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Debunking the Fraudulent Claim: Reading ≠ Training on IP

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Debunking the Fraudulent Claim: Reading ≠ Training on IP

2025-03-13

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Pattern matching systems like LLMs operate on fundamentally different mathematical principles than human reading. The claim that "reading books equals training on IP" fails under mathematical scrutiny. Pattern recognition systems measure distances in vector space without comprehension, while human reading develops conceptual frameworks through sequential information processing with vastly different data requirements and information extraction methodologies.

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Mathematical Fundamentals of the Distinction

Dimensional Processing Divergence

  • Quantitative architecture difference: Human reading processes information sequentially through neural networks (unidirectional); ML training builds statistical correlations across high-dimensional vector spaces (n-dimensional)
  • Core operation: Pattern matching systems measure distances between points in vector space without semantic comprehension
  • Threshold requirements: Pattern matching requires n>10,000 examples for statistical significance; human comprehension functions with n<10 examples

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