[kevinlenane]

Yes thats exactly how neural networks are intended to work - the more we see common anomalies the better we are at recognizing them - and it will happen overall and set by set. Initially we'll have it working for a few sets but we wont have to feed it training data for all of them really only for representative and unique sets. So one or two tobacco sizes - a representative set for circle cards etc. Then over time the system as a whole gets better as does the relative ability to be accurate within each set. Authenticity is actually more era specific where grading tends to be more generic with any major differences having to do with how shiny modern cards are and even this only impacts the surface grading dynamics to account for, say, a smudge, etc...