The average case of a PhD (even in machine learning) is that a handful of people will read your work, and you'll get cited a few times. That's it.
The analogy I've always used is that researchers are like miners in a gold rush. Most workers take their pickaxe, labour at the rock face, and come away with little more than sore muscles. A lucky few will strike gold (sometimes by looking in the right place, sometimes by working hard, and sometimes by being lucky). You need all those hundreds of people labouring away to find the gold, but the efforts of a single worker matter less than you might think.
If your goal is to maximize your lifetime income, academia is clearly not for you, but neither is the Peace Corps, the clergy, civil service, or anything like that. However, if you can afford to spend a few years trying to make the world a better, more interesting place then grad school isn’t a terrible option; you can always do something else afterward.
- Some do, and we're really bad at figuring out which ones the are, especially ahead of time.
- It's a collective effort. Your thesis and my thesis might not be particularly groundbreaking or influential individually, but each one is a tiny step, more or less in the right direction, towards understanding something. It's mostly a myth that "geniuses" make huge leaps forward, while everyone else muddles around. Most ideas are presaged in the literature for a while before someone puts them together and runs with it.
The large majority of phds collect fewer than 20 citations. Most papers are ready by only a handful of people. "Screaming into the void" is a pretty accurate representation of many phds (including my own).
Working in industry and making money also contributes to humankind. Whatever the company is doing must be of some value in order to make money. So someone who may not have the right motivations to getting a PhD is probably better suited to move into industry sooner rather than later and be the most productive contributor to humanity as possible.
PhD's doesn't contribute new knowledge, they contribute knowledge that can't be proven to be old.
It might sound similar, but it is not. Let me explain the difference:
A person performs a study creating lots of data. If he wanted to contribute to human knowledge he would publish the data with no comments, as he is probably not the best person in the world to analyze this data. If on the other hand he was a PhD he would not publish the data, instead he would publish some pet theories related to the data so that he can build his brand, and most of all he will absolutely not publish the data since it could possibly be used to prove that his pet theories are not relevant or maybe even wrong which would be disastrous for his brand.
Now there are of course PhD's who do the right thing but it doesn't benefit their career at all.
I would argue that, while the pursuit of new knowledge is surely admirable, not all of it can be assumed to meet the high bar of being of "great value to history and humankind".
I can't speak for the person you replied to, but sometimes this is done as a way of disparaging money and the desire to have some, perhaps in the same vein as writing "Micro$oft".
I do hope you're not referring to the google leak. That result is merely unreproducible with classical computers. It isn't currently useful for anything except PR.
Unless you mean something very specific by "Quantum theory" I don't understand how you can even make that statement about such a broad topic. Quantum mechanics are extremely useful.
The analogy I've always used is that researchers are like miners in a gold rush. Most workers take their pickaxe, labour at the rock face, and come away with little more than sore muscles. A lucky few will strike gold (sometimes by looking in the right place, sometimes by working hard, and sometimes by being lucky). You need all those hundreds of people labouring away to find the gold, but the efforts of a single worker matter less than you might think.