// model benchmarks

Source: Transformer

Large language models are demonstrably improving at persuasion tasks—mimicking human conversational patterns, generating convincing synthetic media, and circumventing security systems—which moves the persuasion problem from theoretical to operational. The author resists catastrophism precisely because incremental capability gains don't automatically translate to deployed harm; the gap between what a model can do in a lab and what it actually does at scale in the world remains wide, and that gap is where policy, friction, and incentives live. The question is whether institutions will build adequacy in detection, authentication, and friction before these capabilities become cheap enough to weaponize at population scale.