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this post was submitted on 28 Aug 2023
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Not well versed in the field, but understand that large tech companies which host user-generated content match the hashes of uploaded content against a list of known bad hashes as part of their strategy to detect and tackle such content.
Could it be possible to adopt a strategy like that as a first-pass to improve detection, and reduce the compute load associated with running every file through an AI model?
It's more than just basic hash matching because it has to catch content even if it's been resized, cropped, reduced in quality (lower JPEG quality with more artifacts), colour balance change, etc.
Ah, of course - that's unfortunate, but thanks for the pointer.