The Second Wave: From Neuroelectrodynamics to Electrodynamic Intelligence
Year: 2025
Type: article
Abstract: Current AI systems, particularly large language models (LLMs), excel at statistical reasoning and pattern recognition however, they remain symbolic and disembodied, relying on code, not physical processes. We propose a fundamentally different paradigm: NeuroElectroDynamics (NED), a non–von Neumann, physically grounded architecture where cognition emerges from real-time interactions of charge, field, and material structure. Computation flows through memristive, axon-like channels; learning arises from field-driven adaptation and ion dynamics, not backpropagation. Synaptic modulation is analog, using iontronic or ferroelectric junctions. Unlike digital systems, NED embeds memory, semantics, and computation in the same evolving substrate. A brain-scale system with ~10¹¹ neurons may achieve ~312.5 TB dynamic memory at <60 W, potentially scaling to 1.75 PB. This defines a new class of Electrodynamic Intelligence (EDI), self-organizing, embodied, and ultra-efficient. EDI systems represent a shift from simulating intelligence to physically instantiating it, suggesting how advanced intelligences may arise naturally or be engineered in other planetary environments
Author: Aur, Dorian
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7077148930
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