| If you get into it now, you'll probably be on the losing end of a pork cycle [1]. All of the hype is creating overinvestment on the side of "producers" of AI. All that overinvestment will mature at roundabout the same time. When it all hits the market at the same time, they'll have to fiercely compete with each other at the same time as having to deal with "reality" kicking in, i.e. learning the difference between hype and real demand to create real value for real paying customers. There will be massive oversupply. You'd have to find some way to be short that thing, i.e. to somehow take the other side of that trade. You want to be on the receiving end of that investment with no exposure to the crash that will follow (if any). For example, if you had an AI background now, you could start an AI school. Your customers would be people taking the hype at face value. You'd take their money now, but when it later turns out that the skill isn't worth in the job market what they thought it would be, you're not exposed to that. ...that's what acting school does for wannabe Hollywood superstars. Running an acting school for wannabe stars is definitely a better business than trying to actually be a star. [1] https://en.wikipedia.org/wiki/Pork_cycle |
All I can say is, the job market for data science, machine learning engineering and similar is heavily overcrowded. This means that due to competition (lots of supply, not so much demand) salaries will be (a lot) lower than e.g. software engineering. I didn't even bother going into the field, I heard enough horror stories from friends. Several of which got into high prestigious AI companies, for which they had to pass 6+ very challenging interviews and compete against hundreds or thousands of other candidates to get in. Yet, they get paid peanuts compared to what I now rake in as an SWE. When I do 6+ challenging interviews with a company for an SWE job, the least I (can realistically) expect is a TC of > $160k.
Sure, there's these mythical $500k+ salaries for data science / machine learning as well, but they are a lot rarer than for SWE, simply because the market is much smaller for them. So you're playing the game of trying to become a famous football player, where only the top of the top get dream contracts, the rest not in a long shot.
Money is not everything, true, but at some point you have to ask yourself what's worth more; chasing an elusive dream of meaning or focusing a little bit on your well-being as well.
I don't necessarily regret focusing on AI, but from a pragmatic point of view, I rather should have taken a couple more systems and cloud computing classes in hindsight.