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Finding bugs in code with large language models differs fundamentally from proof-of-work mining. LLM executions saturate possible code states, so increasing sampling beyond a threshold does not improve bug discovery. The asymmetry of resources that guarantees a winner in hash collisions does not apply to AI-driven vulnerability detection.
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