Frontier AI's real danger: silent out-of-distribution failures, not in-distribution performance
gerardsans · x · 2026-10-21
The author argues frontier AI's problem is never when it works in-distribution, but that it fails silently in sparse or out-of-distribution regimes. He defines "AI slop" as accumulated incorrect information from OOD sampling that superficial verification lets slide, noting that in high-stakes settings this can cause losses and even deaths.
Related event: Experts: The Real Frontier AI Risk Is Silent Out-of-Distribution Failure(2 posts)→
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