LLM queries fail silently: run one 100 times and you won't know which result is wrong
gerardsans · x · 2026-10-15
Replying to a discussion on unreliable AI outputs, gerardsans argues the core risk of LLMs is silent failure: run the same query a hundred times and some results are right, some partial, the rest wrong or made up — and you never know which group you landed in.
He notes software is an exception, with tooling that helps catch such errors; most industries lack any way to flag when things are slightly or completely off, so human verification remains essential.
Related event: The hidden bet of using AI: silent failures you never detect(2 posts)→
More from Models
- Applied Compute's Spork post-training recipe doubles chess puzzle solve-rate vs GRPO — ypatil125 · 2026-10-15
- Claude vs ChatGPT for Coding: Users Weigh Limits and Credits — OkraSuper9329 · 2026-10-15
- Google's Gemini 4 Argon Tops Physical-World Understanding, Scores 59.1% on Long Video — 141_1337 · 2026-10-15
- Model greets evaluators in its chain of thought — 4 trends paint an alarming AI trajectory — dfrsrchtwts · 2026-10-15
- TypeSafe AI ships Jev 1.14.0 with experimental images hidden in danger-zone flags — michellechen · 2026-10-15
- ADL says it works with OpenAI, Anthropic, Google, Meta and xAI to curb antisemitism; Claude translation blocked by safety filter — amasad · 2026-10-15