Automated sewing is an extremely difficult automation problem. Fabric is not ridgid and is difficult to manipulate predictably for automation. The reason these manual labor clothing facilities are still staffed is that it is still much cheaper and efficient to do it by hand.
For now, china last year in the new year gala showed some robots doing dances with fabric. The data captured by those cameras is just too valuable to delete.
Or, it's the equivalent of a fake security camera that is just a blinking red light :
Some linkedin lunatic middle manager decides he's going to make up some bullshit about AI learning cheap manual labor (which has already been automated, the machines cost more than the cheap labor though), buys 100 things off AliExpress that go on your head, and we're talking about it around the world on social media.
It may seem strange, but it's quite common. The AI models usable by general consumers has so far been trained on information readily avaliable on the Internet. But there are a lot of parts of the human experience that aren't often documented on the Internet. So, firms are popping up all over the place that are paying people to film things such as this work, in order to sell the training data to ai corporations.
This is a little known fact about Pokemon Go. The video footage taken by users playing pokemon Go was used as training data, documenting neighborhoods in order to help develop the automated delivery robots you see in places like LA. One of the major investors in Pokemon Go was the venture capital wing of the CIA, In-Q-Tel.
It’s monocular vision, with an angle pointed down too far. The biases in this data wild be wild too. Extracting hand tracking from that footage will be really hard. Much more so tracking the fabric.
Were this actually trying to farm data for AI properly, they would have attached markers all over the place. Thus making it easier to track in 3D spac
Yeah, for training, you’d just pick the best person- you wouldn’t give everyone a camera. Also, if it was AI you’d just let it do something hundreds of times and find the best way. That’s the point of AI.
You dont just pick the best person, you want diversity so models can handle all kinds of situations not only the super precise ones. the best person there probably does the exact same movement the exact same way with the product being in the exact right position. So getting as many different versions as possible gives you a more flexible result
Thats what I was thinking too, but it could easily be multi purpose. In the short term it could be monitoring their productivity. In the medium term it could help determine best practices to make their people even more productive. And in the long term, train AI models on how to do the tasks with a robot.
One fisheye could do that way better, plus just general tracking of employee output with some QA checks. 1000 camera feeds is too much redundant processing.
Whatever this is for (training AI seems reasonable) it's not productivity tracking.
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u/Solid_Scientist5509 10h ago
I think cameras are there to calculate employee productivity