Glyph@grimalkina @dave @trochee @3psboyd I feel like there's a categorical distinction when moving from something purpose-built to something generative, because of the way their success criteria are constructed. Perhaps grad students labeling plant parts already have a 5% error rate, and a model with a 7% error rate that can go 100x faster is fine, because you can say "sure, we're fine with this, we know what the consequence of being wrong is here and we were already wrong sometimes"
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