Sounds promising, right? I spent some time testing it, but results were poor—high false positives and false negatives, no clear threshold for reliable classification. Plus, it suffers from high inference costs, poor cross-model generalization, difficulty deploying large models locally, and lack of access to closed-source model weights. All in all, it’s neither elegant nor reliable.
«Били в одно место». Российский газовоз уничтожен украинскими дронами в Средиземном море. Что известно об атаке и судьбе моряков14:20
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But that analysis treated bugs as abstract data points. This time I asked different questions: Who writes the buggy code? When do they write it? And who are the super-reviewers who catch bugs faster than anyone else?
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