Honest question: where do you learn advanced stuff if not in a graduate school? Academia undoubtedly sucks if one mainly takes money or career prospects into account. But among people who do challenging and sexy stuff (including in the industry) phd seems to be the norm, not the exception. One might object that phd has become unnecessary because nowadays all the relevant information is online but learning without the help of a community and a mentor is hard.
You absolutely do not need a PhD for industry unless you want an R&D job in a handful of domains. A PhD is not simply learning more facts about a particular topic. It's an apprenticeship for conducting independently directed academic research. There are so many topics that you can not just learn from reading some online sources e.g. most experimental work. Most of the time spent in a typical PhD program is spent trying to solve problems that have no easy answers and no easy guidelines to follow. While you can definitely gain similar knowledge and experience in an industry setting, you almost never have the freedom to take the 3+ years often necessary to explore a narrow topic, struggle and fail repeatedly, be faced with and overcome crushing doubt and frustration, and do so in a generally supportive community.
> You absolutely do not need a PhD for industry unless you want an R&D job in a handful of domains.
I know Phd.s at {MSFT, Google, Uber, Deepmind, GE, P+G} research divisions. I don't know anyone who works at those who does not have a doctorate. So I would say this applies to more than 'a handful of domains' -- If you want to do research, you should plan on having a doctorate, even in industry. The majority of data scientists I know have doctorates, even if that strikes me as (generally) overkill.
Otherwise, I agree with the rest of your statements.
You'd have to find a community adjacent to your interests.
I like programming languages and functional programming and haven't had trouble finding things to learn and people to help me, mostly through the Haskell community. You have everything from completely disorganized but perfectly accessible help like IRC channels and mailing lists to things like type theory meetups and study groups (if you live near enough people with those interests). It'll be easier in the Bay Area or New York, but moving here has lots of other benefits and isn't nearly as constrained as going to grad school.
Once you know enough on your own you can parlay that into a "sexy" job if you're so motivated. I interned at a company that had their own internal language, for example, and one of the main people working on their compiler had a philosophy degree and (unless I'm misremembering) no grad school whatsoever. It's more difficult because interesting jobs are relatively rare and a lot of places (especially ones close to academia) are still disproportionately concerned with credentials but it's possible.
As long as you can concretely demonstrate your capabilities, you have a chance at progressive companies without credentials. This still isn't true within academia itself, at many government roles or at big rules-bound corporations, but it is possible within the "core" tech industry.
>where do you learn advanced stuff if not in a graduate school?
From a degree-less "researcher" whose published in neuroimage, i'd say, wherever you can and as you learn more you get better at knowing where to start when searching/who to talk to/who to work with.
>Academia undoubtedly sucks if one mainly takes money or career prospects into account.
Or tired of trying to get your lab to work on more on the cutting edge of the technology vs the grant hamster wheel and status games or sucking up to people who clearly don't have any understanding of modern technology/physics/mathematics/techniques on a intimate level and squandering resources because they can, and figure you can get what you want done faster with more resources you can more directly allocate.
>…learning without the help of a community and a mentor is hard.
It's going to be "hard" no matter what path you take imo, but that what makes the journey of knowledge fun, because of that small chance you might actually figure something out you never knew before is worth ones time?
learning while getting your PhD is maybe 1/10 learning from classes and 9/10 creating new knowledge and reading papers; I think I am being generous to classes here. You become the world expert by going extremely deep in a very narrow topic and actually creating the knowledge around the topic. You don't need to be a PhD candidate to do this.
For credibility, I was a Computer Science PhD candidate 4 years ago.
I think this is good advice in general. But I doubt that the most effective way to follow it is to devote evenings after your 200k+ corporate job to studying.
