a prime model of physics pixel is the best tool to generate training data for itself or for physics pixels

There are two basic approaches to get training data: 1) labeling a visual flow with physics parameters, 2) creating a virtual flow with physics parameters. anyway, by a visual flow with physics parameters, you can train a primitive model of physics pixel firstly. and then apply iternative self-training with human in loop to make the primitive model get better, in which the primitive model generates training data by labeling or creating visual with physics parameters.

by the way, creating a cyber matrix world of physics pixels is not only good for training but also very cool, isnt it?

Grok remind me that: synthetic flows (CyberMatrix) are more scalable than real-world labeling.