The Perfect Storm: Systemic Vulnerability of Large Language Models to Solar Weather
Authors/Creators
Description
First systematic investigation of correlations between space weather events and AI/LLM operational failures. Analysis of 700+ documented incidents across major AI platforms (OpenAI, Anthropic, Google) during January-November 2025 reveals that solar weather windows increase AI system failure rates by 1,150% (p < .001, Cohen's d = 1.90) within a characteristic 24-72 hour lag window following geomagnetic storms. Statistical validation using permutation testing with 50,000 iterations demonstrates highly significant temporal associations between space weather activity and infrastructure failures. Findings suggest vulnerability through geomagnetically induced currents affecting power delivery systems and enhanced cosmic radiation increasing bit-flip rates in computational hardware. Includes hypothesis regarding potential training corruption during periods of elevated solar activity. Complete dataset publicly available for independent verification.
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Additional details
Software
- Repository URL
- https://github.com/the-meta-value/The-Perfect-Storm
- Programming language
- CSV , Python
- Development Status
- Active