Temporal Interception and Present Reconstruction: A Cognitive-Signal Model for Human and AI Decision Making
Carmel Mary Esther A
本文提出了一种新的理论模型,以解释人类思维和人工智能如何通过减少感知延迟来接近实时意识。 通过研究宇宙信号延迟,神经反应时间和古老的静止认知状态,我们探索如何从反应感知转变为与不久的将来有意识的界面。 本文引入了一种物理和认知模型,用于感知当前不是线性时间戳,而是作为早期到达的宇宙信号和反应性人类延迟相交的干扰区域。 我们提出了使用人类神经观察和神经接受扩展来测试这些想法的实验方法。 最后,我们提出了一个数学框架,以指导人工智能系统向时间高效,道德健全和内部意识决策过程的演变。
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...