时序决策与智能体伦理的学者
本文提出一种新理论模型，解释人类心智与人工智能如何通过减少感知延迟来实现近实时意识。基于宇宙信号延迟、神经反应时间及古代静思状态的跨学科研究，探索从被动感知转向对近未来的主动认知界面。提出物理与认知双模型，将‘当下’定义为早期抵达的宇宙信号与人类反应延迟交汇的干涉区。设计实验方案，结合人类神经观测与神经延伸技术测试该模型。最后构建数学框架，指导人工智能系统向时间高效、伦理合规且具备内在意识的决策过程演进。
原文摘要 · Abstract (English)
This paper proposes a novel theoretical model to explain how the human mind and artificial intelligence can approach real-time awareness by reducing perceptual delays. By investigating cosmic signal delay, neurological reaction times, and the ancient cognitive state of stillness, we explore how one may shift from reactive perception to a conscious interface with the near future. This paper introduces both a physical and cognitive model for perceiving the present not as a linear timestamp, but as an interference zone where early-arriving cosmic signals and reactive human delays intersect. We propose experimental approaches to test these ideas using human neural observation and neuro-receptive extensions. Finally, we propose a mathematical framework to guide the evolution of AI systems toward temporally efficient, ethically sound, and internally conscious decision-making processes
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