Remark. A no-free-feedback result, not a no-learning result [ftip-007T]
Remark. A no-free-feedback result, not a no-learning result [ftip-007T]
Theorem [ftip-007S] says that the declared observations supply no information that distinguishes \(w_0\) from \(w_1\). It does not say that the output must equal the initial model, that the parameters cannot change, or that performance cannot improve in both worlds. Pretraining, inductive bias, computation on the observed records, and generalization may still produce an improvement shared by the two worlds.
Calling the theorem a no-learning result would therefore erase the central condition: only world-dependent conclusions unavailable from the common transcript are ruled out.