It's not as simple as stochastic parrot. Starting with definitions and axioms all theorems can be invented and proved. That's in theory, without having theorems

It's not as simple as stochastic parrot. Starting with definitions and axioms all theorems can be invented and proved. That's in theory, without having theorems in the training set. That's thinking models should be able to do without additional training and data. In other words way forward seems to be to put models in loops. Which includes internal 'thinking' and external feedback. Make them use generated and acquired new data. Lossy compress the data periodically. And we have another race of algorithms.