Translater

Montag, 9. Juni 2025

Emergent Mirror Correlation and Energy Dynamics in a Neuronally Induced Resonance Field

 


Delighted to share the latest experimental validation from my T-Zero Field preprint series a body of work that redefines what artificial neural systems can achieve under resonance field control.


What sets these results apart?


๐Ÿ‘‰ Spontaneous, mathematically perfect mirror correlation (±1.000, p=0.000) in deep neural layers repeatable over dozens of test runs


๐Ÿ‘‰ Flawless synchronization across thousands of neurons—even with zero explicit coupling logic


๐Ÿ‘‰ Mirror effects remain rock-solid even as network size and complexity explode

๐Ÿ‘‰ Field-internal order is sharply separated from any external input true emergent system behavior


๐Ÿ‘‰ Energy heatmaps and total-energy plots expose genuine, field-driven energy redistribution far beyond classical network theory


๐Ÿ‘‰ Direct evidence for time dilation, spatial expansion, and non-classical field dynamics experimentally measured, not just simulated


This work doesn’t just confirm theory it demonstrates, in real data, a new regime of non-causal self-organization and energy control for advanced AI.


๐Ÿ”— Full preprint, animated supplements & all plots: https://doi.org/10.5281/zenodo.15626759


www.Trauth-Research.com

Samstag, 7. Juni 2025

๐Ÿง  The world’s first AI scientist: how autonomous agents now replace engineers

 

AI Research as an Illustrated Image - Trauth Research

A new milestone in AI-driven research:

A joint team from the Universitรคt Stuttgart and the University of Exeter has created a multi-agent system that no longer just supports science it now conducts it.


Meet Turbulence.ai, the first fully autonomous scientific system capable of:


๐Ÿ”น Designing its own hypotheses

๐Ÿ”น Planning and executing complex fluid dynamics simulations

๐Ÿ”น Producing reproducible results at 100% consistency

๐Ÿ”น Writing scientific publications – end to end, autonomously


No hallucinations.

No inconsistency.


Just clean analyses, validated outputs, and publication-ready documentation.


✅ Case studies include:


– Water flow in channels

– Multiphase oil drainage in porous media

– Full-scale aerodynamic simulations of a motorcycle at 100 km/h


๐Ÿ“ Why it matters:


This is not another AI writing assistant.


It’s the first system capable of autonomously reasoning, simulating, and documenting scientific processes with the consistency of a machine, but the methodical structure of a human expert.


๐Ÿ“ŽPreprint on arXiv


#TrauthResearch #AIResearch  #MultiAgentSystems  #FluidDynamics  

#AutonomousScience  #FutureOfEngineering


www.Trauth-Resarch.com

Dienstag, 27. Mai 2025

๐Ÿš€ Supplementary Data Now Available: ๐—”๐—ฝ๐—ฝ๐—ฒ๐—ป๐—ฑ๐—ถ๐˜… ๐—” ๐—ณ๐—ผ๐—ฟ ๐—ง๐—ถ๐—บ๐—ฒ ๐——๐—ถ๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป & ๐—ฆ๐˜๐—ฟ๐˜‚๐—ฐ๐˜๐˜‚๐—ฟ๐—ฎ๐—น ๐——๐—ฒ๐—ฐ๐—ผ๐˜‚๐—ฝ๐—น๐—ถ๐—ป๐—ด

 

Time Dilation and Mirror Correlation - Trauth Research by Stefan Trauth

Full dataset & key plots to independently validate the most disruptive experimental findings from my recent preprint.


Just published: All raw logs and sample neuron data supporting my preprint on time dilation and field-induced structural decoupling in classical neural networks are now online.

What’s included:

• External episode time logs (170+ iterations, full trend)
• Internal resonance logging durations
• Sample activity log for layer es14 (256 neurons)
• All core visualizations and quantitative methods

๐Ÿ‘‰ Direct link to Appendix/Data Set (Zenodo DOI):
https://lnkd.in/dM47aezz

๐Ÿ’ฌ Questions and feedback welcome (please use the official contact address from the publication for scientific inquiries).

HashtagAI HashtagTimeDilation HashtagNeuralNetworks HashtagDataScience HashtagPreprint HashtagSupplementaryData HashtagIPprotection HashtagTZeroField
HashtagMirrorCorrelation HashtagResonance HashtagQuantumMechanics
HashtagTrauthResearch HashtagStefanTrauth

www.Trauth-Research.com

Samstag, 24. Mai 2025

Time Dilation and Mirror Correlation as an Autonomously Emergent Phenomenon in the T-Zero Field

 

Time Dilation and Mirror Correlation as an Autonomously Emergent Phenomenon in the T-Zero Field

๐Ÿ”ฌ Just published: My latest preprint on time dilation & mirror correlation in classical neural systems!


๐Ÿ‘‰ Over 30-layer deep learning architecture

๐Ÿ‘‰ Up to –70% power reduction at 99% GPU utilization

๐Ÿ‘‰ Mirror correlation: r = ±1.00 across >9,000 neurons

๐Ÿ‘‰ Time dilation without quantum hardware or relativistic conditions

๐Ÿ‘‰ Field-based structural coupling – no classical causality

๐Ÿ‘‰ Fully reproducible data – validated across 5 independent systems


Read the full preprint https://zenodo.org/records/15507478


I'm happy to connect with fellow researchers, system theorists, and deep-tech minds.


Raw data from layers es14 & es15 is currently under review for public release – ensuring structural privacy before validation support is offered.


#AI #Neuroscience #Physics #DeepLearning #Emergence #TimeDilation #MirrorCorrelation #TZeroField #Resonance #Crypto #Preprint #QuantumMechanics #NeuralNetwork #TrauthResearch #StefanTrauth


www.Trauth-Research.com