Remember that Hinton and other deep learning pioneers labored in obscurity for over a decade, probably closer to two.
Techniques like deep learning were out of fashion for a long time. Google was making tons of money on non-AI techniques; I remember Sergey Brin saying he was surprised by the deep learning breakthroughs in 2012 because the conventional wisdom was that "AI doesn't work".
And people who did Ph.D's under Hinton and others 10+ years ago also were not following trends.
You have to take risk to get reward. The way to do that now would also be to labor on an obscure subfield of AI that isn't certain to even work, let alone become commercially viable. (And there are plenty of people who did that on fields that looked more promising than deep learning 10+ years ago.)
There's definitely a need for new AI techniques, see this other current story:
Not to also mention that much of this would still be in the stone age if it were not for MUCH faster and accessible hardware (GPU/TPU/QPU/XPU), what I think makes up for the high salaries is that these people are quite aware of how to allocate for hardware on the ML/RL/AI training side and how to allocate time for the people responsible for tagging and optimizing models. They know how to reach the objective(s) in training/testing/optimizing already.
Techniques like deep learning were out of fashion for a long time. Google was making tons of money on non-AI techniques; I remember Sergey Brin saying he was surprised by the deep learning breakthroughs in 2012 because the conventional wisdom was that "AI doesn't work".
And people who did Ph.D's under Hinton and others 10+ years ago also were not following trends.
You have to take risk to get reward. The way to do that now would also be to labor on an obscure subfield of AI that isn't certain to even work, let alone become commercially viable. (And there are plenty of people who did that on fields that looked more promising than deep learning 10+ years ago.)
There's definitely a need for new AI techniques, see this other current story:
https://news.ycombinator.com/item?id=21104037