In my case, I turned a career in driver and low-level algorithm coding into a career in AI in <2 years emphasizing the ability to implement AI algorithms in C/C++ and CUDA. That said, when Tensorflow Monkeys can make $300K right out of school, imagine how someone who could bang the metal directly could do...

TLDR: Chance favored the prepared skill set. No fancy degree required, just results.

PS Before that, I blew a boring blind-allocated gig at Google insisting that GPUs were about to play a huge role there a year before they acquired DNNResearch. I even tried to join the very beginnings of the Google Brain team but they didn't have any openings or the budget/willingness to make one for me.

With no evidence whatsoever, I would argue against that. "Top talent" does not equate to "moving into an industry with potential". I think the other comment re TensorMonkeys is valid. How many AI researchers actually understand the ins and out of what they do or the tools they use? Seems to me that AI is/will become abstraction on abstraction etc as AI gets more complex and that means the people using the tech are more and more removed from "first principles", and therefore need to know less and therefore not really "top talent" in my book. Maybe at the start though.

The top end of engineers and researchers in artificial intelligence earn magnificent salaries. That domain is not, itself, the top end of software engineering, it's a specialization of it with its own salary track. You aren't actually comparing like for like here, because most engineers doing work in "artificial intelligence" aren't even pulling down the salary you noted for the top end of plumbing (which is itself wildly unrealistic).

When you say talent you mean Tensorflow monkeys?