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The peer review paper requirement puts you in a situation where if your topic of research happen to not be interesting for the reviewers (that you have no control over), you can be a talented student that worked very hard and still fail due to being out of time after multiple successive rejections.

Your supervisor may not understand this until it’s too late, and you may not have the ability to judge your adviser's ability to do so until you are committed.

The main problem is that you were raised in a school system where if you show up, study and do your assignments you are pretty much guaranteed to succeed sooner or later. A PhD is not like that.

> it is a career-ending failure

It depends highly on the field. In history, sure. The point of getting a history PhD is to become a history professor, and you can't do that if you don't get the PhD, and meanwhile history PhDs don't meaningfully open up any other job prospects, so attempting and failing to get a PhD provides negative value.

In CS and many engineering disciplines, there is a long history of people dropping out of PhDs and landing in industry. The industry is therefore much more accustomed to, and therefore accommodating to, people taking this path. Whether it's a maximally efficient use of time is another question, but it's certainly not wasted effort.

But I do agree that it's stressful nonetheless because it still feels like a failure even if it is not actually in reality. I wrote about this when I put down my own PhD journey here [1]. In particular after the control replication (2017) paper, I very nearly quit out of academia entirely despite it being my biggest contribution to the field by far.

[1]: https://elliottslaughter.com/2024/02/legion-paper-history (written without any use of LLMs, for anyone who is wondering)

Your point is valid in many ways. The picture can be a little brighter. The PhD path does not have to be an all or nothing.

1. You can hedge your bets by submitting your work to various conferences of various qualities (without going 3rd-tier, you can bet across 1st-tier and 2nd-tier)

2. You can spend time choosing the professor and the topic before going all in

3. You can seek advice and social interactions within your research group, departement and school

None of this is a silver bullet, but it compounds in the right direction.

PhD programs are very different. The environment Karpathy describes is fairly similar to what I saw as a math PhD in a good school, but not an ivy. My theoretical physics PhD friends had the same setup as I had, but experimentals lived in a different world, long hours in the lab every day, including weekends.

My advisor was well established, tenured prof with a number of students. I had to teach, but the effort was light. We taught large, basic courses that are boring for tenured profs. We usually requested the same 1-2 classes to teach and after the first round had all the materials (homework, quizzes, etc.) and could teach on autopilot. University gave us undergrad graders to grade assignments but I never used them since I wanted to see what my students wrote. Which is a testament that the load was light; if I was drowning I would use all free help I could.

But there was a cult of academia. "Get an academic job or you are a loser" mentality was prevalent. My advisor was disappointed, but OK when I decided to go into industry after PhD, but a friend's (Physics PhD from Harvard, CEO of a profitable startup now) advisor does not talk to him anymore because he did not stay in academia.

And I only realized long after finishing my PhD how incredibly lonely PhD path is. You live in your bubble for years, with minimal interactions outside a few other folks at the same grad school. Stipend was enough for basic living, but not much else. No good vacations, ski trips with friends, etc. And a few somewhat creepy characters that grow in this lifestyle. This is all surmountable, but the mental toughness required is certainly something to keep in mind. I did not have that mental toughness, but was an introvert, which helped a lot. But looking back I see that I also could have gone off the rails. My 2c.

Eh. It's different, but framing it as uniquely challenging seems silly. There are very few other jobs where you don't need to deliver any specific, measurable results for months or years. And your "career-ending" outcome is that you go and get a cozy industry job in the same field because you already have a degree. Now, you might have a difficulty adjusting to that because they will want you to get stuff done.

I have never been more depressed than grad school working for a complete sociopath. Even people working for “normal” PIs suffered. You are so right

Use zotero and betterbibtex. By all means type a comment so you know which ideas came from where but I'm a big advocate of taking notes by hand when you really want to understand something, as opposed to reminding your future self about something you already understand.

Ha! You just made me remember how much I used JabRef (open source bibtex reference app) back in 2004 when I did my PhD.

It was the best/worst 4 years of my life. I studied overseas (uk), met my future wife and got a PhD that really wasn't useful for much to me. Fortunately it was under a scholarship.

Not within a PhD, but as a side project I work on a research project on wikiversity about grammatical gender in French. It does reference a bunch of books and academic works, like probably a hundred I guess. The most tedious work though is to check which nouns are used only in a single gender of do have some epicenic or specific inflection used in the wild and giving a reference that attest that when it's not already so consensual that most general public dictionary would already document the fact. For that the research refers to thousand of webpages. I'm glad that most of the time I just need to drop the DOI, ISBN, or page URL and MediaWiki will handle the filing of the most relevant fields. That's not perfect, it generates the output with many different models currently (some don't have an excerpt field), and some required fields might be left blank, url to pdf won't work, and so on. But all in all it make the process of taking note of the reference quick and not going too much in my way. Creating a structured database out of it can certainly be done later.

This is very good advice for a few reasons:

1. It reduces the odds of missing a key reference in your papers and accelerates the write-up of the (often mandatory) Related Work section

2. It helps you maintain a mental map of the field as your research progresses

Zotero and AI have this covered now. If there's one thing AI is good at it's summarising crappy formatted papers. Never understood the 2 and 3 column thing. Horrendous way to format something.

I have had some fun exhuming my old LaTeX skills and assembling a BibTeX bibliography from which I automatically extract the right entries presented in whichever style is needed for a given paper and for my own (HTML) site. I even publish the collection in Zenodo in case useful to others. I use the 'annote' field for the reminder you suggest.

