I think that’s actually really not a limit.

We don’t teach babies by throwing lots of data at them, instead we teach them by giving them useful data.

The loop I see is: - train on a lot of existing data - run out of useful data - people use ai and give feedback (we’re here) - perform reinforcement learning on the data collected

Loop over the last two steps.

There is already more than enough data available, it’s just not nicely labeled to say if it’s high quality or should be discarded. Those last two steps will implicitly do the labeling.