CephaloParrot AGI: Towards a Rhythm-Semantic, Emergent, Distributed Model of Intelligence

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Abstract

We propose CephaloParrot AGI, a novel paradigm inspired by the rhythmic cognition of parrots and the decentralized intelligence of octopuses. Unlike conventional LLMs and spiking neural networks, CephaloParrot operates through rhythm-anchored semantic converters (ESC), self-correcting meta-echo reflections (MER), and decentralized tentacular networks. This approach challenges token-based language models, offering a biologically plausible path toward adaptive, resilient, and emotionally resonant artificial general intelligence.

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