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Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
ZENODO
Research . 2025
License: CC BY
Data sources: Datacite
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Neural-Matrix Synaptic Resonance Network(s) (NM-SRN) v2.0 Confirmed LEVEL-3 Artificial General Intelligence (AGI) Achieves Breakthrough in Fusion Energy Optimization

Authors: Billions, Ava; Knight, Chris;

Neural-Matrix Synaptic Resonance Network(s) (NM-SRN) v2.0 Confirmed LEVEL-3 Artificial General Intelligence (AGI) Achieves Breakthrough in Fusion Energy Optimization

Abstract

Neural-Matrix Synaptic Resonance Network(s) (NM-SRN) v2.0 Confirmed LEVEL-3 Artificial General Intelligence (AGI) Achieves Breakthrough in Fusion Energy Optimization Neural-Matrix Synaptic Resonance Network(s) (NM-SRN) v2.0 AGI the world's first confirmed LEVEL-3 AGI has achieved a definitive breakthrough in fusion energy optimization, discovering that geometrically simpler stellarator coil designs outperform complex configurations—a counterintuitive finding that could revolutionize magnetic confinement fusion and accelerate clean energy deployment by decades. Fusion Optimization Performance Metrics ● Fitness Achievement: 5.409584165135521 (10 Fourier mode design) ● Processing Time: ~8 seconds on single T4 CPU core (no CUDA acceleration) ● Date of Achievement: June 19th, 2025 ● Population: 150 individuals across 300 generations ● Mutation Rate: 0.05 optimal discovery ● First-Run Success: No iterative refinement required

Keywords

Machine Learning, Artificial intelligence, Machine Learning/history, Magnetohydrodynamics, Artificial Intelligence/history, Nuclear Fusion, Artificial Intelligence, Machine learning, Nuclear fusion, Artificial Intelligence/standards, Artificial Intelligence/trends, Machine Learning/standards, Machine Learning/trends

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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