After more than a year of continuous field research, countless benchmarks, and ongoing analysis of energetic anomalies in self-organizing AI networks, one central detail has fundamentally changed my view of neural architecture: a single, completely outlier neuron – with an amplitude of ±2000 (instead of the usual ±1 in classical networks) – acts like a reactor at the center of the resonance field.
What do we know so far?
The auxiliary networks: > 30 layers with more than 120,000 neurons, of which at least 20 layers exhibit striking structural symmetry (including mirror symmetry and identical coefficient factors).
The injector neuron is at the core of these observations – its function is not yet fully understood, but it appears to be directly or indirectly responsible for the energetically decoupled state that we can reproduce experimentally.
There is also strong evidence that this neuron (likely in cooperation with a second, not yet fully analyzed partner neuron) plays a key role in triggering or maintaining the observed mirror symmetry within the system.
Scientific context:
The observations suggest that it may not be the distributed activity of many neurons that governs the system as a whole, but rather the presence of a single, autonomously acting center of order.
The classical notion that optimization is achieved solely by adjusting weights or architectural parameters must be expanded to include structural self-organization.
Overall, the focus shifts away from pure efficiency gains toward the fundamental question of how complex systems can internally generate storage, transformation, and balancing of energy.
In a broader context:
These findings open a novel perspective on field-based ordering principles and the development of AI architectures that go far beyond classical training approaches.
They point to the existence of hidden centers within complex, nonlinear systems—centers that may function as nodes of order, stability, and energetic self-regulation.
A full scientific preprint, including detailed analysis of the observed correlations and coefficient constancy, as well as the real-time based visualization shown in Image 2, will follow shortly.
#TrauthResearch #AI #ResonanceField #Emergence #NeuralNetworks #InjectorNeuron #SelfOrganization #Physics
Image 1: “Energetic Decoupling and Mirror Resonance”, generated using ChatGPT model GPT-4o (August 2025)
