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> That problem along with its many solutions are surely littered throughout the training data. Not to mention, it would be trivial to overfit on that problem.

It would be trivial to over-fit, if that was their goal.

But why would there be a large number of good SVG images of pelicans on bikes? Especially relative to all the things we actually want them to generalise over?

Surely most of the SVG images of pelicans on bikes are, right now, going to be "look at this rubbish AI output"? (Which may or may not be followed by a comment linking to that artist who got humans to draw bikes and oh boy were those humans wildly bad at drawing bikes, so an AI learning to draw SVGs from those bitmap pictures would likely also still suck…)



Because it's become the iconic test for them and countless articles have been written about it with plenty of examples.


I added the word "good" in there, you may have replied before seeing that edit.




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