The lack of good tools to have good research notes with good search is kind of mind-boggling. I have reverted to having a website for myself, a private one that I run on my machine, using mkdocs which comes close to what I would want.

why? like what are you doing with this mega list later? Ive never felt the need for something like this in my research but maybe im missing something

Citeulike [1] was great but is sadly no more.

Add any paper you pick up to your tracking system before you read it. Make that part of your reading ritual.

Save the PDF right away, too. You may later lose access to the journal. Or, CiteULike (where I^Hyou uploaded all those articles) may go away.

[1] https://en.wikipedia.org/wiki/Citeulike

>What was the motivation? Honestly, I was too lazy to get a job and staying in academia for another 3+ years seemed amazing

This is actually how I view academia. "Couldn't get a job"

It really lowered the prestige of a PhD for me. Heck, if I think through my PhD friends... none of them were A students. They were all C-tier.

I'd go further and say it's dangerously untrue. What I advise people is that your results are constantly decaying. Only a rate of progress that exceeds the rate of decay will get you out the door. Decay happens for a number of reasons:

* Your records are never good enough to completely replace your memory of what you did. The longer it takes, the more studies, readings, etc., that you will have to repeat.

* In physical and biological sciences, equipment breaks down, gets taken away, facilities get moved, etc. This stuff happens at a constant rate, and is a pure time cost.

* Technological progress gradually raises the bar for the minimum quality of some results, e.g., in computation. Even "theory" is highly computational these days.

There are also risks of career-ending accidents that can be treated as a constant risk per unit time:

* Your advisor dies, retires, gets promoted to administration, loses funding, changes jobs, gets embroiled in ethical / legal issues, etc.

* Some unexpected new result from another team or industry erases the relevance or novelty of your work.

* You get sick, have family crisis, etc.

* Burnout

Results are the wrong unit of measure. A better KPI is results per unit time. The people who look like they fucked around for 4 years then submitted a brilliant thesis were either working hard all along, or were just brilliant, which I certainly wasn't.

My then-fiancee and I were both grad students. We made a pact to meet at 7:00 every morning in the cafe across from the research building for coffee, to force both of us to stay on a work schedule.

He is obviously talking about computer science. Yes, I know in biology or medicine you can often only access the experimental devices during set hours and the lab may not be accessible 24/7 etc. But in computer science the schedule is mostly free, except for meetings and teaching duties but those are specific time slots not a regular clock-in clock-out job like a cashier or bus driver.

In my part of the world (central Europe), the vast majority of PhD-students is actually employed by the university they aim to obtain the PhD from. So in addition to working on your thesis you most likely have to support other research projects as well as do a lot of teaching. The model of a free PhD student certainly exists, but it is rare.

True, but on the other hand, maybe only a very small subset of people should be doing a PhD.

Kind of feels a bit like

How To Get Rich?

Step 1: be rich

Step 2: you're now rich

Or as a good friend told me when I was starting my PhD: "those of us that finish our PhDs are not the most intelligent, but the most stubborn "

How did you keep the motivation up?

(I tried doing a PhD while working full time, and quit the idea after 3 years.)

Interesting. A couple of questions: - How young are the kids? - How do they behave, especially with essentials like eating and sleeping habits? - Could you carve out a morning and/or evening routine for yourself? - How much outside help could you rely on (grandparents nearby, lovely neighbours...)?

You are right, sir, you should stay away from research. Don't worry, there are others that will handle it.

Linked by Gemini: From https://en.as.com/nfl/these-are-the-lowest-paid-players-in-t...

> The minimum salary for the 2025 NFL season was $840,000

Raise the minimum salary of a Ph.D. student to that level and we have a deal. (The pocket salary, not $830,000 self pay to the university and $10,000 for the pocket of the student.)

Also, the work in NFL is more standardized, all teams play the same games per week, have a similar amount of training time, ...

In a Ph.D. the topic depends a lot of the advisor. It would be like mixing all the sports in the same bag, and for a weird reason the Waterpolo team from Alaska can pick you that are an expert in Tenis.

What would the benefit of that procedure be?

LLMs fall victim to "garbage in, garbage out." Claude can solve open problems if you know what you're doing, but it can also incorrectly convince you it's right if you don't know what you're doing.

A PhD teaches you how to think, how to learn, and how to question the world. That's a vital set of skills no matter what tool exists.

It seems your question largely boils down to: “why do anything when AI could do it instead?”

I think there are many answers to this, not the least of which is that AI can’t really do it instead.

I don’t really know how to optimize for a world where AIs would be smarter than everyone and able to do everything.

If that comes to pass, I guess there won’t be any economic cost to having done my PhD because the entire economy will be AI driven and we’ll hopefully just be their happy pets.

If that doesn’t come to pass, and AIs just remain good at summarizing and remixing ideas, I guess people with experience generating research will still be useful.

Because you may have fun working in a scientific environment and doing research.

I liked my job at the university - independent of the final PhD. I enjoyed what I was doing. Most of the time I also enjoyed writing my dissertation, since I was given the opportunity to write about my stuff. And mostly I could write it in a way how I felt things are supposed to be explained.

Models can solve the problem, but they can't tell you if the problem was worth solving in the first place.

Doing hard things has consistently made me more generally (not only in the narrow hard thing) competent and comfortable with myself.

Why go to the gym if you don't need physical strength? One needs to do something to not degenerate into a miserable state.

Why spend your life doing anything at all? I'm biased on the topic since im writing up atm, but it was, if nothing else, a very itnerseting way to spend 4 years of my life.