AI Scaling as Pattern Saturation via Computational Resources
August 27, 2026
Large language models act as pattern absorbers that operationalize any exposed data structure. Once a domain's pattern space is programmatically enumerated, model capability scales directly with available computational resources.
HOW THIS AFFECTS YOU
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researcherYou can view scaling as a data-enumeration problem rather than just parameter growth.
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founderYou should focus on domains where pattern spaces are exhaustible and enumerable.