In the meantime keep learning and practicing cs fundamentals, ignore hype and build something interesting.
I don't really agree with the reasoning [1], and I don't think we can expect this same rate of progress indefinitely, but I do understand the concern.
If software falls, everything falls.
But as we've seen, these models can't do the job themselves. They're best thought of as an exoskeleton that requires a pilot. They make mistakes, and those mistakes multiply into a mess if a human isn't around. They don't get the big picture, and it's not clear they ever will with the current models and techniques.
The only field that has truly been disrupted is graphics design and art. The image and video models are sublime and truly deliver 10,000x speed, cost, and talent reductions.
This is probably for three reasons:
1. There's so much straightforward training data
2. The laws of optics and structure seem correspondingly easier than the rules governing intelligence. Simple animals evolved vision hundreds of millions of years ago, and we have all the math and algorithmic implementations already. Not so, for intelligence.
3. Mistakes don't multiply. You can brush up the canvas easily and deliver the job as a smaller work than, say, a 100k LOC program with failure modes.
I don’t think that follows at all. Robotics is notably much, much, much harder than AI/ML. You can replace programmers without robotics. You can’t replace trades without them.
We also should end the exploitative nature of globalization. Outsourced work should be held to the same standards as laborers in modern countries (preferably EU, rather than American, standards).