NLA Optimizes for Reconstructability, Not Truth
Turn_Trout · x · 2026-07-13
The author points out that NLA's goal is to maximize reconstruction accuracy, not to pursue "truth." Their only contact point with reality is a "warm start" guess made by Claude about the model's internal state before training; the encoder and decoder are then fine-tuned based on these guesses.
This explains why the training process is strongly influenced by the initial guesses: the system optimizes for reconstructability, not semantic truth.
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