Reminds me of this:

https://youtu.be/JcJSW7Rprio

This is a very balanced take. I appreciate it ☺️

I flew back to America from Tokyo today and as a frequent traveler to Japan I can tell you it’s all of the above. As a very introverted, easily overstimulated person I love going to Japan because it’s my ‘quiet time’. Coming home I’m usually overwhelmed by the sheer noise of being in America.

1. People simply speak louder than they need to here. In Japan you speak in a hushed voice unless it’s necessary to raise it. Also people aren’t afraid to lean in a little closer to hear what is being said to them. In America people stand 2 meters away from each other and have to speak loud enough for the whole room to hear
2. People speak more and don’t value quiet time. In Japan you don’t speak on trains. Your inane conversation can wait. Its more pleasant for everyone if you just stay quiet. Then an American tourist boards and everyone in the car gets to hear all about their opinions on some anime whether they want to or not
3. People tent to interject / interrupt more here

Hopefully this didn’t come across too much as venting. I can’t wait to go back.

Came here to say this: Anki is infinitely better than some scammy ai enabled nonsense.

The challenge is Anki relies on the student being motivated to pursue the education. The solution to that is the student seeing the value and fun in what they’re learning. That can partially be provided by gamification, but really a passionate teacher with genuine enthusiasm is the best.

https://www.npr.org/2025/10/06/nx-s1-5544362/turkey-hair-transplants-tourism

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.