In a general neural network, you can train it on all sorts of data. But there's no causal structure associated with that data. What about if the system understood the assembly space? And rather than guessing what was happening and training on those images and not understanding those features, it could understand them better. I wonder if that is actually the origin of intelligence or how we'll crack intelligence because we need to create an entire graph of events.