> How do you reconcile e.g. AlphaGo with the idea that data is a bottleneck?

Go is entirely unlike reality in that the rules are fully known and it can be perfectly simulated by a computer. AlphaGo worked because it could run millions of tests in a short time frame, because it is all simulated. It doesn't seem to answer the question of how an AI improves its general intelligence without real-world interaction and data gathering at all. If anything it points to the importance of doing many experiments and gathering data - and this becomes a bottleneck when you can't simply make the experiment run faster, because the experiment is limited by physics.