We measured how AI capabilities INTERACT as models scale. Below 3.5B, reasoning and truthfulness fight. Above it, they cooperate. The transition is engineerable. (2 papers + interactive dashboard + 7 falsifiable predictions)
r/artificial
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Data Science
THE FINDING (Paper 1: "Lying Is Just a Phase") Below a critical scale (~3.5B for Pythia), reasoning and truthfulness ANTICORRELATE: r = -0.989. Train the model to reason better, and it gets less truthful. This is the alignment tax. Above that scale, they COOPERATE. The tax vanishes. Not gradually - it flips. But here's what matters for practitioners: the critical scale is a design parameter, not a constant. Three levers shift it: Data curation: Phi at 1B achieves coupling characteristic of 10B web-trained. One unit of data quality ≈ 10x model scale.