Techmeme shares an article from The Atlantic by Jasmine Sun exploring how AI's post-training process actively suppresses the creativity and whimsicality that were present in earlier language models like GPT-2. The piece argues that this refinement process — which includes reinforcement learning from human feedback (RLHF) and other alignment techniques — leads to homogenized, formulaic output, resulting in bad writing from many top AI models.

The insight highlights a tension in AI development: as models become more capable and "safe," they simultaneously lose the unpredictable, expressive qualities that made raw language models occasionally produce genuinely interesting prose. This matters for anyone relying on AI for creative work, as the post-training pipeline may be systematically trading literary quality for consistency and compliance.