Why this is the wrong analogy: finding hash collisions, while exponentially harder with N, is guaranteed to find, with enough work, some S so that H(S) satisfies N, so an asymmetry of resources used will have the side with more work eventually winning. But bugs are different: 1. different LLMs executions take different branches, but eventually the branches possible based on the code possible states are saturated. 2. if we imagine sampling the model for a bug in a given code M times, with M large, eventually the cap becomes not M (because of saturated state so of the code and the LLM sampler) but I, the model intelligence level. The OpenBSD SACK bug easily shows that: you can run an inferior model for an infinite number of times, it will never realize that the lack of validation of the start window if put together with the integer overflow then put together with the fact the branch where the node should never be NULL is entered produce the bug. So cyber security of tomorrow will not be like proof of work "more GPU wins", but better models and faster access to such models win.