This seems like very standard ML. I'm not surprised it works, but also it likely takes a huge amount of training data (i.e. print samples) to recognize a specific machine.

I've done stuff like this. For instance I took a pre-trained model that could identify animals and used reinforcement learning to feed it thousands of annotated images of my cats. After this fine-tuning it could reliably tell the difference between them. Useful? Yes. Neat? Yes. But it's not like it can identify a cat it's never been trained on.

So it's interesting and useful, but not as impressive or useful as the article makes it seem.

Also I'm sure something as simple as changing a nozzle or even what slicer is used would completely throw it off.