this post was submitted on 10 Sep 2023
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A lot of these relied on common mistakes that "AI" algorithms make but humans generally don't. As language models are improving, it's harder to detect.
They're also likely training on the detector's output. That why they build detectors. It isn't for the good of other people. It's to improve their assets. A detector is used to discard some inputs it knows are written by AI so it doesn't train on that data, which leads to it out competing the detection AI.