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I understood it as: a signature of each pattern is stored as 'known' in a dataset. An AI learns which patterns are "known". I don't believe their method has fi

I understood it as: a signature of each pattern is stored as 'known' in a dataset. An AI learns which patterns are "known". I don't believe their method has fine control of placement of the 'readable' parts under the glue; this cuts out methods where you're writing something in data as part of authentication. But, it also makes production MUCH cheaper - you can later just read what you "wrote" under a tag. I would guess in the price points they imagine, this method is "random + read later". For your method - if you can write data, why not just write a digital signature of the item's serial number?

bsza 3y ago
We write data into the tag's digital memory, not the pattern. The pattern is immutable. We use the pattern to mask the tag's private key. The tag authenticates itself with that private key (which is installed on the tag by the manufacturer and can be signed with a CA cert to prove it comes from the manufacturer). The tag can't decrypt the key without the correct pattern, so simply peeling it off and sticking it onto a counterfeit won't work. There is no need for a database. The AI runs on the tag and makes sure tiny changes to the pattern won't make the private key unrecoverable by outputting a "low-res" version of the pattern that is immune to such tiny changes. That's how I understood it.