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If it's anything like Glaze, it's a complete meme. That took a lot of compute to glaze an image (with very visible artifacts) and was bypassed with some trival image processing on a shitty laptop.

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I don't think its meant to stop determined thieves, but rather automated web crawlers or more casual human copycats.

Why would automated web crawlers not throw the best de-Glazing techniques at their dataset before model training?

Because it increases the cost.

Compared to training a model on few thousand or more GPU-hours? Probably merit a footnote, at best.

Just for context LAOIN's largest dataset is 5.8 Billion images

And you'd be spending that compute time for what will be a tiny, tiny,portion of that

On the off chance that a single digit percentage of the dataset is glazed, they would probably detect and exclude, as that is easier.

The technical equivalent of a decorative rope around a painting in a museum to stop theft.

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