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(Source: Bloomberg)

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.

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