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Curated tech posts from X on AI, startups, and product development—signal without the doomscroll, updated on weekdays.
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Cool paper on catching alignment failures with Jev. The ideas is to ask Jev one generic yes/no question about a model's response, and use its probability as a score. With no extra training, that score separates failures from good responses well, with a median AUROC of 0.886. It is also cheap. On 19 benchmarks, a Jev pass cost $0.30, while the LLM judges those benchmarks use cost $18.96. Researchers built RLCDAlignBench from 44 existing benchmarks across ten failure types, including…
